Chapter V 

 

Docket No. PA02-2-000 V-1 Price Manipulation in Western Markets 

V. The Influence of Electricity Spot Prices on Electricity 

Forward Prices 

Summary of Results 

The vital link between the spot price and forward price for a 

commodity is the ability to store the commodity. In essence, someone 

can meet future needs by purchasing the commodity now and storing it 

for future consumption. As a result, the forward price that someone is 

willing to pay will approximate the cost of purchasing plus the 

carrying cost involved with stockpiling and net of the risk associated 

with not holding the physical commodity. Since electricity has few 

storage applications, we would expect to see little or no relationship 

between spot electric prices today and the forward price of electricity. 

Instead, forward prices should mostly reflect a buyer’s expectations of 

prices in the future. Since natural gas is the marginal fuel for 

producing electricity in the West, forward gas prices should, in large 

part, explain forward electricity prices. Our analysis shows, however, 

that the forward power contracts negotiated during the period 2000–

2001 in the western United States were influenced by then-current spot 

prices, presumably because spot power prices influenced buyers’ and 

sellers’ expectations of spot prices in the future. The influence of spot 

prices on forward prices was the greatest for forward contracts with 

the shortest time to delivery (1-2 years) and varied by location. While 

Staff has found a statistically significant relationship, the magnitude of 

the impact is limited (that is, the impact of spot power prices on longterm power prices is clearly not dollar-for-dollar). Rather, a reduction 

of about one-third in the price of a 2-year forward contract would 

require a finding that spot power prices were three times above the just 

and reasonable level. 

Background 

The relationship between electricity spot prices and long-term contract 

prices has been the subject of debate since Enron filed for bankruptcy 

in December 2001. Questions have been raised in Congress and the 

media about whether Enron manipulated the spot market to influence 

the West forward market. 

The Commission’s February 13, 2002 Order establishing the factfinding investigation specifically directed FERC Staff to look into 

whether manipulated spot prices resulted in unjust and unreasonable 

long-term power sales contracts. 
Chapter V 

 

Docket No. PA02-2-000 V-2 Price Manipulation in Western Markets 

In addition, a number of utilities1 filed complaints with the 

Commission alleging that dysfunctions in the California electricity 

spot markets caused long-term contracts negotiated in the bilateral 

markets in California, Washington, and Nevada to be unjust and 

unreasonable. The complainants seek the extraordinary remedy of 

contract modification. The Commission issued an Order on April 11, 

2002 consolidating these complaints and set them for an evidentiary 

hearing.2 Subsequently, additional complaints were set for hearing. 

Two studies that estimated the electricity spot/forward price 

relationship were filed in testimony in the proceeding. 

On July 2, 2002, Snohomish submitted Mr. Robert McCullough’s 

Direct Testimony. Mr. McCullough alleges a link between short-term 

prices and the prices of long-term contracts.3

 Mr. McCullough’s 

analysis found a large, significant correlation between prices for shortterm and long-term contracts. 

On August 27, 2002, Mr. McCullough’s analysis was challenged by 

Mr. William W. Hogan and Mr. Scott M. Harvey.4

 Representing 

Morgan Stanley Capital Group, Inc., Mirant Americas Energy 

Marketing, L.P., American Electric Power Service Corporation, and 

Reliant Energy Services in the same proceedings, Mr. Hogan and Mr. 

Harvey testified that no significant correlation can be demonstrated 

between spot and long-term power prices. 

 

1

Nevada Power Company (Nevada Power) and Sierra Pacific Power Company 

(Sierra Pacific), Southern California Water Company (SCWC), and Public Utility 

District No. 1 Snohomish County, Washington (Snohomish). 

2

Consolidated proceeding: Nevada Power Company and Sierra Pacific Power 

Company v. Enron Power Marketing, Inc., El Paso Merchant Energy, and American 

Electricity Power Services Corporation; Nevada Power Company v. Morgan Stanley 

Capital Group, Calpine Energy Services, Reliant Energy Services, and Mirant 

Americas Energy Marketing, L.P.; Southern California Water Company v. Mirant 

Americas Energy Marketing, L.P.; and Public Utility District No. 1, Snohomish 

County, Washington v. Morgan Stanley Capital Group, Inc.—Docket Nos. EL02-28-

000, EL02-33-000, EL02-38-000, EL02-29-000, EL02-30-000, EL02-32-000, EL02-

34-000, EL02-39-00, EL02-43-000, and EL02-56-000. 

3

Testimony of Robert McCullough, Exh. SNO-17. 

4

Prepared Answering Testimony of Scott M. Harvey and William W. Hogan, Exh. 

No. MSC-65. 
Chapter V 

 

Docket No. PA02-2-000 V-3 Price Manipulation in Western Markets 

Comparison of the Two 

Studies 

McCullough used different econometric models than Harvey and 

Hogan to estimate the spot/forward price relationship. 

McCullough used a simple regression model to estimate the 

relationship between electricity forward and spot prices. This model 

uses only two variables: an explanatory variable and a dependent 

variable. McCullough attempted to estimate how the change of 

electricity spot prices (explanatory variable) correlates with electricity 

forward prices (dependent variable). By running this simple regression 

model with NYMEX strip prices5 and spot prices from Energy 

Markets Report, McCullough estimated that, at the Palo Verde trading 

hub, 51 percent of the variance in the forward power price can be 

explained by the variance in the spot power price, and at the 

California-Oregon Border (COB) trading hub it is 40 percent. 

McCullough concluded that the change in the daily price was very 

closely correlated to the change of the forward price.6

Harvey and Hogan made several refinements to the McCullough 

analysis. First, they included forward gas prices and other independent 

variables designed to capture monthly and seasonal effects in their 

regression analysis. Second, they performed several analyses using 

alternative measures of forward power prices including NYMEX 

futures prices and forward prices reported by TFS, a major 

independent broker. Third, they employed econometric techniques 

specifically designed to address time-series data with “serial 

correlation.”7 Their analyses generally show small and statistically 

insignificant impacts of spot power prices on forward power prices.8

Neither study has the benefit of reliable data on long-term power sales 

contracts in the West during 2000–2001. There was little or no 

transaction volume in the NYMEX electricity futures market after 

February 2000. The electricity futures closing prices published by 

NYMEX until the product was delisted in February 2002 were not 

based on actual trading on the exchange. NYMEX maintained its 

index by surveying prices of bilateral trades. 

 

5

NYMEX strip prices are an average of the daily settlement prices of the next 12 

months of futures contracts. 

6

Testimony of Robert McCullough, Exh. SNO-17, pp. 86-87. 

7

Serial correlation is discussed at more length in Appendix V-D. 

8

Prepared Answering Testimony of Scott M. Harvey and William W. Hogan, Exh. 

No. MSC-65, p. 139, line 22 to p. 140, line 2. 
Chapter V 

 

Docket No. PA02-2-000 V-4 Price Manipulation in Western Markets 

Staff’s Analysis 

To help resolve the debate on this important issue, Staff performed its 

own statistical analysis with the help of an independent outside 

consultant, Robert S. Pindyck,9

 a nationally recognized 

econometrician with a specialty in energy futures markets, and 

consultants from Analysis Group/Economics. Our methods, data, 

models, and results are presented as follows: the basic economic logic 

and statistical methods that Staff employed, the data that Staff relied 

on for the analysis, the regression model used in detail, and the main 

results. Detailed results are provided in the appendices to this chapter. 

Basic Economic and 

Statistical Methodology 

Economics 

For a storable commodity, such as crude oil, there is a clear 

relationship between spot and forward (or futures) prices that depends 

on the flows of benefits to producers and consumers from holding 

inventories.10 Because of electricity’s limited storability, the 

relationship between spot and forward prices is not as clear. Instead, 

forward power prices should largely reflect expectations of future 

demand and supply conditions. 

Expectations, however, are often difficult to measure. In electricity 

markets, forward prices for fuel can provide an important measure of 

expectations about future electricity costs. In the western United 

States, natural gas is the marginal fuel for electricity in the short term, 

particularly in California and even in the Northwest when hydro water 

levels are low (as they were in 2000–2001), and in the long term for 

the construction of new generating capacity. As a result, forward gas 

prices should help explain forward electricity prices to the extent that 

prices reflect costs. The futures market for gas delivered to Henry Hub 

provides transparent signals about future input prices. Forward prices 

 

9

Robert S. Pindyck is a professor of Economics and Finance, Sloan School of 

Management, Massachusetts Institute of Technology. 

10See, for example, B. Routledge, D. Seppi, and C. Spatt, “Equilibrium Forward 

Curves for Commodities,” The Journal of Finance, v. LV, no. 3, June 2000, 

pp. 1297-1338, and R. Pindyck, “The Dynamics of Commodity Spot and Futures 

Markets: A Primer,” The Energy Journal, v. 22, no. 3, June 2001. 
Chapter V 

 

Docket No. PA02-2-000 V-5 Price Manipulation in Western Markets 

for delivery of gas to specific locations in the West are less 

transparent. Nonetheless, market participants had access to forward 

market price quotations for gas to be delivered in the western United 

States, and could use these to project likely power prices. 

In power markets, a relationship between spot and forward prices can 

exist when current spot prices convey information about spot prices in 

the future. For example, if one component of the current spot price 

represents market “dysfunction,” market participants might use current 

spot prices to formulate expectations about future dysfunction. 

Statistical Methodology 

We tested the relationship between forward and spot power prices 

using multiple linear regression, because there are many factors that 

potentially explain forward power prices. Multiple linear regression is 

a statistical method for decomposing the influence of different factors 

(independent variables) on a variable of interest (dependent variable). 

We seek to explain forward power prices as a function of current spot 

prices, forward gas prices, and seasonal factors. The forward gas price 

is the fundamental factor that drives the forward power price in the 

western United States because gas is the short- and long-term marginal 

fuel. Controlling for the forward gas price, we can test whether the 

current spot price can explain any portion of the variation in forward 

power prices. 

We also include dummy variables to capture seasonal effects.11 Many 

seasonal factors influence energy markets. On the supply side, 

hydroelectric resources vary seasonally. On the demand side, weather 

varies seasonally and influences consumption. A spot price that 

appears high in the spring may be normal for the summer. By 

including season dummy variables, we attempt to isolate the effect of 

abnormal spot price movements on forward prices. 

Most of our results are based on ordinary least squares (OLS) 

regression, but we employed several other linear regression techniques 

to address specific econometric issues. 

 

11Dummy variables are the standard way of representing binary (yes/no) effects in 

regressions. The dummy variable for a season takes the value of 1 if the observation 

in question occurs during that season and is 0 otherwise.
Chapter V 

 

Docket No. PA02-2-000 V-6 Price Manipulation in Western Markets 

Data 

We requested data from wholesale sellers in the West on their 

electricity transactions during 2000 and 2001.12 The data request was 

targeted at all marketers active in the West and compliance with the 

request was nearly universal. 

The responses to the Staff data request were provided in electronic 

templates. These responses left some room for interpretation. As 

discussed below, we spent a considerable amount of effort in 

comparing different parties’ responses and verifying responses against 

written contracts and other documentation provided by most, but not 

all, sellers. To the best of our knowledge, this is the most 

comprehensive database of forward power contracts for the period and 

locations in question. 

Sample Size 

In our March 5, 2002 Data Request, we asked market participants to 

report all of their short-term, monthly, and long-term energy sales. We 

defined short-term sales as transactions of a week or less. Monthly 

sales were defined as transactions with a period of 1 month. Long-term 

sales were defined as transactions with a contract duration of 1 year or 

more. We focused our analysis exclusively on long-term contracts.

The data reflect contracts for delivery during peak, off-peak, and all 

hours. The majority of contracts in the database are for peak deliveries. 

In addition, by definition, peak hours cover the periods of highest 

demand and hence are the most economically significant. Therefore, 

our analysis relies on contracts for peak delivery exclusively. 

Staff received data on long-term transactions (a year or more in 

duration) that either included the period 2000–2001 or were signed 

after January 2000. We included in our analysis contracts signed from 

the beginning of 2000 through March 2002, when the data request was 

issued. For this 27-month period, we have 2,652 unique contracts for 

the 5 major delivery locations on which we focus our analysis. 

We considered two major subperiods: the period from January 2000 

leading up to and including the period of high Western power prices, 

and the period after June 19, 2001 (when West-wide price mitigation 

 

12Staff data request to all jurisdictional sellers and all nonjurisdictional sellers in the 

West issued March 5, 2002 in Docket PA02-02. 
Chapter V 

 

Docket No. PA02-2-000 V-7 Price Manipulation in Western Markets 

went into effect)13 through March 2002. As Table V-1 demonstrates, 

the number of observations varies by location and period. The first 18 

months account for 1,066 observations, or 40.2 percent of the total. 

The last 9 months account for 1,586 observations, or 59.8 percent of 

the total. 

Table V-1. Sample Size by Region and Period Definition 

Hub 1/1/00 – 6/30/01 7/1/01 – 3/31/02 

Mid-C/COB 199 163 

NP15 136 429 

SP15 314 635 

PV 417 359 

All Hubs 1,066 1,586 

Hubs and Duration Classes 

Our analysis considered contracts at the five main trading hubs in the 

West—COB, Mid-Columbia (Mid-C), Palo Verde (PV), and 

California Independent System Operator (ISO) zones NP15 and SP15. 

We treat Mid-C and COB as a single hub based on the high correlation 

of prices at these two locations.14

As discussed above, one key issue that we sought to address is how the 

relationship between spot and forward power prices changes with time 

to delivery. To simplify our analysis of this issue, we grouped 

contracts into time-to-delivery bins.15 We initially assigned contract 

duration classes corresponding roughly to the time between each 

contract’s signing date and the midpoint of its delivery window 

rounded to the nearest year—e.g., a contract for 10 years of deliveries 

signed and commencing today was assigned a duration of 5. 

 

13The June 19, 2001 Order marks the date when all sellers in the western United 

States were subject to a must-offer requirement and price caps. See 95 FERC at 62, 

558.

14In addition, we performed statistical analyses in which we tested whether the 

relationship between spot and forward prices at the two locations was different. We 

could never reject the null hypothesis that the relationship at the two hubs was the 

same. 

15Alternatively, we could have used more complicated nonlinear regression 

techniques in which we allowed various model coefficients to depend on time to 

delivery. 
Chapter V 

 

Docket No. PA02-2-000 V-8 Price Manipulation in Western Markets 

Forward Gas and Electricity Spot Price Data 

We relied on two different commercially available databases for our 

independent variables. We obtained data on forward gas prices for 

various locations in the West from TFS, an independent power and gas 

broker16 that has collected the most complete forward gas quotes 

covering the period and locations in question. Staff also obtained the 

forward gas prices that Williams and Enron used to price their own 

trades. Limited forward gas prices from Morgan Stanley are publicly 

available.17 We have verified that the TFS quotes are broadly 

consistent with the forward curves used by these major market 

participants.18 It is useful to know that expectations about forward gas 

prices were roughly similar among major market participants. For our 

analysis, however, we used TFS data because of their independence. 

The long-term transaction data used in our analysis are for periods of 1 

year or more. The TFS forward gas quotes are for delivery periods of 1 

month. In our regression analysis, we use averages of these monthly 

gas prices calculated over the entire delivery period of each forward 

power contract. 

Because gas and electricity are traded at slightly different locations, 

we had to decide which forward gas price to assign to the forward 

power contracts at each location. Our assumed correspondence is as 

follows: 

Power Trading Hub Relevant Gas Hub Price

SP15 Topock 

NP15 Malin 

COB Malin 

Mid-Columbia Sumas 

Palo Verde Permian 

For spot power prices, we used the on-peak firm power prices reported 

by Bloomberg. For the two delivery locations inside the California 

ISO (NP15 and SP15), we compared the Bloomberg prices to the 

average of the hourly day-ahead prices for peak hours of the California 

Power Exchange (PX) during the period when the PX was still 

operating. The Bloomberg prices are consistent with the PX prices. 

 

16Information about TFS Brokers is available at http://www.tfsbrokers.com/. 17See Harvey and Hogan, op. cit., note 4. 

18The details of this comparison are discussed in Appendix V-B. 
Chapter V 

 

Docket No. PA02-2-000 V-9 Price Manipulation in Western Markets 

Audit Process and Results 

We performed a number of initial quality checks on the transaction 

data we collected and contacted respondents to resolve problems with 

the data. We undertook a comprehensive audit of the filed data by 

comparing reported transaction data with reported actual contracts and 

contract confirmations.19

We audited all contracts that were supported with appropriate 

documentation. Auditable transactions make up about 59 percent of 

the total number of transactions.20 Once we verified the sales data for 

these auditable transactions, we compared the results of a statistical 

analysis that used just the audited data with the results of an analysis 

that used all transactions.21 The regression results using the auditedonly transaction data and the all-transaction data generally are not 

significantly different statistically. Therefore, we concluded that 

including the remaining unaudited data did not change our results and 

decided that further review of the data was not necessary. 

Regression Specification 

Definition of Sample Period 

Our primary analysis covers the 18-month period from January 2000 

through June 2001. The long-term transaction data we collected cover 

the period from January 1999 to March 2002. We focused our 

attention on the period through June 2001 because of the West-wide 

price mitigation put in place beginning June 19, 2001. We examined 

the period after June 2001 separately to assess whether the relationship 

between spot and forward power prices changed with this change in 

market structure. 

 

19The details of this audit are discussed in Appendix V-A. 

20Table V-A2 in Appendix V-A shows the breakdown of documented and 

undocumented contracts by seller. 

21This analysis is shown in Appendix V-A, Tables V-A3 and V-A4. 
Chapter V 

 

Docket No. PA02-2-000 V-10 Price Manipulation in Western Markets 

Basic Equation 

Our regressions have the following general form: 

log( ) log( ) log( ) FP a b SP c FG e ijt ij ij it ij ijt ijt = ++ +q + (1) 

For example, FPijt is the forward electricity price in year 2003 (time t) 

for delivery at Palo Verde (location i) in year 2008 (time j), SPit is the 

spot price at Palo Verde in 2003, and FGijt is the forward gas price in 

2003 for delivery at Permian in 2008. Factor q controls for seasonal 

variations22 and eijt captures any remaining unexplained component of 

FPijt. 

We estimate equation (1) in logs. A log specification has a number of 

desirable properties in the context of estimation such as ours. In 

particular, it captures a constant proportional relationship between the 

dependent and independent variables over a wide range of prices. For 

example, it assumes that an increase in spot power prices from $100 to 

$110 has the same percentage impact on forward power prices as an 

increase from $10 to $11.23 When equation (1) is specified in logs, the 

coefficient on the spot electricity price, bij, is the elasticity of forward 

electricity prices with respect to spot electricity prices. The elasticity is 

the ratio of the percentage change in one variable with respect to the 

percentage change in another variable. 

Aggregation 

As discussed above, we examined data for five hubs and a number of 

duration classes. After some preliminary analysis, we decided to treat 

COB and Mid-Columbia as a single hub. In addition, we were able to 

obtain stable and precise results by aggregating the duration into three 

classes: (1) contracts with average times to delivery of less than 2 

 

22We define seasons quarterly (i.e., spring is March to May, summer is June to 

August, fall is September to November, and winter is December to February). 

23There are technical reasons for preferring a log specification. The error for 

regressions based on price data usually is thought to be proportional to price, i.e., a 

$10 error for a $100 price is equivalent, by some measure, to a $1 error for a $10 

price. If the error is in fact proportional to the level of prices, specifying the 

estimation in logs guarantees that the individual elements of the error are 

homoscedastic, i.e., equal in variance, and hence that our parameter estimates are 

unbiased and efficient. In other words, a log specification guarantees that our 

parameter estimates are as accurate and precise as possible. If the elements of the 

error are not homoscedastic, not only are parameter estimates from OLS regression 

inefficient, but estimated standard errors are biased and hence can lead to incorrect 

statistical inference. For a discussion of these issues see R. Pindyck and D. 

Rubinfeld, Econometric Models and Economic Forecasts, 4th edition, New York: 

McGraw-Hill, 1998, pp. 146-152. 
Chapter V 

 

Docket No. PA02-2-000 V-11 Price Manipulation in Western Markets 

years, (2) contracts with average times to delivery of 3 to 4 years, and 

(3) long-term contracts with average times to delivery of 5 years or 

greater.24

Instrumental Variables 

Statistical inference using OLS regression rests on a set of 

assumptions. One assumption is that the error, i.e., the component of 

the dependent variable that is not explained by the statistical model, is 

uncorrelated with any of the independent variables. Given that forward 

gas and power prices are simultaneously determined, i.e., the forward 

gas price is a major input to the generation of electricity and the 

generation of electricity is a major source of demand for gas, this 

assumption may not hold in our case. Hence, estimation of equation 

(1) may show a correlation between forward gas and power prices, but 

that correlation cannot be interpreted as causal. 

We address this econometric issue using a technique known as 

instrumental variables (IV) estimation,25 which attempts to break the 

circle of simultaneity by using proxy variables, or instruments, that are 

not plagued by the same simultaneity problems. “Good” instruments 

have two characteristics: (1) they are exogenous, i.e., they are 

uncorrelated with the error, and (2) they are correlated with the 

variable for which they are instruments. 

Our instrument for the forward gas price was the contemporaneous 

forward gas price at Henry Hub. Henry Hub, near the production 

basins along the Gulf Coast, is a large and liquid trading hub. Gas 

originating at or near Henry Hub has a variety of uses throughout the 

United States, including electricity generation, chemical processing, 

and heating. Demand for gas for electricity generation in the western 

United States should have relatively little impact on Henry Hub prices, 

and the Henry Hub forward price therefore meets the first criterion of a 

good instrument. With respect to the second criterion for a good 

instrument, because there is some transportation between Henry Hub 

and locations in the West, Henry Hub prices are usually correlated 

with prices in the West. 

Absent the ability to store electricity, there is no reason to believe that 

current spot power prices are influenced by expectations about future 

gas and power prices as reflected in forward prices, so we treat spot 

power as exogenous in our estimation, i.e., we do not instrument for it. 

 

24Detailed results based on the disaggregated data are presented in Appendix V-D. 25See R. Pindyck and D. Rubinfeld, op. cit., Chapter 7. 
Chapter V 

 

Docket No. PA02-2-000 V-12 Price Manipulation in Western Markets 

Under the assumption that a set of instruments is “valid,” the extent of 

any bias due to simultaneity can be assessed by comparing 

instrumental variables and ordinary least squares parameter 

estimates.26 When these estimates are close, any presumed 

simultaneity problem is negligible. In the next section, we present the 

regression results using both ordinary least squares with and without 

instrumental variables. Our estimates tell us that any simultaneity 

problem is negligible. Therefore, we believe that the results using the 

ordinary least squares method are appropriate for use in the long-term 

power contract proceeding. 

Regression Results 

Our analysis is summarized below. We performed separate analyses 

for the periods before and after West-wide price mitigation was 

introduced. The subsequent section discusses a few minor extensions 

and modifications of our analysis. 

“During” Period Results Summary 

We found that spot power prices influence forward power prices in a 

statistically significant and economically important way. In the 

simplest formulation, in which we estimated a single average elasticity 

for all contracts of different times to delivery and different locations, 

the elasticity is 0.07. This formulation masks substantial variation in 

the elasticity by region and time to delivery—the longer the contract 

duration, the lower the impact of spot market prices upon the forward 

price. 

Table V-2 shows results based on an analysis that combines data from 

all five trading hubs, and shows the effect of time to delivery. As 

expected, the effect declines with time to delivery. Using ordinary 

least squares, the point estimates of the spot power coefficients range 

from 0.05 to 0.33. These estimates imply that for each 10-percent 

increase in the spot price, forward power prices rose by approximately 

0.5 percent to 3.3 percent. These effects are larger for contracts with 

short times to delivery than contracts with longer times to delivery. 

 

26This comparison can be formalized as a Hausman test. See R. Davidson and J. 

MacKinnon, Estimation and Inference in Econometrics, New York: Oxford 

University Press, 1993. 
Chapter V 

 

Docket No. PA02-2-000 V-13 Price Manipulation in Western Markets 

Table V-2. Spot Power Coefficient by Time-to-Delivery Class: “During” 

Period 

Time-to- Ordinary Least Squares (OLS) With Instrumental Variables (IV)

Delivery 

Class 

Spot Power 

Coefficient 

Standard 

Error 

t-Statistic Spot Power 

Coefficient 

Standard 

Error 

t-Statistic Number of 

Observations

1-2 Years 0.33 0.03 9.80 0.27 0.04 6.34 451 

3-4 Years 0.12 0.02 6.54 0.11 0.02 5.73 398 

5-8 Years 0.05 0.01 3.36 0.06 0.01 4.18 217 

The regression results with instrumental variables are generally close 

to those without instrumental variables. This may indicate that 

simultaneity is not a significant concern. Alternatively, the results may 

indicate that, even if the forward gas price is endogenous, it does not 

bias our estimate of the coefficient on spot power. 

Table V-2 gives point estimates, standard errors, and t-statistics for the 

spot power elasticities. The standard error measures the precision of 

the estimate, i.e., the smaller the standard error the more precise the 

estimate. The standard error of the OLS estimate for duration class 1-2 

years is 0.03. A one standard error band around the point estimate 

defines a 68-percent confidence interval, i.e., there is a 68-percent 

probability that the “true” elasticity (i.e., the one we are attempting to 

estimate) lies between 0.30 (0.33 – 0.03) and 0.36 (0.33 + 0.03). 

Naturally, our best estimate is in the middle of this range. 

The t-statistic, which is commonly used to assess whether a parameter 

estimate is statistically significantly different from zero, is simply the 

point estimate divided by the standard error. Statistical significance is 

usually measured at the 90- or 95-percent confidence level. A 

coefficient is considered statistically significant at the 95-percent 

confidence level if the value of zero is not within a band around the 

coefficient value of 1.96 standard deviations. For example, for the 

OLS for duration class 1-2 years, the 95-percent confidence band is 

.33 plus or minus (1.96 times .03 = .0588) or between .2712 and .3888. 

All of the parameter estimates in Table V-2 are statistically significant 

at the 95-percent level. 

Table V-3 shows disaggregated results by hub. The OLS and IV 

coefficients are generally close considering the precision of the 

estimates. Most estimates of the spot power coefficient are statistically 

significant at the 90-percent level or higher. For most hubs, we 

observe the expected pattern of the magnitude of the coefficient on 

spot power falling with time to delivery. 

The significance of these results is weakest for contract duration class 

5-8. Only for the Palo Verde hub are these results significant at the 95- 
Chapter V 

 

Docket No. PA02-2-000 V-14 Price Manipulation in Western Markets 

percent level. For the other hubs in the 5-8 class, the estimates are not 

significant at the 90-percent level. 

Since the effects in Table V-3 seem to vary by location, any policy 

conclusions should be based on the coefficient for the relevant 

location. 

Table V-3. Spot Power Coefficient by Time to Delivery and Hub: “During” Period 

Hubs Time-to- Ordinary Least Squares (OLS) With Instrumental Variables (IV)

Delivery 

Class 

Spot Power 

Coefficient 

Standard 

Error 

t-Statistic Spot Power 

Coefficient 

Standard 

Error t-Statistic

Number of 

Observations

1-2 Years 0.38 0.09 4.16 0.21 0.13 1.66 101 

3-4 Years 0.13 0.04 3.12 0.19 0.05 3.58 62 Mid-C/ 

COB 

5-8 Years (0.00) 0.03 (0.13) (0.01) 0.03 (0.41) 36 

1-2 Years 0.22 0.13 1.64 0.29 0.14 2.10 40 

NP15 3-4 Years 0.14 0.04 3.16 0.14 0.05 3.01 72 

5-8 years 0.06 0.05 1.33 0.06 0.05 1.20 24 

1-2 Years 0.38 0.06 6.58 0.40 0.06 6.90 221 

PV 3-4 Years 0.09 0.04 2.37 0.08 0.04 2.14 122 

5-8 years 0.07 0.02 3.36 0.07 0.02 3.35 74 

1-2 Years 0.23 0.08 2.99 0.14 0.08 1.69 89 

SP15 3-4 Years 0.07 0.03 2.33 0.07 0.03 2.28 142 

5-8 years 0.04 0.03 1.29 0.04 0.03 1.35 83 

“After” Period Results Summary 

Next, we examine whether the relationship between spot and forward 

power prices changed after the spot market prices stabilized following 

the introduction of West-wide price mitigation. Tables V-4 and V-5 

show these results for the July 2001 to March 2002 period in the same 

format as Tables V-2 and V-3. They generally show a persistence of 

the effects found during the crisis, i.e., statistically significant positive 

elasticities of the forward price with respect to the spot price. 

Table V-4. Spot Power Coefficient by Contract Duration Class: “After” Period 

Time-to- Ordinary Least Squares (OLS) With Instrumental Variables (IV)

Delivery 

Class 

Spot Power 

Coefficient 

Standard 

Error 

t-Statistic Spot Power 

Coefficient 

Standard 

Error t-Statistic 

Number of 

Observations

1-2 Years 0.12 0.02 7.15 0.13 0.02 7.41 887 

3-4 Years 0.12 0.02 7.12 0.14 0.02 7.35 473 

5-8 years 0.15 0.02 6.83 0.17 0.02 7.22 226 

TableV-4 does not show the decline in elasticity with contract duration 

observed in Table V-2. On average, the point estimates are smaller 

than those in Table V-2. 
Chapter V 

 

Docket No. PA02-2-000 V-15 Price Manipulation in Western Markets 

The results in Table V-5 show elasticities that are sometimes smaller 

and less significant than those in Table V-3, but in other cases the 

opposite is true. There are regional variations. The SP15 elasticities 

have larger t-statistics in the “after” period. Several large elasticities 

estimated for shorter term contracts (0.35 for Mid-C/COB and 0.38 for 

PV) in Table V-3 are absent from Table V-5. The largest elasticity 

after the price mitigation is for class 3-4 years at Mid-C/COB. It is 

unclear why this is the case. 

Table V-5. Spot Power Coefficient by Hub and Duration: “After” Period 

Hubs Time-to- Ordinary Least Squares (OLS) With Instrumental Variables (IV)

Delivery 

Class 

Spot Power 

Coefficient 

Standard 

Error 

t-Statistic Spot Power 

Coefficient 

Standard 

Error t-Statistic

Number of 

Observations

1-2 Years 0.03 0.05 0.67 0.05 0.05 1.05 91 

3-4 Years 0.38 0.08 4.83 0.37 0.08 4.46 45 Mid-C/ 

COB 

5-8 years 0.14 0.07 1.94 0.17 0.08 2.16 27 

1-2 Years 0.08 0.02 3.17 0.08 0.02 3.43 204 

NP15 3-4 Years 0.02 0.02 0.90 0.03 0.02 1.17 145 

5-8 years 0.02 0.03 0.70 0.03 0.03 0.96 80 

1-2 Years 0.10 0.06 1.74 0.10 0.06 1.74 197 

PV 3-4 Years 0.02 0.05 0.53 0.03 0.05 0.57 106 

5-8 years 0.13 0.06 2.30 0.13 0.06 2.27 56 

1-2 Years 0.07 0.02 3.26 0.06 0.02 3.04 395 

SP15 3-4 Years 0.09 0.02 3.82 0.09 0.02 3.88 177 

5-8 years 0.09 0.04 2.29 0.09 0.04 2.28 63 

The results for the “after” period show persistence in the relationship 

between spot and forward power prices. This indicates that the process 

for forming expectations that developed during the crisis period did 

not instantly disappear or reverse itself following the implementation 

of the spot power mitigation measures required by FERC’s June 19, 

2001 Order. 

We have conducted a number of other tests that are described in more 

detail in Appendix V-C. These are variations on the basic equation 

using different pooling approaches. The results are broadly consistent 

with Tables V-2 to V-5. We also report more disaggregated results in 

this appendix. Finally, we address another econometric issue in 

Appendix V-D, namely, whether serial correlation affects the estimates 

and their precision. In Appendix V-D, we show results indicating that 

this is not the case. 
Chapter V 

 

Docket No. PA02-2-000 V-16 Price Manipulation in Western Markets 

Interpreting Regression 

Results 

To illustrate the implications of the estimated spot power elasticities 

on forward power prices, we construct some stylized examples. 

For each of our time-to-delivery classes, we calculated the average 

forward power price (FP) for all Mid-Columbia and Palo Verde 

contracts signed between January 1, 2001 and March 31, 2001. To 

apply the estimated spot power elasticities from Table V-3, we need to 

assume spot power prices were distorted and by how much. We 

consider two hypothetical cases: 100-percent and 200-percent 

distortion. 

Hypothetical spot power price distortions of 100 percent and 200 

percent can be roughly justified with reference to the implied system 

heat rate calculated in Table V-6 below. The implied system heat rate 

is simply the spot power price divided by the spot gas price and is a 

convenient measure of market performance that is sometimes used by 

traders. Under normal conditions, it would typically be in the range of 

10,000 to 11,000 Btu/kWh, representing the thermal efficiency of 

older steam boilers that typically serve marginal demand in California. 

Under short supply market conditions the implied system heat rate 

might be higher than this level. For a useful point of reference, we 

have calculated the relevant average of “clearing” heat rates that have 

been used in the California refund case.27 For the same period, these 

heat rates are in the 15,000 to 17,000 Btu/kWh range during peak 

demand periods. These values represent very inefficient peaking plants 

that operated for many peak hours during this period. In comparison, 

the implied system heat rate for Mid-C and PV in Table V-6 is 2 to 3 

times higher.28 This suggests that 100-percent to 200-percent spot 

price excess may not be unreasonable. 

 

27See Exhibit ISO-6 in the refund case. This exhibit was originally protected; 

however, the protection was removed by Administrative Law Judge Birchman on 

December 16, 2001. 

28The data in Table V-6 are simple averages over the period between January 1, 2001 

and March 31, 2001. 
Chapter V 

 

Docket No. PA02-2-000 V-17 Price Manipulation in Western Markets 

In Table V-6, we calculate the mitigated forward power price (MFP) 

for each combination of hub and assumed level of spot price distortion 

using the following equation:29

MFP FP (1 ) β γ − = ×+

where γ is the assumed percentage spot price distortion and β is the 

estimated elasticity. 

Table V-6. Impact of Estimated Spot Power Elasticity on Forward Price 

of Power (January 1, 2001 – March 31, 2001) 

Spot 

Power 

Elasticity

Assumed 

Spot 

Power 

Distortion 

Average Forward Power 

Price 

($/MWh) 

 Observed31 Mitigated 

Hub 

Time-toDelivery 

Class 

Average 

Spot 

Power 

Price 

($/MWh)30

Average 

Spot Gas 

Price 

($/MMBtu)

Implied 

System 

Heat Rate

(Btu/kWh) β γ FP MFP 

1-2 Years 0.38 153.75 101.28 

3-4 Years 0.13 84.02 72.84 

5-8 years - 

200% 

54.86 54.86 

1-2 Years 0.38 153.75 118.15 

3-4 Years 0.13 84.02 76.78 

Mid-C/ 

COB 

5-8 years 

284.21 6.30 

(Sumas) 45,113 

- 

100% 

54.86 54.86 

1-2 Years 0.38 123.28 81.21 

3-4 Years 0.09 71.43 64.71 

5-8 years 0.07 

200% 

52.68 48.78 

1-2 Years 0.38 123.28 94.73 

3-4 Years 0.09 71.43 67.11 

PV 

5-8 Years 

220.88 6.25 

(Permian) 35,341 

0.07 

100% 

52.68 50.18 

The calculations in Table V-6 are intended to indicate plausible 

applications of the statistical results. When we use our estimates of the 

regression coefficients from Table V-3 under the assumption of 100- 

to 200-percent spot price excess, we get substantially lower forward 

 

29Starting from the main regression equation FP SP FG β δ =× × α (expressed in 

equation (1) in logarithmic form), we assume that the observed spot power prices are 

γ percent inflated over the mitigated spot power prices (MSP), or mathematically, SP 

= MSP × (1 + γ). Substituting for SP we then get

(1 ) (1 )

SP MFP MSP FG FG FP

β

β δ δ β

β α α γ

γ

− =× × =× × = ×+

+

30We calculated the average daily peak spot power prices using historic Bloomberg 

quotes from January 1, 2001 to March 31, 2001. 

31The average observed forward prices were estimated using the actual long-term 

sales contract data for contracts signed during the period January 1, 2001 to March 

31, 2001. 
Chapter V 

 

Docket No. PA02-2-000 V-18 Price Manipulation in Western Markets 

contract prices for time-to-delivery class 1-2. Under the 200-percent 

spot power prices excess case, the implied reduction in contract price 

is about one-third. For the 100-percent spot power inflation case, the 

reduction is about 23 percent for this class. These effects are much 

smaller for time-to-delivery classes 3-4 and 5-8. 

Conclusion 

Our analysis shows that there is a statistically significant relationship 

between spot and forward power prices during the period from January 

1, 2000 through June 30, 2001. This relationship is somewhat 

unexpected in a market for a commodity with little storability and 

reflects the fact that market participants used current spot prices to 

form expectations about future spot prices during the period in 

question. 

Although estimated elasticities vary by hub and time to delivery, the 

results show that the influence of spot on forward power prices 

declines with longer times to delivery. This pattern is consistent with 

the notion that current spot prices convey more information about spot 

prices in the near future than the distant future. 

If, as we maintain in earlier chapters, spot power prices were distorted, 

these results imply that the price distortion flowed through to forward 

power prices, particularly those for contracts of short (1-2 years) time 

to delivery. 

Our analysis shows clearly (Tables V-2 and V-3) that the elasticity of 

forward power prices with respect to spot power prices is much greater 

for forward contracts of 1-2 years (about 33 percent) than for contracts 

of 3-4 years (about 12 percent) and is very small for contracts of 

longer average time to delivery. 

Because spot gas prices influence spot power prices, the manipulation 

of spot gas prices could have led to power prices that were distorted 

above and beyond the levels established in the refund hearing. 

According to the analysis in this chapter, this additional distortion 

would have influenced forward power prices. The magnitude of such 

an effect can be calculated in the manner illustrated in Table V-6. 

In addition, because spot and forward gas prices are linked through 

arbitrage, spot gas manipulation may have influenced forward power 

prices by inflating the price of forward gas. We have made no estimate 

of the magnitude of this second effect. 
Chapter V 

 

Docket No. PA02-2-000 V-19 Price Manipulation in Western Markets 

Recommendation 

Given the finding that forward power prices were distorted and a 

detailed statistical analysis providing estimates of the extent of the 

distortion based on a certain level of distortion in spot power prices, 

we present the following recommendation: 

♦ For contracts that are subject to a just and reasonable standard of 

review in the ongoing complaint proceeding (see footnote 2), the 

Commission should send this analysis to the Administrative Law 

Judges to use as they see fit to resolve the complaints. 
Chapter VI 

 

Docket No. PA02-2-000 VI-1 Price Manipulation in Western Markets 

VI. Trading Strategies, Economic Withholding, Inflated Bidding, 

and Other Anomalous Activities 

Initial Recommendations 

In this chapter, Staff will conclude its analysis of the Enron trading 

strategies (first discussed in the Initial Report) and describe further 

developments and investigations since the Initial Report was issued. 

This chapter builds upon the Cal ISO report released on January 6, 

2003, which identified potential transactions and parties that may have 

used the Enron trading strategies. This chapter also discusses potential 

economic withholding during the summer of 2000. We discuss 

evidence indicating that Enron worked in concert with other entities, 

both inside and outside California, to implement these strategies in 

ways that manipulated market outcomes. In this regard, Enron’s 

business model is discussed along with Staff’s recommendations. 

We also discuss whether the Enron trading strategies, underscheduling, 

economic withholding, and inflated bidding fall within the scope of the 

antigaming and/or anomalous market behavior provisions in the Cal 

ISO’s and Cal PX’s Market Monitoring and Information Protocol 

(MMIP). The MMIP is part of both the Cal PX and Cal ISO tariffs, 

which have been on file with the Commission since the Cal ISO began 

operations in April 1998. Staff recommends that the Commission issue 

orders to show cause why these behaviors did not constitute “gaming” 

in violation of the MMIP, with disgorgement of unjust profits 

associated with the violations or other appropriate remedies. Such 

disgorgement would be in addition to any refunds owed to establish 

just and reasonable rates in the California Refund Proceeding. 

The preponderance of evidence reviewed by Staff during this 

investigation indicates that Enron and its affiliates intentionally 

engaged in a variety of market manipulation schemes that had 

profound adverse impacts on market outcomes. Due to this 

overwhelming evidence, Staff recommends that the Commission issue 

an order to show cause why its market-based rate authorizations and 

blanket certificate authority should not be revoked. This order should 

cover Enron and its affiliates with the exception of Portland General 

Electric Company, which is the subject of an ongoing investigation in 

Docket No. EL02-114-000. Staff recommends that such revocation be 

made effective prospectively so that any preexisting contracts are not 

affected. 
Chapter VI 

 

Docket No. PA02-2-000 VI-2 Price Manipulation in Western Markets 

Background 

On May 6, 2002, Enron’s Washington, DC counsel provided the 

Commission with three internal memoranda, two of which date from 

December 2000, that describe certain trading strategies employed by 

Enron’s electricity traders in the West. Enron’s counsel informed Staff 

that Enron’s Board of Directors had voted to disclose the documents 

and to waive all claims of privilege. The Commission made these 

documents publicly available on the Web site for Docket No. PA02-2-

000 within hours of receiving them. 

Staff immediately requested followup information from Enron to 

better understand the trading strategies discussed in the memoranda, 

including Enron’s receiving transmission congestion payments without 

actually relieving any congestion. Among other things, Staff sought 

any comparable memoranda that discuss trading strategies for natural 

gas products. Finally, the data request asked Enron to provide all 

correspondence related to the subject matter of the memoranda. 

The documents provided by Enron indicated that traders from other 

companies were also employing several of the trading strategies 

discussed in the memoranda. In order to pursue this issue, on May 7, 

2002, Staff issued a notice to all sellers of wholesale electricity and/or 

ancillary services in the West, informing them that Staff would soon 

be sending them a data request seeking information about their use of 

the trading strategies discussed in the Enron memoranda, and directing 

them to preserve all documents related to such trading strategies. 

On May 8, 2002, Staff issued a data request to more than 130 sellers of 

wholesale electricity and/or ancillary services in the West during 

2000–2001, with a due date of May 22, 2002. This data request 

contained a series of requests for admissions in which an officer of 

each company was required to admit or to deny, under oath, whether 

his or her company had engaged in specific activities described in the 

request. The specific activities were based on the trading strategies 

discussed in the Enron memoranda; in addition, there was an 

additional request asking the corporate officer to admit or deny, under 

oath, whether the company had engaged in any other trading strategies. 

The data request also sought production of all internal documents 

relating to trading strategies that the company may have engaged in 

during the relevant time period, including correspondence between 

companies, reports, and opinion letters. Staff also requested specific 

information in regard to any megawatt laundering transactions 

between any of these sellers and Enron. 
Chapter VI 

 

Docket No. PA02-2-000 VI-3 Price Manipulation in Western Markets 

This data request required a senior officer of the company to state, in 

an affidavit and under oath, that he or she conducted a thorough 

investigation of the company’s trading activities in the West during 

2000–2001 and that the information being provided in response to the 

data request was complete and accurate to the best of that person’s 

knowledge and belief. 

In our Initial Report, Staff concluded that, while the exact economic 

impact of the trading strategies is difficult to determine precisely, these 

now infamous trading strategies have adversely affected the 

confidence of markets far beyond their dollar impact on spot prices. 

Even those trading strategies that are not anticompetitive have been 

viewed by customers as clever exploitations of overly complex rules 

by companies that do not account for the impact of their decisions on 

prices and customers. Market participants from all sectors of the 

industry may have engaged in these trading strategies along with 

Enron, and in trading strategies of their own, including nonpublic 

utility entities such as municipal and governmental agencies in 

California and jurisdictional public utilities (including power 

marketers). 

Staff’s initial review of the evidence indicated that Enron, as a 

corporate entity, displayed great eagerness to experiment with all 

aspects of market rules and protocols in an effort to “game the system” 

or to simply provide false information. In fact, shortly after the 

issuance of our Initial Report, Enron’s former chief West Coast trader, 

Timothy N. Belden, pleaded guilty to Federal fraud charges for his 

role in implementing these trading strategies. Enron’s corporate 

culture fostered a disregard for the American energy customer; the 

success of the company’s trading strategies, while temporary, 

demonstrates the need for explicit prohibitions on harmful and 

fraudulent market behavior and for aggressive market monitoring and 

enforcement. 

In a market environment, one expects that traders, working within 

Commission-approved market rules, will use various strategies in an 

effort to maximize profits. But a fundamental aspect of some of the 

Enron trading strategies was the deliberate use of false information. A 

market cannot operate properly without accurate information. Implicit 

in Commission orders granting market-based rates is a presumption 

that the power marketer’s behavior will not involve fraud or deception. 

For this reason, our Initial Report recommended that the Commission 

explicitly prohibit the use of false information as a condition for 

granting all market-based rate authorizations. Staff recommends that 

this condition also be added to all open access transmission tariffs. 
Chapter VI 

 

Docket No. PA02-2-000 VI-4 Price Manipulation in Western Markets 

Overview of the Cal PX and 

Cal ISO Operations 

The Enron trading strategies and Enron’s use of them to game the 

system are best understood in the specific context of Western energy 

markets. Thus, we provide a brief overview of the Cal PX and Cal ISO 

operations and trading rules. 

The Cal ISO operates much of the transmission grid in California and 

is responsible for all real-time operations, such as continually 

balancing generation and load and managing congestion on the 

transmission system it controls. In California, a certified scheduling 

coordinator is the intermediary between the Cal ISO and the ultimate 

customer. Under California’s restructuring legislation, the Cal PX was 

created primarily to operate two markets in which energy was traded 

on an hourly basis. These were the day-ahead and day-of markets. 

These markets established a single clearing price for each hour across 

the entire Cal ISO control area, provided there were no transmission 

constraints. Where transmission congestion existed, a separate clearing 

price was established for each transmission constrained area or zone in 

California. Each individual zonal clearing price was based on 

adjustment bids submitted by buyers and sellers. The adjustment bids 

represented the value to an entity of increasing or decreasing (i.e., 

adjusting) its use of the system. In essence, this is a redispatch of the 

system to deal with congestion. 

California’s restructuring plan required the three California public 

utilities (SoCal Edison, San Diego, and PG&E) to sell all of their 

generation resources into the Cal PX and to buy all of their energy 

needs from the Cal PX. This made the Cal PX by far the largest 

scheduling coordinator in California, representing at times close to 90 

percent of the load served by the Cal ISO grid. This requirement that 

the three public utilities exclusively use the Cal PX was critical in the 

restructuring program, since this was how the three public utilities 

were to calculate savings from using the new market structure and 

apply those savings to recover their stranded costs. 

Under the California restructuring rules, the three California public 

utilities were both buyers and sellers in the Cal PX. The prices paid for 

buying back their own resources through the Cal PX served to value 

those resources for stranded cost purposes. As long as the three public 

utilities paid less than the frozen retail rates, they used the difference 

to write off stranded costs. As noted in the Commission’s December 
Chapter VI 

 

Docket No. PA02-2-000 VI-5 Price Manipulation in Western Markets 

15, 2000 Order, stranded cost estimates show PG&E collected $8.3 

billion, SoCal Edison collected $9.3 billion, and San Diego fully 

recovered its stranded costs early in 2000. This formula broke down, 

however, when the public utilities had to buy back their resources at 

more than the retail rate. 

All scheduling coordinators (including the Cal PX before it ceased 

operations in January 2001) were required to submit a balanced 

schedule of load and generation to the Cal ISO for the following day. 

The Cal ISO then performed a security analysis to determine if the 

generation selected could serve customer demand without causing 

congestion on the transmission system. Although the rules were being 

modified constantly during 2000–2001, the basic steps of the dayahead auction process were as follows: 

♦ 7:00 a.m.—The Cal PX conducts 24 hourly energy auctions for the 

following day. 

♦ 9:00 a.m.—The unconstrained market-clearing prices (i.e., a single 

price for all of the Cal ISO system) become publicly available. 

♦ 10:00 a.m.—The Cal PX (like all scheduling coordinators) submits 

to the Cal ISO the estimated load for the next day and the 

generating resources that will produce the energy necessary to 

serve that load. 

♦ 11:00 a.m.—The Cal ISO either determines that the initial 

schedule is feasible (no congestion) using the available 

transmission facilities or requires that the schedule be modified by 

redispatch using adjustment bids. 

♦ 12:00 p.m.—Modified schedules are submitted. At this time, the 

Cal ISO can automatically modify schedules to relieve any 

remaining congestion. 

♦ 1:00 p.m.—The Cal ISO calculates the day-ahead charge for 

congestion on any congested paths. 

♦ 3:00 p.m.—The Cal PX publishes zonal price information when 

there is transmission congestion in the day-ahead market. The 

zonal price differences are equal to the Cal ISO’s hour-ahead 

congestion charges along the relevant paths. 

The Cal ISO operates a variety of markets in order to procure the 

resources necessary to reliably operate the transmission system, 

including a day-ahead market and an hour-ahead market for relieving 

transmission congestion and an energy market to continuously balance 

the system’s energy needs in real time. The Cal ISO’s real-time market 

is the final energy market to clear chronologically, after all other 
Chapter VI 

 

Docket No. PA02-2-000 VI-6 Price Manipulation in Western Markets 

markets in the region. Bilateral spot markets at trading hubs outside 

California generally operated in the time period between the close of 

the Cal PX market and the Cal ISO real-time market. 

Understanding the interaction of the Cal PX and Cal ISO spot markets 

with all their complexities, together with the different market 

operations outside of California, is crucial to understanding and 

analyzing the impact of the various Enron trading strategies. An 

example of the market complexities in California market rules is the 

transmission congestion management system. A transmission path is 

“congested” when total schedules exceed the available transmission 

capacity of the facilities. The Cal ISO used a zone-based approach to 

alleviate congestion. Buyers and sellers submitted adjustment bids 

identifying the prices they were willing to use to increase or decrease 

their generation on demand to relieve congestion in a particular zone. 

However, the software used by the Cal ISO to evaluate adjustment 

bids did not accept prices that were higher than the Cal ISO price cap. 

These and other market rules not only caused market inefficiencies but 

also contributed to bidding strategies that circumvented the market 

design, such as underscheduling by the three California IOUs. This, in 

turn, created an opportunity for Enron to develop strategies that 

capitalized on the market rules and the trading behavior of others. 

The Cal ISO’s and Cal PX’s 

MMIP Contains an 

Antigaming Provision and an 

Anomalous Market Behavior 

Provision 

The MMIP is one of several protocols that (as explained below) the 

Commission required the Cal ISO and Cal PX to include as part of 

their filed rate schedules.1

 The underlying purposes of the MMIP are 

discussed in the Objectives section of the MMIP. In pertinent part, this 

section reads: 

 

This Protocol (MMIP) sets forth the workplan and, where 

applicable, the rules under which the ISO will monitor the ISO 

markets to identify abuses of market power, to ensure to the 

extent possible the efficient working of the ISO Markets 

immediately upon commencement of their operation, and to 

provide for their protection from abuses of market power in 

both the short term and the long term, and from other abuses 

that have the potential to undermine their effective functioning 

 

1

Both the Cal PX and Cal ISO have substantially similar MMIPs. For convenience 

sake, we will refer to the language of the Cal ISO’s MMIP. 
Chapter VI 

 

Docket No. PA02-2-000 VI-7 Price Manipulation in Western Markets 

or overall efficiency in accordance with Section 16.3 of the 

ISO Tariff.2

In Staff’s view, one key function of the MMIP is to put market 

participants on notice as to the “rules of the road” for them so that the 

markets operated by the Cal ISO are free from abusive conduct and 

can function as efficiently and competitively as possible. Thus, while 

one key function of the market surveillance unit (which is created by 

the MMIP) is reporting, “that function is designed to facilitate efficient 

corrective actions to be taken by the appropriate body or bodies 

[including this Commission] when required.”3

In short, while the MMIP does not expressly prohibit any specific 

behavior, including the Enron trading strategies, Staff believes that 

market participants cannot reasonably argue that they were not on 

notice that misconduct that arose from abuses of market power and 

that adversely affected the efficient operations of the Cal ISO and Cal 

PX markets (as delineated in the MMIP) would be a violation of the 

Cal ISO or Cal PX tariffs. Staff believes that the key function of the 

MMIP is to put market participants on notice of what practices would 

be subject to monitoring and, potentially, corrective or enforcement 

action, by either the Cal ISO in the first instance or, as a last resort, by 

the Commission, whose function is to enforce the terms and conditions 

of filed rate schedules. 

With respect to past actions of sellers (both public utilities and 

governmental entities) under either the Cal PX tariff or the Cal ISO 

tariff, however, the Commission’s remedial authority may be broader. 

Staff believes that most of the misconduct engaged in by participants 

in the Cal ISO and Cal PX markets may come within the scope of the 

MMIP found in both tariffs. 

As set forth in the Cal ISO’s MMIP 1.3.1, the MMIP applies to “all 

ISO market participants; PX participants; [and] the ISO.”4

 As set forth 

in the Cal PX’s MMIP 1.3.1, the MMIP applies to Cal PX participants, 

market participants “whose actions have the potential to influence the 

competitiveness or the achievement of efficiency in the PX markets,” 

and the Cal PX itself.5

 

Part 2 of the MMIP specifies what are termed “Practices Subject to 

Scrutiny.” Among those practices are two of particular concern to the 

 

2

MMIP 1.1. 

3

MMIP 1.1.2 (Reporting Requirements). 

4

MMIP 1.3.1. 

5

MMIP 1.3.1. 
Chapter VI 

 

Docket No. PA02-2-000 VI-8 Price Manipulation in Western Markets 

Commission: “gaming” and “anomalous market behavior.” Gaming is 

defined as: 

“Gaming,” or taking unfair advantage of the rules and 

procedures set forth in the PX or ISO Tariffs, Protocols or 

Activity Rules, or of transmission constraints in periods in 

which exist substantial Congestion, to the detriment of the 

efficiency of, and of consumers in, the ISO [and PX] Markets. 

“Gaming” may also include taking undue advantage of other 

conditions that may affect the availability of transmission and 

generation capacity, such as loop flow, facility outages, level of 

hydropower output or seasonal limits on energy imports from 

out-of-state, or actions or behaviors that may otherwise render 

the system and the ISO [and PX] Markets vulnerable to price 

manipulation to the detriment of their efficiency.6

Anomalous market behavior is defined as: 

Anomalous market behavior . . . is . . . behavior that departs 

significantly from the normal behavior in competitive markets 

that do not require continuing regulation or as behavior leading 

to unusual or unexplained market outcomes. Evidence of such 

behavior may be derived from a number of circumstances, 

including: 

♦ withholding of Generation capacity under circumstances in 

which it would normally be offered in a competitive 

market; 

♦ unexplained or unusual redeclarations of availability by 

Generators; 

♦ unusual trades or transactions; 

♦ pricing and bidding patterns that are inconsistent with 

prevailing supply and demand conditions, e.g., prices and 

bids that appear consistently excessive for or otherwise 

inconsistent with such conditions; and 

♦ unusual activity or circumstances relating to imports from 

or exports to other markets or exchanges. 

The [ISO] Market Surveillance Unit [or PX Compliance Unit] 

shall evaluate, on an ongoing basis, whether the continued or 

persistent presence of such circumstances indicates the 

presence of behavior that is designed to or has the potential to 

 

6

Cal ISO MMIP 2.1.3; Cal PX MMIP 2.1.4. Hereafter, for convenience sake, we will 

refer to the antigaming provision as MMIP 2.1.3. 
Chapter VI 

 

Docket No. PA02-2-000 VI-9 Price Manipulation in Western Markets 

distort the operation and efficient functioning of a competitive 

market, e.g., the strategic withholding and redeclaring of 

capacity, and whether it indicates the presence and exercise of 

market power or of other unacceptable practices.7

Section 2.3 of the MMIP and its several subparts address in detail how 

the Cal ISO, including the market surveillance unit, is to respond to 

determinations that market participants are engaged in any of the 

suspect practices delineated in the MMIP. While the MMIP outlines 

intermediate steps (such as arranging for alternative dispute resolution 

or proposing language changes to the tariff), ultimately it directs the 

market surveillance unit to refer matters to the Commission for 

enforcement.8

 In other words, the MMIP contemplates that, while the 

Cal ISO may try to correct misconduct on its own, the Commission is 

to be “the court of last resort” for misconduct committed by market 

participants, including the gaming and anomalous market behavior 

misconduct defined in the MMIP. Because of the fact that Part 2 of the 

MMIP specifically enumerates suspect practices, that Section 7.3 of 

the MMIP authorizes the Cal ISO to impose “sanctions and penalties” 

or to refer matters to the Commission for appropriate sanctions or 

penalties, and that the MMIP is part of the Cal PX’s and Cal ISO’s rate 

schedules on file with the Commission, Staff concludes that entities 

that transact through the Cal PX or Cal ISO and engage in such 

enumerated practices are in violation of those filed rate schedules. 

The stated objectives of the MMIP are to identify abuses of market 

power by giving particular scrutiny to a list of abusive practices and 

misconduct and to take corrective action, including sanctions and 

penalties. In Staff’s view, the identified misconduct remains a 

violation of the Cal ISO’s and Cal PX’s filed rate schedules even if 

such formal procedures as referral outlined in the MMIP did not occur. 

The Commission can enforce a rate schedule on file even when there 

are processes in that rate schedule which, had they been used, would 

have assisted the Commission. Ultimately, the Commission can 

enforce a tariff with or without the assistance of a complaint or 

referral. 

The Cal ISO and Cal PX initially submitted the MMIP (along with 

other protocols) for informational purposes only on October 31, 1997. 

The Commission, however, found that the protocols, including the 

MMIP, “govern a wide range of matters which traditionally and 

typically appear in agreements that should be filed with and approved 

 

7

Cal ISO MMIP 2.1.1 (subparts MMIP 2.1.1.1 through 2.1.1.5 are denoted by 

bullets); Cal PX MMIP 2.1.1 (subparts a to e). 8

MMIP 3.3.4. 
Chapter VI 

 

Docket No. PA02-2-000 VI-10 Price Manipulation in Western Markets 

by the Commission.” 9 Therefore, the Commission accepted the 

protocols, including the MMIP, for filing, and directed the Cal ISO 

and Cal PX to post the protocols on their Internet sites and to file the 

complete protocols pursuant to Section 205 of the Federal Power Act 

within 60 days of the Cal ISO’s operations date.10 The Cal ISO and the 

Cal PX made their compliance filings on June 1, 1998. Accordingly, 

the MMIP has been part of the Cal ISO’s filed rate schedule and the 

Cal PX’s filed rate schedule since the Cal ISO’s operations date (April 

1, 1998). 

Staff Finds That There May 

Have Been Numerous 

Instances of the Misconduct 

Addressed in the MMIP 

Staff now reviews some of the various forms of misconduct discussed 

throughout this Report and provides its preliminary views on how the 

misconduct violated the MMIP. Staff recommends that the 

Commission issue orders to show cause to the companies specified in 

this chapter as to why the identified behaviors did not violate the Cal 

ISO or Cal PX tariff protocols and why unjust profits should not be 

remitted to customers. 

Further, because these behaviors involve past violations of a filed rate 

schedule, such disgorgement of unjust profits would relate to periods 

prior to the October 2, 2000 refund effective date in the California 

Refund Proceeding and would be in addition to any refunds owed to 

customers in establishing just and reasonable rates for the period 

October 2, 2000 through June 21, 2001. 

In the Commission’s July 25, 2001 Order in the California Refund 

Proceeding,11 the Commission discussed at length its establishment of 

the October 2, 2000 refund effective date. While rejecting a variety of 

arguments for refunds preceding that date, the Commission expressly 

noted that one exception to the refund limitations set forth in Section 

206 was “where the sellers have charged a rate other than the filed 

rate.”12 The Commission explained: 

We agree that the Commission may take retroactive action to 

address circumstances where a seller did not charge the filed 

 

9

Pacific Gas and Electric Co., et al., 81 FERC ¶ 61,320 at 62,470-471 (1997). 10Id. 

11San Diego Gas & Electric Co., et al., 96 FERC ¶ 61,120 at 61,506-511, order on 

clarification and reh’g, 97 FERC ¶ 61,275 (2001). 1296 FERC at 61,504. 
Chapter VI 

 

Docket No. PA02-2-000 VI-11 Price Manipulation in Western Markets 

rate or violated statutory or regulatory requirements or rules 

in applicable rate tariffs.13

However, in the July 25 Order, the Commission stated that there had 

been no demonstration that there were any violations of any 

Commission-filed tariffs.14

The July 25 Order preceded the initiation of this investigation, and 

Staff finds that the Commission’s statement that there were no tariff 

violations that would warrant refunds prior to October 2, 2000 appears 

to be no longer accurate. In short, Staff believes that numerous 

participants in the Cal ISO and Cal PX markets violated the terms of 

the Cal ISO’s or Cal PX’s tariff, specifically the MMIP; thus, the 

Commission could order disgorgement of unjust profits prior to 

October 2, 2000 if it determines there have been such violations. 

The Enron Trading Strategies 

and Their Impact on Prices 

As stated in our Initial Report, quantifying the exact economic impact 

of the trading strategies is difficult because we have not identified a 

way to definitively associate particular transactions with particular 

strategies. A passage from an undated Enron document entitled 

“Public Service of New Mexico California Service Overview” 

illustrates this point. The document describes a partnership 

arrangement providing mutual benefits and services, e.g., Enron acting 

as a scheduling coordinator on behalf of Public Service of New 

Mexico for certain trades. The document states that in Enron’s opinion 

no Cal ISO forms or notifications are required: “in fact the ISO will 

not even be aware that PNM is in the path.” 

On January 6, 2003, the Cal ISO Department of Market Analysis 

released a 34-page report entitled “Analysis of Trading and Scheduling 

Strategies Described in Enron Memos” (January 6 Cal ISO Report), 

originally dated October 4, 2002. While the Cal ISO indicates that 

some of the results of its analysis require further verification, the 

analysis is generally consistent with our Initial Report as to the effect 

these strategies had on the market. 

The Cal ISO’s Department of Market Analysis issued a report on 

November 15, 2002 entitled “Did Any of Enron’s Trading and 

 

13Id at 61,507-80 (citing Washington Water Power Co., 83 FERC ¶ 61,282 (1998), in 

which the Commission imposed sanctions and required public utilities to disgorge 

profits derived from past violations of the companies’ market-based rate orders). 

14Id.
Chapter VI 

 

Docket No. PA02-2-000 VI-12 Price Manipulation in Western Markets 

Scheduling Tactics Contribute to Outages in California?” (November 

15 Cal ISO Report). This report concludes that while Enron strategies 

could have financial impacts on the markets, they did not contribute to 

the outages during the winter of 2000–2001. Staff notes that the Cal 

ISO Report was submitted in a state proceeding before the California 

Select Committee to Investigate Price Manipulation of the Wholesale 

Energy Market (California Committee). The November 15 Cal ISO 

Report addresses and specifically refutes statements and allegations 

made by Mr. Robert McCullough in two earlier memoranda presented 

as part of his testimony before the state proceeding. In the memoranda 

he argues that the Enron strategies played a role in the blackouts 

during the winter of 2000–2001. 

The Enron trading strategies clearly fall within the scope of the 

MMIP’s antigaming and anomalous market behavior prohibitions. 

Indeed, one of the now infamous Enron memoranda that the 

Commission posted on the Web site for this proceeding even lists 

these prohibitions in a discussion of the trading strategies (however, 

the memorandum does not conclude whether or not the trading 

strategies are gaming or anomalous market behavior). 

We will discuss the various trading strategies in the same order as in 

the Initial Report. We first focused on “load shift” because, by Enron’s 

own admission, this was an explicit attempt to manipulate prices. 

The second set of trading strategies discussed includes marketing 

power and energy in an effort to sell the product where it is needed the 

most. These strategies include various forms of exports and imports. 

The last set of trading strategies involves deceitful tactics, such as 

providing false information or reporting imaginary transactions. 

Price Manipulation—Load Shift 

As described in the May 8, 2002 Data Request, the trading strategy 

known as load shift involves a company submitting an artificial load 

schedule in order to receive interzonal transmission congestion 

payments. Load shift involves deliberately creating congestion on a 

transmission line to increase the value of Enron’s transmission rights 

and is clearly an attempt to manipulate prices. This Enron trading 

strategy is particularly complicated and its success was dependent, in 

part, on the independent bidding behavior of other entities. 

By Enron’s own admission, the load shift strategy was not very 

successful. Enron was not able to move the price paid for congestion 
Chapter VI 

 

Docket No. PA02-2-000 VI-13 Price Manipulation in Western Markets 

management. However, whether successful or not, it was a clear 

attempt to manipulate prices. 

As described in the Enron memoranda, the load shift trading strategy 

involves creating the appearance of congestion by deliberately 

overscheduling in one zone (e.g., the southern zone) and 

underscheduling by a corresponding amount in another zone (e.g., the 

northern zone). For example, assume Enron’s true load and resources 

were balanced by zone. Enron schedules an additional 100 MW of 

load in the southern zone and underschedules by the same 100 MW in 

the northern zone. This inaccurate schedule requires 100 MW of 

additional north-to-south transmission relative to Enron’s true loads 

and resources. By shifting load in this manner, Enron created 

congestion and potentially raised congestion prices. This benefited 

Enron because it owned Firm Transmission Rights (FTRs) on the paths 

that it attempted to congest. 

As stated in the Initial Report, Enron purchased 1,000 MW (62 

percent) of the 1,621 MW in rights to north-to-south transmission on 

Path 26. The purchase of these FTRs cost Enron a total of $3.6 million. 

Path 26 is one of the two main transmission interfaces linking northern 

and southern California.15 Enron’s FTRs entitled it to collect a 

significant portion of all congestion revenues on Path 26 that were due 

to north-to-south congestion, the typical direction of congestion during 

periods of peak demand in the summer. This gave Enron an incentive 

to try to create—through a load shift—north-to-south congestion over 

this transmission line. If Enron could shift load and thereby increase 

the congestion price, it would be paid the higher price for all 1,000 

MW of the FTRs. 

The vast majority of Enron’s congestion revenues were from Path 26 

during July and August 2000, and totaled approximately $33 million 

for those 2 months for that path alone. This amount represented a 

considerable profit above the $3.6 million that Enron paid for the Path 

26 FTRs, even though (as explained below) it was not able to 

manipulate the prices of congestion payments. 

Enron was generally not able to move the cost of congestion because 

two large market participants, SoCal Edison and PG&E, often set the 

price for congestion relief over a large band of load used for 

congestion relief. Nonetheless, the false schedules that Enron 

 

15It is useful to think of the California system as an hourglass figure, with the two 

transmission paths connecting the northern and southern zones. During the winter, 

these paths constrain lower-cost generation in the south from reaching load in the 

north. Conversely, during the summer, these paths constrain lower-cost generation in 

the north from reaching load in the south. 
Chapter VI 

 

Docket No. PA02-2-000 VI-14 Price Manipulation in Western Markets 

submitted added unneeded confusion to the already complex 

congestion management program that the Cal ISO administered. In this 

manner, Enron harmed the market. It is also important to not view the 

Enron trading strategies in isolation. 

In an FTR Market Report dated December 1, 2000, the Cal ISO states 

that it actively monitored the FTR market and closely scrutinized 

Enron’s scheduling behavior. The FTR Market Report noted that 

PG&E’s underscheduling of load in the Cal PX day-ahead market 

could cause or exacerbate north-to-south congestion on Path 26. The 

Report concluded: 

It is important to note that the [Cal ISO’s] examination of 

bidding behavior has revealed that the primary FTR owners 

on Path 26 were not the entities causing these congestion and 

load scheduling patterns. Rather, these patterns are the result 

of behavior by other load-serving entities. Thus the major 

FTR holders were the beneficiaries of usage charge revenues 

resulting from the cost minimizing bidding strategy of loadserving entities in northern California.16

While Enron’s load shift trading strategy by and large did not move 

the price paid to relieve congestion, Enron nevertheless attempted to 

raise the price of congestion by artificially scheduling load in the 

hopes that it could collect higher revenues. This trading strategy was 

defeated, not by market rules or oversight, but rather by the actions of

other companies (primarily PG&E in the north and SoCal Edison in 

the south) that were underscheduling load, contrary to the market 

design rules. Both of these behaviors would be prohibited by Staff’s 

recommendation to prohibit submission of false information. Market 

rules should also be designed to economically discourage infeasible 

schedules. 

Finally, we note that in Mr. McCullough’s testimony before the 

California Committee, he references a letter from a former Enron 

employee named David Fabian to Senator Boxer. The letter refers to 

Enron’s rights to north-to-south transmission on Path 26. According to 

Mr. McCullough’s testimony, this person “heard” that Enron 

overbooked the line and that Enron “was allowed to price-gouge at 

will.” Both Staff’s analysis and the Cal ISO analysis of the economic 

impact of this Enron strategy indicate that this allegation is wrong. 

Additionally, this former Enron employee alleged that this 

overbooking strategy resulted in 2 days of rolling blackouts in northern 

California in the summer of 2000. Staff notes that this Enron scheme 

was designed to increase its congestion revenues. However, there is no 

 

16FTR Market Report, p. 35.
Chapter VI 

 

Docket No. PA02-2-000 VI-15 Price Manipulation in Western Markets 

evidence to suggest that any of the schemes or other practices 

discussed in the Enron memos contributed to the blackouts that 

occurred in California. As a general matter, congestion schemes such 

as this raise prices but do not factor into actual power flows. 

Staff concludes that load shift falls within the definition of gaming 

because it involves taking unfair advantage of the Cal ISO’s or Cal 

PX’s tariffs or rules, “to the detriment of the efficiency of, and of 

consumers in, the ISO [or PX] Markets.”17 To the extent that load shift 

involves creating false congestion or the receipt of excess congestion 

revenues, it also involved “taking undue advantage of . . . transmission 

constraints in periods in which exist substantial Congestion.”18 Finally, 

since load shift is a prime example of price manipulation, it is also a 

behavior that makes the Cal PX or Cal ISO markets “vulnerable to 

price manipulation to the detriment of their efficiency.”19 In short, we 

conclude that all companies, including Enron, that engaged in load 

shift violated at least MMIP 2.1.3. 

Price Maximization—Exports 

The following two trading strategies involve using exports and imports 

in some way to sell power where or when it is most valued. 

Export of California Power 

The trading strategy known as “export of California power” involved 

buying energy at the Cal PX to export outside of California in order to 

take advantage of the price spread between the California market 

(which was capped) and the uncapped markets outside of California. 

As noted in our Initial Report, fewer than a dozen entities either 

admitted to engaging in exports of California power or gave answers 

other than a denial. However, Staff notes that data indicate an increase 

in total exports from California during this period. 

In narrative responses to the May 8 Data Request, various market 

participants argue that some of the Enron trading strategies, such as 

exports of California power, are examples of economically rational 

behavior, or legitimate arbitrage. They note that the Cal PX, Cal ISO, 

and the Commission have never implemented market rules prohibiting 

the export of energy from California. Respondents maintain that 

exporting power outside of California in order to reach other market 

opportunities, or to take advantage of a price spread, is good business 

 

17MMIP 2.1.3. 

18Id. 19Id.
Chapter VI 

 

Docket No. PA02-2-000 VI-16 Price Manipulation in Western Markets 

practice. They argue that, from an individual entity’s perspective, an 

export may have provided an optimal business opportunity. 

For example, some respondents state that California generators may 

have wanted to make a long-term sale to avoid being entirely exposed 

to the California spot markets. Staff notes that, under California’s 

restructuring plan, the three California public utilities were required to 

buy their energy in the spot market. This created an incentive for 

entities with in-state generation who desired to enter into forward sales 

to seek markets outside of California. Also, they simply may have 

exported spot sales to avoid the price cap in California. 

While it may have been a rational economic decision for an individual 

company to export its power to a market with higher prices, the large 

amount of exports collectively contributed to the scarcity in California 

during 2000–2001. The Enron trading strategy called “thin man” 

(described as the opposite of the strategy called “fat boy”) involved 

submitting a false schedule that artificially decreased load in 

California and an equal amount of energy exports. Moreover, if 

entities other than Enron acted in concert on a coordinated basis to 

implement this strategy, it would represent a form of cooperative 

corporate behavior with significant ramifications. 

Historically, California has relied heavily on generation imports to 

meet its peak summer needs. However, the summer of 2000 did not 

follow this pattern. In fact, compared to earlier periods, the total 

amount of power exported from California during that summer was 

significantly larger than expected. This anomaly has been the subject 

of prior reports and studies. For example, a report by the General 

Accounting Office (GAO) on California restructuring indicated that 

monthly exports from May through October 2000 were between 40 

and 230 percent higher than the same months in 1998 and 1999. 

Overall, exports were approximately 200 percent higher from May 

through October 2000 than in the same period in either 1998 or 1999.20

When California deregulated its retail electric market, the three 

California public utilities sold their oil- and gas-fired generation assets 

to other entities that did not have franchised service areas or an 

obligation to serve particular customers. At the time, this was a unique 

retail market structure in the West. The differences in retail market 

structures, including the mandated reliance on the spot market in 

California, contributed to the regional market problems. A merchant 

 

20U.S. General Accounting Office, Restructured Electricity Markets: California 

Market Design Enabled Exercise of Market Power, Report No. GAO-02-828 

(released July 2002), p. 32 (GAO California restructuring report). 
Chapter VI 

 

Docket No. PA02-2-000 VI-17 Price Manipulation in Western Markets 

generator who exported power out of California in search of a better 

price or the opportunity to sell in forward (rather than spot) markets 

was behaving in a rational economic manner. Existing, vertically 

integrated utilities in neighboring states still had an obligation to serve 

their native load from their own generation resources. When it was 

economical, these utilities also bought generation from California to 

serve their load or for resale in other Western markets, whichever was 

most valuable. 

Staff concludes that the export trading strategy was largely the result 

of asymmetrical market rules under which products were sold where 

they brought the highest price. 

Ricochet or Megawatt Laundering 

The trading strategy known as “ricochet” or “megawatt laundering” 

involved one entity buying energy from the Cal PX in the day-ahead 

market and exporting it to a second entity, which received a fee from 

the first company. The energy was later sold to the Cal ISO in the realtime market (or as an out-of-market sale).21

Ricochets necessarily involve multiple entities, and the responses to 

Staff’s data requests indicate that there was an abundance of willing 

counterparties. Because both generation and transmission were 

required, Enron needed others to move power into and out of the Cal 

ISO system. As noted in our Initial Report, most of the transmission 

facilities critical for these trading strategies that are directly connected 

to the Cal ISO system are owned or controlled by nonpublic utility 

California municipals, including the Transmission Agency of Northern 

California (TANC) and the City of Los Angeles Department of Water 

and Power (LADWP). 

In addition to California transmission systems not operated by the Cal 

ISO, Enron also relied on transmission systems in the Pacific 

Northwest, specifically, those of Bonneville Power Administration 

(BPA), Avista, and Enron’s public utility affiliate, Portland. 

Transcripts of Portland traders and transmission personnel include 

detailed instructions by Enron personnel on how the various 

participants (Portland and Avista) were to record transactions and how 

to report the various parts of the transactions consistent with NERC 

requirements and the Commission’s regulations. 

 

21If there were insufficient bids in the Cal ISO real-time market, the Cal ISO, as a 

last resort to procure the resources necessary to operate the system, would purchase 

energy out of its market. These out-of-market resources were paid their bid, but did 

not affect the market-clearing price paid to other generators. 
Chapter VI 

 

Docket No. PA02-2-000 VI-18 Price Manipulation in Western Markets 

Entities routinely try to capture profits from price differences that exist 

between different time periods, e.g., purchasing power in the dayahead market and selling it in real time. The actual price in the realtime market can be higher or lower than the original price paid in the 

day-ahead market. Entities that engage in these strategies assume this 

arbitrage risk where others are unwilling to do so. 

During the 2-year review period, this trading strategy could also be 

used to avoid the price caps that were set in the Cal ISO real-time 

market. This is because the Cal ISO also bought power out of market 

at the last minute when there was insufficient supply bid into its 

market. These out-of-market purchases were typically priced above the 

price cap. Suppliers knew that the Cal ISO would pay any price in an 

effort to avoid blackouts. In the Initial Report, Staff concluded that this 

behavior (raising prices at the last minute, when buyers are unable or 

incapable of saying no) was not legitimate arbitrage, but was an 

exercise of market power. We reaffirm this conclusion and view it as 

inappropriate gaming of the system. 

Staff concludes that the ricochet trading strategy, at a minimum, is an 

example of anomalous market behavior—that is, “behavior that 

departs significantly from the normal behavior in competitive markets 

that do not require continuing regulation or behavior leading to 

unusual or unexplained market outcomes.”22 Indeed, the MMIP 

includes as one of the examples of anomalous market behavior 

“unusual activity or circumstances relating to imports from or export 

to other markets or exchanges.”23 In short, Staff concludes that all 

entities that engaged in the ricochet trading strategy violated at least 

MMIP 2.1.1.5. 

The Enron memoranda indicate that Enron included the generation of 

other sellers, such as British Columbia Power Exchange (Powerex) 

and Puget Sound Energy, Inc. (Puget), when employing this trading 

strategy. In addition, Cal ISO data indicate that during the critical 

period of the first week in December 2000, 10 market participants may 

have engaged in this trading strategy and may have generated close to 

$10 million in profits. The 10 market participants are listed in 

descending order of potential profits:24

 

22MMIP 2.1.1. 

23MMIP 2.1.1.5. 

24These transactions represent exports and imports by the same entity; therefore, the 

screen used by the Cal ISO is very conservative because it does not include 

transactions in which the import and export legs were performed by two or more 

parties. (See Issue 3 Chart in Cal ISO’s Response to Staff’s February 10, 2003 Data 

Request.) 
Chapter VI 

 

Docket No. PA02-2-000 VI-19 Price Manipulation in Western Markets 

♦ Puget Sound Energy 

♦ Powerex or British Columbia 

♦ Avista Energy Inc. 

♦ Los Angeles Department of Water and Power 

♦ PacifiCorp 

♦ Enron Energy Services, Inc. 

♦ Portland General Electric 

♦ Bonneville Power Administration 

♦ Arizona Public Service Corporation 

♦ Idaho Power Company (also referred to as Ida Corp.) 

Staff concludes that, to the extent these 10 market participants used 

exports from California prior to real time in order to withhold 

generation until the last minute for sales to the Cal ISO, such activity 

is an exercise of market power and a violation of the Cal ISO tariff. 

Staff recommends that the potential ricochet transactions of the 10 

entities listed in this section be part of the show cause order discussed 

later in this section. 

Trading Strategies Based on False Information 

The following trading strategies are all premised on submitting false 

information schedules. One trading strategy, fat boy, was designed to 

offset the bidding strategies of the California public utilities. In 

addition, this strategy itself did not affect market outcomes. The other 

trading strategies are all attempts to fabricate transactions for profit 

and to change market outcomes. 

After the Staff Initial Report was released, Jeffrey Richter, an 

employee of Enron and the manager of the Short-Term California 

trading desk in 2000, pleaded guilty to several counts. The February 3, 

2003 Plea Agreement states that he and other individuals at Enron 

agreed to devise and implement fraudulent schemes through the 

California spot markets. In this regard, the schemes required them to 

submit false information to the Cal ISO in the electricity and ancillary 

services markets. The Plea Agreement states the following: 

Among other things, we knowingly and intentionally filed 

energy schedules and bids that misrepresented the amount 

and geographic location of the load we intended to serve. We 
Chapter VI 

 

Docket No. PA02-2-000 VI-20 Price Manipulation in Western Markets 

did so for the purpose of increasing the appearance of 

congestion on transmission lines, increasing the market price 

for congestion fees for transmission between zones, earning 

congestion payments that otherwise would not have been 

available, and increasing the values of our FTRs (which only 

generated revenue when congestion existed). 

We also submitted bids to supply ancillary services that we 

did not have, or did not intend to supply, in the ISO’s dayahead ancillary services market. The bids we submitted 

contained fabricated information regarding the source and 

nature of the ancillary services we proposed to supply to the 

ISO. Once the bids were accepted, we would cancel our 

obligation to supply the ancillary services by purchasing them 

in the ISO’s hour-ahead ancillary services market. Enron 

would then profit by capturing the difference in price between 

the two markets. 

Fat Boy (or Inc-ing Load) 

The fat boy trading strategy involved a scheduling coordinator, such as 

Enron, artificially increasing (“inc-ing”) load on the schedule it 

submits to the Cal ISO to correspond with the amount of generation in 

its schedule.25 Under California market rules, all schedules submitted 

to the Cal ISO had to be balanced (i.e., load and generation had to be 

equal). The company then dispatched the generation it scheduled, 

which was in excess of its actual load. This resulted in the Cal ISO 

paying the company for the excess generation at the clearing price 

established in the real-time market.26

Staff emphasizes that this trading strategy was conceived and used in 

response to the procurement strategy used by the three California 

public utilities, which itself was a response to the unintentional 

interplay of Cal PX and Cal ISO market rules. The Cal PX, as the 

scheduling coordinator for the three California public utilities, was 

required to send the Cal ISO a schedule that balanced an equal amount 

of generation and load. The Cal PX day-ahead market cleared before 

the Cal ISO market, which was capped at various levels (depending on 

the date). Under the original California restructuring program, PG&E 

and the two other California public utilities were supposed to “bid all 

 

25An Enron strategy with the opposite market effect was called thin man, in which a 

load is artificially reduced and a corresponding amount of generation is exported out 

of California. 

26Staff performed an electronic search of the Enron transaction database (Enpower) 

with an explicit reference to “fat boy.” This search produced approximately 100 

transactions predominantly in coordination with the Cities of Glendale and Redding, 

California and Valley Electric. 
Chapter VI 

 

Docket No. PA02-2-000 VI-21 Price Manipulation in Western Markets 

of their generation into the Power Exchange and satisfy their need for 

electric energy on behalf of their full service customers with purchase 

made from the Exchange” (D.95-12-063). California required this buysell procedure in order to: (1) provide price transparency, (2) mitigate 

market power and reduce the burden of regulatory issues, (3) ensure 

that customers would receive the benefit of competitive market prices, 

and (4) provide sufficient depth to the PX such that its market signals 

could be relied on as a benchmark. 

In an effort to minimize their procurement costs under the California 

market rules, the three California public utilities, especially PG&E, 

habitually underscheduled their load in the Cal PX market. In other 

words, they would only buy energy in the Cal PX market that was 

priced at or below the capped Cal ISO real-time market, relying on the 

fact that residual load could be supplied in the Cal ISO real-time 

market at capped prices. PG&E’s strategy involved a deliberate 

attempt to push the Cal PX price below the capped price in the Cal 

ISO real-time market.27

PG&E’s load makes up a significant portion of the load in California. 

Its load represents approximately 85 percent of the demand in northern 

California, the NP15 zone. Therefore, PG&E’s decisions on how to 

bid its demand have a significant impact on both buyers and sellers in 

the market. Due to PG&E’s large size, changes in the company’s 

bidding behavior that represented a shift from the market design not 

only caused uncertainty and volatility but also greatly influenced a 

number of market outcomes, including market-clearing prices. The 

most obvious problem was shifting a large percentage of its load out of 

the Cal PX day-ahead market, causing the load to be met with the Cal 

ISO’s real-time market, resulting in increased reliability problems. 

Bid data submitted by PG&E to the Cal PX on August 26, 2000 

demonstrated its bidding strategy. PG&E’s expected load between 

12:00 and 1:00 p.m. was 9,060 MW. PG&E’s bid indicated that it was 

only willing to purchase its total expected load if the price was less 

than or equal to $75/MW in that hour. As the Cal PX price increased, 

PG&E was willing to purchase decreasing amounts. For example, if 

the expected price rose to $200/MW, PG&E was only willing to 

purchase half of its total expected load (4,530 MW). Because the 

actual clearing price in NP15 that hour was $249.39/MW, PG&E 

actually purchased 3,813 MW in the Cal PX. As a result, the 

 

27As initially proposed in the November 1, 2000 Order and as adopted in the 

December 15 Order, the Commission halted the practice of near-total reliance on the 

spot market to allow the three California public utilities to procure a more balanced 

portfolio and to procure resources under long-term contracts. 
Chapter VI 

 

Docket No. PA02-2-000 VI-22 Price Manipulation in Western Markets 

remainder of PG&E’s load (5,242 MW) would have to be served by 

purchases in the Cal ISO’s real-time market. Due to this bidding 

strategy, an equal amount of supply was not committed in the Cal PX 

day-ahead market. 

The obvious short-term effect of PG&E’s bidding strategy was to 

reduce the amount of load in the Cal PX day-ahead market, which 

reduced the price for every megawatt purchased in that market. 

However, this bidding strategy had the opposite effect on the Cal ISO 

real-time market. By increasing the amount of load served by the Cal 

ISO’s real-time market, the price for every megawatt served increased. 

Due to PG&E’s large size, its actions caused the market prices to 

move up and down appreciably. 

Another disruptive market outcome caused by PG&E’s bidding 

strategy occurred in December 2000. During this period, other market 

participants were willing to pay more for energy in the Cal PX market, 

which resulted in PG&E’s transition from a net buyer of generation 

(including its own resources bid into the market) to a net seller. In 

other words, PG&E’s bidding strategy resulted in the loss of its own 

generation to buyers, including out-of-state entities. This, of course, 

resulted in an even greater amount of PG&E load relying on service 

from the Cal ISO in real time. According to PG&E, after it began 

losing its own generation to other buyers, it sought California Public 

Utilities Commission (CPUC) support to use an alternative bidding 

approach to keep its own low-cost generation for its retail customers. 

Even after discussions with CPUC President Lynch’s office and the 

head of the Energy Division, it did not receive support to use the 

alternative bidding approach. Furthermore, the Cal ISO raised new 

reliability concerns.28 Only after the FERC lifted the requirement that 

utilities sell their generation into the Cal PX market on December 15, 

2000 was PG&E able to keep all of its own generation and contracts to 

meet its customers’ demand. 

While this procurement strategy attempted to minimize the public 

utilities’ wholesale electricity costs, underscheduling caused chronic 

operational and reliability problems for the Cal ISO (as documented in 

numerous filings with the Commission). The Cal ISO’s real-time 

market was designed to supply only the small amount of energy (less 

than 5 percent) needed to constantly balance generation with actual 

load. Chronic underscheduling in the Cal PX day-ahead market 

transformed this “balancing” market into an energy commodity market 

that served far more load than it was designed to supply. The 

uncertainty of not knowing how to supply a much larger percentage of 

 

28PG&E e-mail dated January 30, 2001 (p. 0221) of their response to Staff’s data 

request. 
Chapter VI 

 

Docket No. PA02-2-000 VI-23 Price Manipulation in Western Markets 

the load until real time caused considerable reliability problems for the 

Cal ISO. In short, California load-serving entities were using the realtime market for a purpose for which it was not intended. 

Shifting load out of the day-ahead market into the real-time market put 

additional market pressure on the Cal ISO. When insufficient supplies 

were available in the Cal ISO real-time market, the Cal ISO was 

forced to procure necessary supplies through out-of-market purchases 

that were not subject to a price cap. The uncertainty of this last-ditch 

effort to procure necessary resources was significant. In addition, the 

end result was that energy prices in real time were often much higher 

than the Cal PX clearing price. The effect of both the higher Cal ISO 

clearing prices and the still higher out-of-market prices was felt by all 

load-serving entities until December 8, 2000, when the Commission 

issued its Order Accepting Tariff Amendment on an Emergency Basis. 

On that date, the Cal ISO made an emergency filing to amend its tariff 

in an effort to curb the underscheduling problem and to protect the 

reliability of the system. After this order, only entities that 

underscheduled or caused the imbalance were directly assigned the 

costs of out-of-market purchases. 

In its filing, the Cal ISO stated that it had been forced to declare Stage 

2 Emergencies for the previous 4 days, and saw no immediate relief. 

The Cal ISO requested three tariff modifications as follows: 

(1) increase the amount of generation in the real-time market by 

allowing bids above the then-current $250 cap (such bids would not 

set the market-clearing price); (2) assess penalties (twice the highest 

price paid by the Cal ISO) against generators that refused to operate in 

response to a Cal ISO dispatch instruction and, if firm load was 

curtailed, an additional penalty of $1,000/MWh for energy a generator 

failed to deliver; and (3) underscheduling entities such as PG&E 

would be allocated the highest priced energy and out-of-market 

purchases. Given the extraordinary circumstances, the urgency of the 

request, and the overriding reliability concerns, Commission acted 

immediately to accept the Cal ISO’s proposed tariff changes. 

The fat boy trading strategy was a response to this underscheduling 

problem. Under California market rules, all scheduling coordinators 

(e.g., Cal PX and others, such as Enron) were required to submit to the 

Cal ISO day-ahead schedules that were balanced. The fat boy trading 

strategy was a way to preschedule on a day-ahead basis an imbalance 

sale in the Cal ISO’s real-time market. While neither underscheduling 

nor inc-ing load was an intentional part of California restructuring, it is 

clear to Staff that underscheduling was of far greater concern to the 

Cal ISO, no doubt because it led directly to reliability problems. 

Indeed, some of the respondents informed Staff that the Cal ISO 
Chapter VI 

 

Docket No. PA02-2-000 VI-24 Price Manipulation in Western Markets 

actually helped them to engage in the fat boy trading strategy by 

providing them with artificial or simulated load and delivery points. 

For example, an entity with only generation and no load could not 

submit a balanced schedule to the Cal ISO. According to Reliant, the 

Cal ISO created an artificial load point that enabled Reliant to submit a 

balanced schedule to the Cal ISO. 

Enron’s use of the fat boy trading strategy did not set the marketclearing price in the Cal ISO’s real-time market. Under California 

market rules, entities are price takers for the amount of generation in 

excess of actual load; that is, they are paid the clearing price that is 

established in the Cal ISO market.29 Nevertheless, the submission of 

false schedules, and the Cal ISO’s encouragement of such fabrications 

to circumvent the balanced schedule rule, would be prohibited under 

Staff’s recommendations in the Initial Report. The Initial Report

included a recommendation that all tariffs for market-based rates 

include an express prohibition against submitting false information. In 

addition, all open access transmission tariffs should be amended to 

include this prohibition. Flawed market rules that are not working as 

intended should be amended by the Commission, not circumvented by 

market participants. More significant was the elimination of the market 

rule that held the three California public utilities in the spot market. As 

stated in the Initial Report, allowing a greater use of forward 

contracting resulted in far less reliance on the spot market, thus 

reducing the economic incentive for this trading strategy. 

While Staff has concluded that the fat boy trading strategy alone did 

not set the market-clearing price in the Cal ISO’s real-time market, and 

may in fact have been encouraged by at least one Cal ISO employee, 

this trading strategy nonetheless involves the deliberate submission of 

false information and falls within the scope of the antigaming 

provision because it necessarily involves taking “unfair advantage” of 

the Cal ISO’s rules and may otherwise have made the “ISO Markets 

vulnerable to price manipulation to the detriment of their efficiency.”30 

 

29The day-ahead and real-time imbalance pricing during May 20-23, 2000 illustrates 

this trading strategy. Unexpected high loads occurred on May 20-21, which caused 

prices in the Cal ISO real-time market to reach the $750 price cap while the Cal PX 

day-ahead prices were in the $40 to $50 range. Reacting to these prices, Enron and 

British Columbia Power Exchange Corporation overscheduled between 1,000 and 

2,000 MW of generation as “price takers” in the Cal ISO real-time market on May 

22. Because the Cal ISO market continued to exceed the Cal PX day-ahead prices, 

the fat boy strategy was profitable relative to selling in the Cal PX. On May 23, 

2000, these two scheduling coordinators continued to overschedule more than 1,000 

MW in the Cal ISO imbalance market. However, the Cal ISO’s market dropped to 

the $200 range, while prices in the Cal PX rose to the $300 to $500 range. Thus, this 

overscheduling strategy ceased, for a time, to be profitable relative to selling in the 

Cal PX. 

30MMIP 2.1.3. 
Chapter VI 

 

Docket No. PA02-2-000 VI-25 Price Manipulation in Western Markets 

Underscheduling by the Three California Public Utilities 

California public utilities submitted false schedules when they 

knowingly underscheduled their loads to the Cal PX. Their 

underscheduling violated the California restructuring plan and the 

antigaming provisions of the Cal ISO and Cal PX tariffs. Both of these 

conclusions are true irrespective of the fact that the California public 

utilities viewed this practice as a cost minimization strategy. While the 

Commission has the authority to order disgorgement of profits, there 

are no profits to disgorge from a price-reducing strategy. 

Cal ISO Actions 

Staff is also concerned that a review of certain Cal ISO reports 

indicates a complacency with the submission of false schedules, such 

as in the fat boy trading strategy. The Cal ISO issued a report by its 

Department of Market Analysis entitled, “Did Any of Enron’s Trading 

and Scheduling Practices Contribute to Outages in California?” This 

report, which was reviewed by the Market Surveillance Committee, 

addressed issues raised by Robert McCullough before the California 

Committee. The report concludes that, based on data available to the 

Cal ISO, the Enron practices reviewed by Mr. McCullough did not 

cause the blackouts during the winter of 2001. Rather, the blackouts 

were caused by a combination of the limited supply of energy that was 

made available to the Cal ISO and limited transmission capacity 

available to deliver energy from southern to northern California. 

Within this context, an addendum to the report discusses the fat boy 

trading strategy. Again, the Cal ISO report criticizes Mr. 

McCullough’s previous analysis, but in doing so, the Cal ISO appears 

to view this strategy as benign or even helpful because it “simply has 

the effect of reducing the Cal ISO’s projected demand for imbalance 

energy that must be procured by the Cal ISO to meet real time load.” 

The Cal ISO also describes how, in performing its daily operations 

(such as system load projections and reserve requirements), it ignored 

the false information contained in the schedules submitted by Enron 

and others. The report seems to indicate that the Cal ISO was aware of 

the false underscheduling by the California public utilities and the 

counterbalancing effects of the false overscheduling of load by Enron 

and others. 

Because the Cal ISO is the control area operator of the transmission 

grid, it is imperative that the Cal ISO identify poorly designed market 

rules and make filings with the Commission proposing solutions. 

However, the Cal ISO must implement the Commission-approved 
Chapter VI 

 

Docket No. PA02-2-000 VI-26 Price Manipulation in Western Markets 

rules until they are changed, as all other public utilities are required to 

do. 

Transmission Congestion 

Strategies 

Non-Firm Exports, Death Star, and Wheel-Out 

In this section, we examine three Enron trading strategies known as 

“non-firm exports,” “death star,” and “wheel-out,” along with similar 

variations.31 All are designed to generate payments for relieving 

transmission congestion by “fooling” the Cal ISO’s computerized 

congestion management program. These trading strategies generally 

involved scheduling transmission in the opposite direction of 

congestion, and thereby getting paid for the counterflow. They are all 

premised on imaginary transactions that are nonetheless eligible for 

congestion payments from the Cal ISO. 

As described in the May 8, 2002 Data Request, in death star a 

company schedules energy in the opposite direction of congestion 

(counterflow), but no energy is actually put onto the grid or taken off 

of the grid. This trading strategy has been the subject of hearings in 

California. In a wheel-out, a company, knowing that an intertie is 

completely constrained (that is, its available capacity is set as zero) or 

out of service, schedules a transmission flow over the facility, knowing 

that the schedule will be cut and that it will receive a congestion 

payment without actually sending energy over the facility. In a nonfirm export, a company gets a counterflow congestion payment from 

the Cal ISO by scheduling non-firm energy from a point in California 

to a control area outside of California and cutting the non-firm energy 

after it receives such payment. 

As discussed in the Initial Report, the first instance of these trading 

strategies occurred on May 25, 1999. On that day, Enron scheduled an 

infeasible transaction in the Cal PX market across an intertie between 

southern California and Nevada. Because this schedule called for 

2,900 MW to go across a line with only 15 MW of available capacity, 

it triggered the Cal ISO’s congestion management procedures. A later 

investigation into this incident by the Cal PX resulted in a cash 

settlement by Enron. 

 

31Related schemes that are referenced in documents other than the Enron memoranda 

include “black widow,” “red congo,” and the “Forney perpetual loop.” 
Chapter VI 

 

Docket No. PA02-2-000 VI-27 Price Manipulation in Western Markets 

However, according to the Enron memoranda, these trading strategies 

became more complex and included the participation of other entities. 

The counterparties were used primarily to schedule parts of the 

transactions or to use transmission facilities outside the Cal ISO’s 

control area in order to hide the transaction. 

In fact, no energy flowed because the schedule began and ended at the 

same location. Noninvestor-owned California utilities, such as the 

Northern California Power Agency and LADWP, were also 

particularly crucial to these strategies because they own and control 

transmission facilities that interconnect with the Cal ISO’s system but 

are outside the control of the Cal ISO, which was crucial in helping to 

avoid detection. 

Staff notes that in its response to the May 8, 2002 Data Request, 

Powerex states that there is a structural flaw in the Cal ISO’s 

congestion management software that prevents the software from 

recognizing that a tie is out of service. Powerex claims that it has a 

standing practice of maintaining adjustment bids at interties to relieve 

congestion. The Cal ISO occasionally requested Powerex to remove its 

adjustment bids when the Cal ISO intended to take the line out of 

service. However, if the Cal ISO did not provide such advance notice, 

Powerex would receive a congestion payment. Powerex states that it is 

unable to identify such payments. 

In a March 15, 2001 e-mail from an Enron employee to the Enron 

Portland shift, he describes a new strategy for taking power from 

southern California to northern California using the Silverpeak intertie 

with the Sierra Pacific Power Company system as part of the 

transmission path. There is no indication from this e-mail that Sierra 

Pacific is aware of the import/export strategy. However, the following 

quote from the e-mail is interesting: 

Also do not sell to a marketer (especially POWEREX) 

without sleeving. We do not want anybody else to know 

about the path. If Powerex sees this I guarantee that they 

would try to schedule this and we do not want competition. 

The Cal ISO report identifies Powerex, along with Coral Power, LLC 

(Coral) and Sempra Energy Trading Corporation (Sempra), as the 

largest recipients of revenues from this type of activity. 

In addition, TransAlta described several transactions that have certain 

operational elements common to these Enron trading strategies. Unlike 

the Enron trading strategies, however, the TransAlta transactions 

actually moved power. For example, what TransAlta calls 
Chapter VI 

 

Docket No. PA02-2-000 VI-28 Price Manipulation in Western Markets 

“recirculation” was a way to move energy supply from southern 

California to northern California when the Cal ISO-controlled 

transmission path between these regions was fully subscribed. 

TransAlta would move the energy to the northwest using its 

transmission rights over non-Cal ISO facilities and then import the 

power into northern California. At times, the Cal ISO actively sought 

the assistance of TransAlta in implementing these energy transfers. 

TransAlta was very helpful and aided Staff’s understanding of 

different variations of the strategies by volunteering a significant 

amount of information. While TransAlta used a very broad reading of 

Staff’s data requests and was very cooperative, many respondents took 

the opposite approach. In fact, some entities used such a narrow 

interpretation of the questions about the Enron strategies that, if Enron 

were to use these interpretations, it would not admit to using its own 

strategies. 

An example is Sempra. Sempra denied engaging in the Enron 

strategies in its original May 22, 2002 response. On October 4, 2002, 

the Cal ISO issued a report prepared by the Department of Market 

Analysis, “Analysis of Trading and Scheduling Strategies Described in 

Enron Memos.” This report was provided to regulatory and law 

enforcement agencies on a confidential basis. On January 6, 2003, the 

Cal ISO released the report publicly and posted it on its Web site. The 

report was intended to (1) indicate how extensively the Enron trading 

strategies may have been used by Enron and others and (2) identify 

specific schedules and transactions that could be further investigated. 

The report identifies Sempra in connection with its analysis of the 

following Enron trading strategies: wheel-out, scheduling energy to 

collect congestion charges, death star, and get shorty. The analysis 

indicates that Sempra was among the top three in all these categories 

and potentially generated more revenues than Enron in each strategy. 

In a letter dated January 15, 2003, Sempra informed Staff that nothing 

in the Cal ISO report suggests that Sempra engaged in the Enron 

strategies. The Sempra explanation of how they could not have 

engaged in wheel-out illustrates our point. 

The Enron memos describe wheel-out as a simple strategy that took 

advantage of a market design flaw. Knowing that an intertie is 

completely constrained or out of service, a company schedules a 

transmission flow over the facility. This strategy generates revenue 

because the schedule will be cut and it will receive a congestion 

payment without actually having to send energy over the facility. The 

Cal ISO report focused on revenues on out-of-service tie points only. 

In its defense, Sempra states that while it did submit schedules over a 
Chapter VI 

 

Docket No. PA02-2-000 VI-29 Price Manipulation in Western Markets 

facility even after it received notification of constraints on a facility, 

the Cal ISO notices are only for “informational purposes” and their 

accuracy cannot be relied on. Next, Sempra explains that it would only 

receive a payment if the Cal ISO actually cut its schedule. However, a 

payment can and should be expected when a line is out of service, 

which is all that the Cal ISO report focused on. Sempra concludes by 

stating: 

Thus, that [Sempra] may have received certain counterflow 

payments in connection with schedules or adjustment bids on 

tie points that were out of service, in no way suggests that 

[Sempra] submitted those schedules or bids knowing that the 

schedule would be cut and that it would receive a congestion 

payment without actually having to send energy over the 

facility. 

Sempra wants Staff to believe that it ignored the fact that a facility was 

out of service, scheduled power over that facility anyway, and was 

shocked that it actually made money. Using this rationalization, not 

even Enron could be accused of engaging in the wheel-out trading 

strategy. 

 

This lack of cooperation is not limited to jurisdictional public utilities. 

For example, the city of Glendale, California (Glendale) also denied 

any knowledge of the Enron strategies in its May 31, 2002 response to 

Staff’s data request. On January 16, 2003, Glendale submitted a 

supplemental response maintaining that Glendale did not knowingly 

engage in the Enron trading strategies. However, included in the 

submittal are two memos (one from Enron and one from Coral) that 

were found during an internal review; these memos describe many of 

the Enron trading strategies in detail. They also describe the steps 

Glendale needs to take to implement the strategies in conjunction with 

Enron. 

Under the heading “Phantom Ancillary Services,” the Coral memo 

details how Glendale can bid capacity for day-ahead ancillary services 

when the capacity is not actually available. The memo describes 

Glendale’s ability to use its non-Cal ISO transmission rights to “play” 

the Cal ISO system. Another strategy is called “detrimental price plays 

in ISO.” Because both Glendale and Coral have load within California, 

this strategy involves phantom trades between the two in order to 

capture differences in energy prices between zones and congestion 

payments. 

Glendale’s continued denial of any knowledge of the Enron trading 

strategies is not supported by the evidence it submitted or the evidence 
Chapter VI 

 

Docket No. PA02-2-000 VI-30 Price Manipulation in Western Markets 

in the Enron e-mails described elsewhere in this chapter. For example, 

an Enron e-mail dated February 17, 2000, from an Enron employee to 

the Enron Portland shift, states the following: 

GLENDALE—we have been getting few opportunities to do 

profit sharing transactions with certain members of their staff. 

We need to let [Enron employee name] and myself know 

when we call to get them involved and they have no interest. 

Their manager wants to do this every time we see fit. 

Everyone needs to know why they don’t want to play. 

The city of Redding, California (Redding) is also discussed in the 

Enron e-mails as participating in the congestion relief scheme known 

as “red congo.” In one e-mail to the Enron Portland shift, it is advised 

that red congo is a new marketing arrangement to relieve congestion 

that also uses Pacificorp West as the northwest utility that moves 

energy from south to north from the Cal ISO. Part of the scheme uses 

Redding’s existing rights on non-Cal ISO transmission and a series of 

sales and purchases between the parties. This e-mail also notes the 

following: “Redding is on board with this strategy as is Pacificorp.” 

This preponderance of evidence suggests that nonjurisdictional entities 

such as Redding and Glendale were associated with Enron in 

executing the trading strategies in a willful and knowing manner. 

These trading strategies would not be possible if a single 

comprehensive congestion management system were implemented in 

the West, as Staff recommends. In addition, artificial congestion or 

congestion relief would violate Staff’s recommended tariff language 

prohibiting false schedules and information. 

Staff concludes that the transmission congestion strategies not only 

involve gaming, but also may fall into the category of anomalous 

market behavior because they are departures from normal behavior in 

competitive markets and lead to unusual or unexplained market 

outcomes.32 Staff emphasizes that Enron, in conjunction with other 

parties, took intentional advantage of the market rules in creating and 

implementing these trading strategies. The Cal ISO Report, as 

discussed earlier, identifies Powerex, Coral, and Sempra as the largest 

recipients of revenues for such strategies. 

 

32MMIP 2.1.1. 
Chapter VI 

 

Docket No. PA02-2-000 VI-31 Price Manipulation in Western Markets 

Ancillary Services Strategies 

Get Shorty 

As described in the May 8, 2002 Data Request, the “get shorty” 

trading strategy involves the “paper trading” of ancillary services. 

Ancillary services include various types of generation capacity that are 

held in reserve for use in a contingency situation, such as the loss of a 

critical generation or transmission facility (e.g., replacement reserves). 

These services are required by the Cal ISO in order to reliably operate 

its system and to meet various operational standards. 

In this trading strategy, Enron would commit to provide the ancillary 

services in the Cal PX’s day-ahead market and then cover its position 

by purchasing those services in the Cal ISO’s hour-ahead market. 

There is a legitimate profit motive here: to sell high in the day-ahead 

market and buy back at a lower price in the real-time market. Staff 

notes that Cal ISO Tariff Amendment No. 4, which the Commission 

accepted for filing,33 permits the buyback of ancillary services as a 

legitimate form of arbitrage. 

At one point a Cal ISO employee attempted to stop the buyback by 

setting a high market-clearing price. In this incident, which was 

examined by the California Committee, a former Cal ISO employee 

attempted to stop market participants from buying back ancillary 

services in the hour-ahead market at a low price. Transcripts from a 

recorded phone conversation indicate that the Cal ISO employee 

contacted an Enron trader and suggested that he submit a bid of $91.86 

in order to set the market-clearing price at the then-current ceiling 

price. Following the conversation, the Enron trader did submit a bid at 

the maximum rate. The incident appears to be an isolated case. 

The original Enron memoranda indicate that its traders committed to 

sell ancillary services without actually having the ancillary services on 

standby (which is why the trading strategy is also called paper 

trading). Because entities are required to identify the source of the 

ancillary services (that is, the specific generating unit), Enron’s traders 

submitted false information to the Cal ISO. It is this aspect of the 

trading strategy—the deliberate submission of false information to the 

Cal ISO—that distinguishes it from permissible arbitrage activity. An 

e-mail dated January 11, 2000 from an Enron employee to the Enron 

Portland shift explains how Enron will take a more aggressive strategy 

 

33California Independent System Operator Corporation, 82 FERC ¶ 61,327 (1998).
Chapter VI 

 

Docket No. PA02-2-000 VI-32 Price Manipulation in Western Markets 

(currently used with Glendale) to bid into the day-ahead ancillary 

services market without the necessary resources (i.e., paper trading of 

ancillary services). 

The Initial Report concluded that, to the extent that this trading 

strategy involves deliberately supplying false information, the practice 

should also be prohibited. 

The Cal ISO analysis reporting on this trading strategy notes the 

difficulty of determining whether resources were actually available 

when ancillary services were sold in the day-ahead market, especially 

when the resource is imported from another control area into the Cal 

ISO’s control area. In an attempt to quantify the potential extent of this 

practice, the Cal ISO summarized the total amount of ancillary 

services sold back to the Cal ISO in the hour-ahead market. These data 

indicated that four entities were far more active than Enron, which had 

net sales of $5 million. These entities, in order of magnitude, are Coral 

Power, LLC ($17.1 million), Sempra Energy Trading Corporation 

($13 million), Avista Energy Inc. ($11.8 million), and Modesto 

Irrigation District ($10.3 million). These four entities and Enron had a 

total net gain of more than $57 million. 

As discussed in the final section of this chapter, these entities may not 

have acted independently. In fact, evidence recently produced by 

Enron in response to Staff data requests indicates that the buyback of 

ancillary services by certain entities may have been coordinated under 

the direction of Enron under business alliances. For example, in an 

Enron document entitled “Washington Water and Power (now Avista) 

Ancillary Services Information,” the pricing arrangement states the 

following: “All Capacity revenue will be divided between WWP and 

[ENRON] in the following ratio: 75 percent to Washington Water and 

Power and 25 percent to Enron Power Marketing Inc.” Following a 

similar description for splitting energy revenue, the document states 

that: “WWP understands this concept and prices accordingly.” 

An Enron e-mail dated June 5, 2000 describes the results of the joint 

effort and details “a summary of money made on ancillary services for 

the month of May” as follows: 

 

Customer Total Amount Enron Amount

Colorado River 

Commission $401,770 $220,885

City of Glendale 608,520 $150,135

Valley Electric Association $56,038 $14,010

El Paso Electric Company $2,000 $500

TOTAL $1,068328 $365,530
Chapter VI 

 

Docket No. PA02-2-000 VI-33 Price Manipulation in Western Markets 

Another e-mail dated November 5, 1999 to the Portland shift (with the 

subject line “DEAL ENTRY ERRORS”) explains the consequences of 

such mistakes from both management’s and the customer’s 

perspective. For example, the e-mail states: “This morning our book 

showed us losing $51,000 because the Redding profit sharing deal was 

incorrectly entered....” Another customer complaint is explained as 

follows: “We have had to explain to EPE why they received only 

expost for their exercised ancillary services deal (it’s because we had a 

zero exercise price in the hour ahead bid to the Cal ISO).” In the final 

section of this chapter, Staff makes further recommendations for 

further investigations of these and similar relationships. 

Finally, Staff notes that this trading strategy was used more widely by 

other entities than indicated by the responses to our data request. 

Certain entities, through a very narrow reading of the question, were 

not forthcoming in their responses. Sempra’s response is one example. 

 

As explained in the Enron memo, the paper trading strategy involves 

the following: (1) a sale of ancillary services in the day-ahead market 

and (2) the next day, in the real-time market, the company “zeroes out” 

the ancillary services by canceling the commitment to sell and buying 

ancillary services in the real-time market to cover its position. The 

critical element here is that companies could commit to sell on a dayahead basis without having capacity available and fulfill their 

obligation by buying this service from the Cal ISO in the hour-ahead 

(real-time) market. 

The Sempra original response states: “[Sempra] did not sell ancillary 

services in the day-ahead market and later cancel its commitment to do 

so in the real-time market.” It adds that there is nothing in the Cal ISO 

report and contradicts this statement because the clause “canceling 

commitments in the real-time market” is not mentioned. Sempra also 

argues that the Enron memo and Staff data request incorrectly refer to 

a buyback in the real-time market (rather than the hour-ahead market); 

therefore, it correctly denied engaging in the strategy. 

In spite of this denial, Sempra has stated that it adjusted its ancillary 

service schedules in the hour-ahead market based on, among other 

things, market opportunities. However, this does not address the real 

question: was this revenue earned by legitimate arbitrage or through 

submitting a false schedule (i.e., committing capacity it did not have 

on a day-ahead basis). Once again, using Sempra’s reading of the data 

request, not even Enron could be accused of engaging in the trading 

strategy. Staff notes that the preliminary screen used in the Cal ISO 

report shows that Sempra earned over $13 million, which is more than 
Chapter VI 

 

Docket No. PA02-2-000 VI-34 Price Manipulation in Western Markets 

twice the amount that Enron earned ($5 million). Staff notes that, 

according to the Cal ISO report, Coral Power, LLC, Avista Energy 

Inc., and Modesto Irrigation District of California also earned more 

than Enron. 

Staff concludes that the get shorty trading strategy falls within the 

scope of the antigaming provision because it makes the Cal ISO or Cal 

PX markets vulnerable to price manipulation.34 According to the Cal 

ISO report discussed in this chapter, Coral Power, Sempra, Avista 

Energy, and Modesto Irrigation District of Northern California, as well 

as Enron, had a total net gain of more than $57 million from the get 

shorty trading strategy. 

Selling Non-Firm Energy as Firm Energy 

 

As described in the Initial Report, in this trading strategy a company 

deliberately sells or resells what is actually non-firm energy to the Cal 

PX, while claiming that it is firm energy. 

NERC prohibits this practice since it violates NERC’s existing 

interchange rules. However, the Enron memoranda attempt to justify 

this trading strategy on the grounds that it supposedly brought 

additional supply to California with no apparent impact on Cal PX 

energy prices. The Enron memoranda also explain that Enron was 

subject to financial risk because, if the non-firm energy supply were 

cut, Enron would have to cover its position by purchasing that energy 

in the Cal ISO’s real-time market as a price taker. 

Staff finds this rationalization to be particularly troubling because 

Enron attempted to legitimize deception, the deliberate submission of 

false information, and actions that NERC expressly prohibited. This is 

a key example of why Staff is recommending an explicit prohibition 

against providing false information. 

This trading strategy also compromises reliability because non-firm 

energy improperly represented to be firm energy is not backed up with 

reserve generation by the supplying party. This problem is made worse 

when non-firm energy is imported into another control area. The 

receiving control area will not procure reserves for the import under 

the illusion that the supplying party is responsible for providing 

adequate generation reserves. Because this Enron trading strategy 

usually involved a purchase, it is difficult to detect absent the reporting 

of the entity selling the non-firm energy to Enron. 

 

34MMIP 2.1.3. 
Chapter VI 

 

Docket No. PA02-2-000 VI-35 Price Manipulation in Western Markets 

Recommended Commission Responses 

The Enron trading strategies that were based on false information and 

that had an adverse effect on the markets are encompassed within the 

MMIP protocol of the Cal ISO and Cal PX tariffs. Therefore, Staff 

recommends that the Commission initiate show cause proceedings for 

the companies listed in this chapter, with disgorgement of unjust 

profits associated with the various transmission congestion strategies 

(e.g., non-firm exports, death star, and wheel-out), load shift, ancillary 

service sales without the necessary resources, megawatt laundering, 

and selling non-firm energy as firm energy. These proceedings should 

involve both public and nonpublic utilities that engaged in these 

strategies under the Cal ISO and Cal PX tariffs. 

We emphasize that the trading strategies—while bearing Enron’s 

name—were not limited to Enron but appear to have been widely 

engaged in by numerous parties. Indeed, it would appear to Staff that 

the majority of public utility entities, and some nonpublic utilities, 

engaged in at least some of the trading strategies some time during the 

2-year review period. The cumulative effect of this prevalent alleged 

misconduct is that customers did not pay just and reasonable rates for 

wholesale electricity. This is because the trading strategies as a whole 

adversely affected the operations of Cal ISO or Cal PX markets and 

the calculation of the market-clearing price, which is dependent on 

participants engaging in bidding practices consistent with the Cal ISO 

and Cal PX tariffs and market rules, and not gaming the system or 

otherwise taking undue advantage of market rules. 

All of the market participants identified in the Cal ISO study by its 

initial screen should be required to show cause why their behaviors did 

not constitute gaming in violation of the Cal ISO and Cal PX tariffs, 

with disgorgement of unjust profits associated with the violations or 

other appropriate remedies. Those market participants are as follows: 

♦ Sempra 

♦ San Diego Gas & Electric 

♦ Morgan Stanley Capital Group 

♦ Coral Power, LLC 

♦ Powerex or British Columbia 

♦ Enron Power Marketing Inc. and its affiliate, Enron Energy 

Services Inc. 

♦ Avista Energy Inc. 
Chapter VI 

 

Docket No. PA02-2-000 VI-36 Price Manipulation in Western Markets 

♦ Pacific Gas and Electric Company 

♦ American Electric Power Services Corporation 

♦ Duke Energy Trading & Marketing 

♦ Mirant (previously known as Southern Company Energy 

Marketing, L.P.) 

♦ Cargill-Alliant, LLC 

♦ Idaho Power Company 

♦ Puget Sound Energy 

♦ Dynegy 

♦ PGE Energy Services 

♦ Calpine Corporation 

♦ Modesto Irrigation District 

♦ City of Glendale, California 

♦ City of Azusa, California 

♦ City of Riverside, California 

♦ City of Pasadena, California 

♦ City of Vernon, California 

♦ Salt River Project 

♦ Reliant 

♦ Arizona Public Service Company 

♦ Williams Energy Services Corporation 

♦ PacifiCorp 

♦ Automated Power Exchange 

♦ Bonneville Power Administration (BPA) 

♦ Portland General Electric 

♦ Los Angeles Department of Water and Power (LADWP) 

♦ Aquila 

♦ Southern California Edison 

♦ Citizens Electric 

♦ Constellation Power Service 

♦ Sierra Pacific Power Company 
Chapter VI 

 

Docket No. PA02-2-000 VI-37 Price Manipulation in Western Markets 

Staff also recommends that the Commission require the Cal ISO to 

provide transaction data that its analysis identified. The Cal ISO 

should also fully explain the screen that was used to identify the 

subject transactions. This information should also be made available 

publicly. 

Enron’s Business Model 

In addition to the trading strategies discussed, Enron also created a 

marketing program based on the use of other entities’ assets, thus 

avoiding large capital expenditures and the risk of owning its own 

resources. Business opportunities under Enron’s business model were 

focused on smaller utilities, such as public utility districts, 

municipalities, qualifying facilities, and cogeneration facilities. Enron,

using partnerships or alliances with others, gained market share, 

acquired commercially sensitive data, shared decisionmaking 

authority, and promoted reciprocal dealings and equity sharing of 

profits, among other things. 

A company’s business strategy is obviously devised by top 

management. In Enron’s case, the business model is described in 

Enron documents from a 30,000-foot view as “Skilling’s ‘Enron 

Network’ story.” Enron formed business alliances or partnerships 

without filing the agreements with the Commission as required under 

its market-based rate authorizations. Its promotional literature entitled 

“Why customers choose Enron” was intended to convince others that 

using Enron, with its market knowledge of complicated markets such 

as in California, was a good business decision. Using Enron would 

save these entities labor and systems costs. Most importantly, using 

Enron would be profitable. 

Under this business model, the nature of Enron’s interaction with its 

business partners developed over time under a flexible master contract. 

For example, Enron35 would first offer “consulting” services that 

allowed entities to outsource certain tasks rather than manage these 

tasks themselves. Enron gradually developed these relationships by 

expanding its services in an attempt to effectively control the assets of 

others in the decisionmaking process. Enron’s compensation for these 

“services” usually started with a fee structure (e.g., a charge/MWh for 

 

35From the documents in Staff’s possession, it would appear that Enron may have 

used its jurisdictional and nonjurisdictional affiliates interchangeably; that is, at 

times, its nonjurisdictional companies performed the functions of jurisdictional 

companies. To the extent that a nonjurisdictional Enron affiliate in fact performed 

jurisdictional services, it was operating in the absence of a filed rate schedule and 

was in violation of the Federal Power Act. Revenues from such services would be 

refundable to the customers, at least in the absence of Enron’s bankruptcy. 
Chapter VI 

 

Docket No. PA02-2-000 VI-38 Price Manipulation in Western Markets 

scheduling energy with the Cal PX). However, as the original 

relationship grew into a more comprehensive partnership, the 

compensation typically changed to an equity basis (share of profits) 

when the marketing of wholesale power was involved. 

An Enron Services Handbook explains that in most instances, profits 

from marketing energy were split on a 50/50 basis while profits from 

capacity sales for ancillary services were split 25/75, with 25 percent 

going to Enron and 75 percent to its partner. One exception explained 

in the handbook involves certain energy sales with Puget when a 

sliding scale was used. If the sale was under $99/MWh, Enron 

received $5 and the remainder went to Puget. For sales between $700 

and $750/MWh, Enron received $80 and the remainder went to Puget. 

While some forms of this rate structure may be appropriate under 

certain situations, this rate structure was used without notification to 

the Commission and without Commission approval. 

Another e-mail dated December 24, 1999 explains the Big Foot deal as 

buying energy from Washington Water Power Company and 

scheduling it into California as a supplemental energy bid. As 

explained earlier, supplemental energy bids are associated with 

available capacity (e.g., generation used for ancillary services). The email suggests that the traders may want to consider the following as 

part of the profit sharing: “If you buy from WWP and do real well on a 

supplemental, you might consider giving a few more dollars for their 

energy.” With these types of profit-sharing arrangements, it is hard to 

argue that Enron’s “partners” or “customers” did not have an 

understanding of how their profits were derived. 

An undated Enron document entitled “Public Service of New Mexico 

California Service Overview” demonstrates a form of cooperative 

corporate behavior as follows: 

Enron and PNM will partner up and attempt to extract profits 

by purchasing day-ahead power in bilateral market and 

sinking the power in one of several markets: [...] The 

combination of these potential sinks should increase the 

ability of the partnership to find a profitable spread between 

the cost of purchasing the power and the revenues received 

from its eventual sale. Any profit/losses after all costs will be 

split 50 percent by each party. Enron will utilize its trading 

expertise, SC status, and California load to enhance this 

partnership. PNM will contribute its trading expertise and SW 

system to this partnership. 
Chapter VI 

 

Docket No. PA02-2-000 VI-39 Price Manipulation in Western Markets 

Enron’s Business Partners 

Various Enron documents indicate that Enron had service agreements 

or other contractual relationships with a number of entities, including 

the following: 

♦ Energy West 

♦ Montana Power Company 

♦ Puget Sound Power and Lighting Company 

♦ Powerex Corporation (formerly British Columbia Power Exchange 

Corporation) 

♦ City of Redding, California 

♦ City of Glendale, California 

♦ Colorado River Commission (CRC) 

♦ Las Vegas Cogeneration 

♦ Washington Water Power Company (later named Avista) 

♦ Valley Electric Association 

♦ Public Service of New Mexico 

♦ Grant Public Utility District 

♦ Grays Harbor Paper Company 

♦ Northern California Power Agency 

♦ Modesto Irrigation District of Northern California 

♦ TOSCO 

Mr. Belden explained in an e-mail that Enron was able to develop 

alliances with other entities because: 

As regulatory changes, competitive markets, and institutions 

such as the California ISO increase the complexity of power 

trading, scheduling and settlements, more and more 

organizations are outsourcing certain tasks rather than 

manage these tasks themselves. Enron Power Marketing, Inc. 

(EPMI) is increasingly being called on to provide these 

services. Service transactions generally include ongoing 

EPMI performance obligations and greater daily customer 

interaction. Examples of these types of transactions include 

El Paso Electric, Valley Electric, Glendale, Enron Energy 
Chapter VI 

 

Docket No. PA02-2-000 VI-40 Price Manipulation in Western Markets 

Services, and many others that are currently being 

contemplated or finalized.36

Gaining Control of Assets 

A presentation at an Energy West Power Business Review Meeting 

characterizes the business strategy even more bluntly under a section 

entitled “Gaining Control of Assets.” The presentation states: 

Currently pursuing two strategies. The first is gaining control 

of a variety of small resources or capabilities around the west. 

For example, the combination of El Paso Electric, Las Vegas 

Cogen, Valley Electric, and Glendale joint venture provide us 

with a useful mix of loads and resources in the southwest. 

These transactions require relatively little capital, but will 

require automated IT links to customers and more people in 

the logistics group.37

Essentially, Enron developed initial business relationships with 

entities, which over time evolved into alliances in which Enron could 

gain more control of decisionmaking in a way that maximized profits 

for itself and its business partners. As the summary of the Energy West 

Power Business Review Meeting states: 

(1) Currently provide scheduling services to El Paso Electric, 

Glendale, CFE (Mexico), Tosco, Washington Water Power, and 

Enron Energy Services. 

(2) Use scheduling as a platform that will dovetail with click trade 

and that will lead to larger transactions that will make more 

money (e.g., joint venture with the City of Glendale).38

An Enron Services Handbook contains a list of California market 

conditions with instructions for the Enron employee concerning whom 

to call and what steps the partner should follow in order to take 

advantage of a particular market situation. For example, if the prices in 

the California market are high, the Enron employee would refer to the 

handbook section entitled “Who do you call and what action to take?” 

The Enron employee first decides if the price is high enough to be 

profitable to the “customer.” If it is profitable, the Enron employee 

implements the fat boy strategy: “generate or import and fake, or 

 

36Staff Exhibit No. S-34 in Docket No. EL02-113-000. 

37Staff Exhibit No. S-34 in Docket No. EL02-113-000. 

38Staff Exhibit No. S-34 in Docket No. EL02-113-000. Click trading refers to the use 

of electronic trading on the EnronOnline platform. 
Chapter VI 

 

Docket No. PA02-2-000 VI-41 Price Manipulation in Western Markets 

increase, load.” In this situation, the Enron employee could call 

Glendale, El Paso Electric, CRC, or Valley Electric and instruct them 

to increase imports into California; the handbook lists the transmission 

paths to be used. Redding and Tosco could be instructed to increase 

generation in northern California to implement this strategy. The 

pricing structure for this strategy specifies an even 50/50 split between 

Enron and its partner. 

The instructions alert the Enron employee to check to see if there are 

also high ancillary service prices. In that situation, the Enron employee 

should “call Glendale, Puget and El Paso Electric to try to get ancillary 

services bids in” and “call customers and have them ‘bid in’ more.” 

The handbook also includes a list of steps to take if the prices in 

California are low. In this situation, the instructions call for the 

opposite strategy known as thin man—“artificially reduce load and 

export.” The same counterparties are listed with corresponding 

delivery points for exporting their resources out of California. A 

similar pricing structure is also listed. Staff notes that in an August 22, 

2000 West Mid-Market Quarterly Business Review, Enron states that 

it “touched/managed 3,500 MW/day.” 

Still other Enron documents describe arrangements that go beyond 

joint coordinated activity and describe total Enron control of 

decisionmaking authority. An Enron e-mail dated December 23, 1999 

to Portland shift, with the subject “Valley Electric,” states the 

following: 

We will be scheduling and making marketing decisions on 

Valley’s behalf starting 1/1/2000[...]. There is an agreed on 

value sharing mechanism, in which Enron will get 40% of 

this “marketing value.” 

Enron literature describes how it planned to grow its relationship with 

parties. As its relationship grew, Enron collected data from the 

customer that it used for its own trading and marketing activities. For 

example, its strategy allowed “Enron to know as much or more about 

the customer’s near term position.” Finally, under this strategy, Enron 

planned to: 

Store operational data that the customer’s merchant group 

would not normally be storing. Provide service around 

analysis and manipulation of data. [Enron North America] 

would own the data—a potential to lock customers in—if 

they leave [Enron North America] their data stays here. 
Chapter VI 

 

Docket No. PA02-2-000 VI-42 Price Manipulation in Western Markets 

In our Initial Report, the alliance between El Paso Electric Company 

and Enron was set for hearing in a proceeding apart from Docket No. 

PA02-2-000. That proceeding (Docket No. EL02-113-000) 

investigated whether Enron’s use of El Paso Electric’s facilities, 

pursuant to an unfiled service agreement, may have been improper. 

A settlement has been reached in that proceeding and El Paso Electric 

agreed to a substantial dollar settlement. That partial settlement, which 

is between El Paso Electric, the California Parties,39 and the Trial 

Staff, does not address alleged violations of Enron and has not yet 

been certified to the Commission. Therefore, Staff recommends no 

further action against El Paso Electric. 

Recommended Commission Responses 

Staff believes that some of the Enron trading strategies violated the 

Cal ISO and Cal PX tariff provisions, which were in effect since 

operation began in April 1998. If a trade simply took advantage of a 

legitimate arbitrage opportunity, such as exporting a legitimate energy 

schedule, there would not be a tariff violation. If, however, in 

executing an Enron strategy a component was based on fictitious 

information that adversely affected market outcomes (such as death 

star or other transmission congestion strategies, get shorty, megawatt 

laundering simply to raise prices, load shift, or treating non-firm 

supply as firm supply), such activity could fall within the scope of the 

antigaming and/or anomalous market behavior provisions of the Cal 

ISO and Cal PX tariffs.40 Therefore, Staff believes that it would be 

appropriate to issue an order to Enron and its partners (both public 

utilities and governmental entities) to show cause why these behaviors 

did not constitute gaming in violation of the Cal ISO and Cal PX 

tariffs, with disgorgement of unjust profits associated with the 

violation or other appropriate remedies. It makes no difference if the 

Enron partner or Enron itself executed the transaction. In either case, 

the misconduct falls under the Cal ISO and Cal PX tariffs. 

All parties subject to the show cause orders41 should be required to 

inventory all revenues related to the Enron trading strategies and 

 

39The California Attorney General, the California Electricity Oversight Board, the 

Public Utilities Commission of the State of California, Pacific Gas and Electric 

Company, and Southern California Edison Company (collectively, California 

Parties). 

40Although the fat boy strategy included submitting false load schedules, it did not 

adversely affect the market outcomes, if the generation is simply bidding as a “price 

taker.” To the extent the generator submitted strategic bids that affected the market 

outcomes, this would constitute market behavior prohibited under the Cal ISO tariff. 

41Energy West; Montana Power Company; Puget Sound Power and Lighting 

Company; Powerex Corporation (formerly British Columbia Power Exchange 

Corporation); City of Redding, California; City of Glendale, California; Colorado 

River Commission (CRC); Las Vegas Cogeneration; Washington Water Power 
Chapter VI 

 

Docket No. PA02-2-000 VI-43 Price Manipulation in Western Markets 

demonstrate whether or not the transactions were legitimate as 

discussed in this chapter. 

In summary, the evidence indicates that Enron, on its own, could not 

have implemented its trading strategies. It was only with the willing 

cooperation of others that these strategies could have been executed. 

Through Enron’s direction, other entities both inside and outside 

California made business decisions that capitalized on market 

conditions in an effort to maximize profits from their assets on a 

coordinated basis. The coordination activity of Enron and its partners 

clearly changed market outcomes in a variety of ways. These parties 

capitalized on the complexities of the California market rules and 

structure. Market problems and dysfunctions were considered 

opportunities. As discussed above, Enron either acted on its partners’ 

behalf or alerted others to act in a like manner in order to capitalize on 

market conditions that it anticipated or knew about. Profits from this 

activity were typically shared. 

Enron systematically acted in partnership with others without the 

Commission’s knowledge, and the joint behavior of these entities 

served to game the market. The collective behavior of these entities 

turned defects in market rules and market structures into profit-making 

opportunities for Enron and its partners. 

A critical component of the Commission’s market-based rate 

authorization involves a determination of an applicant’s relative size in 

a market (market share). This determination is based on the amount of 

generation an entity either owns or has under contract, and the 

applicant is responsible for notifying the Commission in a timely 

manner of significant changes to its market share. According to the 

internal Enron documents, Enron controlled a significant amount of 

generation which it did not disclose in its filings before the 

Commission, and it never notified the Commission that changes in 

circumstances had occurred. 

The preponderance of evidence reviewed by Staff during this 

investigation indicates that Enron and its affiliates intentionally 

engaged in a variety of market manipulation schemes that had 

profound adverse impacts on market outcomes. Due to this 

overwhelming evidence, Staff recommends that the Commission issue 

an order to show cause why its market-based rate authorizations and 

 

Company (later named Avista); Valley Electric Association; Public Service of New 

Mexico; Grant Public Utility District; Grays Harbor Paper Company; Modesto 

Irrigation District of Northern California; and TOSCO. 
Chapter VI 

 

Docket No. PA02-2-000 VI-44 Price Manipulation in Western Markets 

blanket certificate authority should not be revoked.42 This order should 

cover Enron and its affiliates with the exception of Portland General 

Electric Company, which is the subject of an ongoing investigation in 

Docket No. EL02-114-000. Staff recommends that such revocation be 

made effective prospectively so that any preexisting contracts are not 

affected. 

Filing Requirements 

Staff is also aware that other entities conducted promotional activity 

similar to Enron in an attempt to form similar strategic alliances. For 

example, Sempra and Public Service of New Mexico may have 

competed with Enron in an attempt to perform similar services for El 

Paso Electric Company. Other evidence indicates that various entities 

may have had agreements with other market participants that had 

similar attributes as the Enron partnership agreements (e.g., sharing 

commercially sensitive information and coordinating activities). These 

entities include Avista and Turlock Irrigation District; Avista and the 

City of Riverside, California; Coral and the City of Glendale, 

California; and Coral and Sempra. To address this situation, Staff 

recommends that the Commission order all public utilities with 

market-based rates to file any past and present agreements with other 

entities having any of the characteristics described above within 30 

days. This requirement applies to both sides of an agreement 

regardless of whether the entity is supplying or receiving service. The 

Commission can determine if such agreements cede operational 

control of assets or provide for an equity split of profits from 

unauthorized coordinated marketing activity. The Commission may 

need to clarify at what point Section 203 and 205 filings should be 

triggered. Failure to comply with this order should be dealt with 

harshly. For example, if entities do not provide this information and it 

is later discovered that such agreements exist, the Commission should 

immediately revoke market-based rate authorization for that entity. 

 

42The Commission has already instituted formal proceedings to investigate Enron’s 

ownership interest in various qualifying facilities, including Las Vegas Cogeneration 

Limited Partnership; Saguaro Power Limited; Victor Garden Phase IV Partnership; 

Sky River Partnership; Cabazon Power Partners LLC; Zond Wind System Partners, 

Ltd. Series 85-A; and Zond Wind System Partners, Ltd. Series 85-B.
Chapter VI 

 

Docket No. PA02-2-000 VI-45 Price Manipulation in Western Markets 

Economic Withholding of 

Generation and Inflated 

Bidding During May to 

October 2000 

Staff’s preliminary analysis of the excessively high spot marketclearing prices as compared to the generation input costs (primarily 

natural gas costs) during May to October 2000 reveals what appear to 

be potential gaming violations, as defined in the MMIP of the Cal ISO 

and Cal PX tariffs. Staff has focused its analysis on this period because 

it covers the period of escalating prices prior to the October 2, 2000 

refund effective date. 

As explained earlier in this chapter, since the commencement of 

service in April 1998, the MMIP of the Cal ISO and Cal PX tariffs 

defined anomalous market behavior as including: 

♦ Unusual trades or transactions. 

♦ Pricing and bidding patterns that are inconsistent with prevailing 

supply and demand conditions, e.g., prices and bids that appear 

consistently excessive for or otherwise inconsistent with such 

conditions. 

♦ Unusual activity or circumstances relating to imports from or 

exports to other markets or exchanges. 

Clearing prices for the Cal ISO spot markets between May and 

October 2000 reached the then-current purchase price caps (that is, the 

Cal ISO would reject offers to sell power and/or energy to it at prices 

above these levels).43 As explained below, the input costs for 

generation during this period do not support these excessively high 

spot market-clearing prices. 

An example of the bidding behavior in question is the overall timing of 

the rise in spot market-clearing prices. As explained in Chapter IV of 

this Report (Figure IV-1), in May 2000 a disparity began to appear 

between the input costs of generation and the spot market-clearing 

prices for electricity. Over this time period, electric prices rose to 

levels often in excess of $500/MWh even though natural gas prices 

would have supported electric prices of only about $75/MWh. As 

explained in Chapter IV, the capital recovery requirement for a 

hypothetical new power project is between $16 and $19/MWh at a 60-

 

43The initial $750/MW cap was lowered to $500/MW on July 1, 2000. Subsequently, 

the purchase price cap was lowered to $250/MW on August 7, 2000. 
Chapter VI 

 

Docket No. PA02-2-000 VI-46 Price Manipulation in Western Markets 

percent plant factor.44 Therefore, the fixed and variable cost of 

generation would not exceed $100/MWh. As opposed to a rise in input 

costs, the excessively elevated bid prices appear to be solely an 

attempt to raise prices and Staff views this as a form of economic 

withholding. For example, bids were at or near the $750/MWh bid cap 

in both the Cal ISO and Cal PX until it was lowered on July 1, 2000. 

Bids for the same units were at or near the $250/MWh cap later in the 

summer even though input prices had risen during the interim period. 

The Commission’s June 19, 2001 Order discussed the past 

performance of the single clearing price auction in California. The 

marginal unit of the least efficient unit dispatched (i.e., the unit with 

the highest heat rate) sets the clearing price that is paid to all 

generation in the market. In 1998 and 1999 (California’s restructuring 

commenced operation on April 1, 1998), the California spot market 

produced average annual wholesale energy prices of $29 and 

$31/MWh, respectively. Staff notes that weather conditions were more 

favorable during this historical period, resulting in better hydro 

generation and lower system loads than during 2000 and 2001. Even 

with these major differences, the disparity in clearing prices before and 

during the crisis period is instructive. 

Table VI-1 calculates the implied heat rates of units during the 

summer of 2000. The spot gas prices during this period ranged from 

$3.71 to almost $6.00. Dividing bid prices (ranging from $200 to 

$750/MWh) by the spot gas prices produces a rough approximation of 

the implied heat rate of a unit. These results show heat rates far beyond 

even the most inefficient units in California. 

 

44See Chapter IV, footnote 11: California Energy Commission, 2000–2012 

Electricity Outlook Report, pp. 32-33. 
Chapter VI 

 

Docket No. PA02-2-000 VI-47 Price Manipulation in Western Markets 

Table VI-1. Implied Heat Rate 

Month Cost of Gas 

($/MMBtu) 

Price Cap 

($/MWh) 

Bid 

($/MWh) 

Implied Heat Rate 

(Btu/kWh) 

May 2000 $3.711 $750 $200 53,894 

 $300 80,841 

 $500 134,735 

 $750 202,102 

June 2000 $4.658 $750 $200 42,937 

 $300 64,405 

 $500 107,342 

 $750 161,013 

July 2000 $4.499 $500 $200 44,454 

 $300 66,681 

 $500 111,136 

Aug 2000 $5.103 $250 $200 39,193 

 $250 48,991 

Sep 2000 $5.975 $250 $200 33,473 

 $250 41,841 

Sources: Gas cost from Gas Daily for PG&E citygate and SoCal large packages; 

monthly cost is the average of daily prices for the month; California average is 50/50 

north/south. 

Staff notes that the Commission’s April 26, 2001 Order (95 FERC ¶ 

61,115 at 61,360) cites certain anticompetitive behaviors that would be 

prohibited under public utility sellers’ market-based rate authorizations. 

First, bids that vary with unit output in a way that is unrelated to the 

known performance characteristics of the unit are prohibited. An 

example of this bidding practice is the so-called “hockey stick” bid in 

which the last megawatts bid from a unit are bid at an excessively high 

price relative to the bids on the other output from the unit. Another 

example cited in the order is excessively high bids for a single unit in a 

portfolio compared with the remainder of the portfolio, without any 

apparent performance or input cost basis. 

The order explains a second category of prohibited bids—those that 

vary over time in a manner that appears unrelated to a change in the 

unit’s performance or to changes in the supply environment that would 

induce additional risk or other adverse shifts in the cost basis. An 

example of this is a bid that appears to change only in response to 

increased demand or reduced reserve margins, particularly if the 

timing of the bid is related to public announcements of system 

conditions or to timing of outages in a participant’s portfolio. 

Staff now concludes that such behavior was a violation of the MMIP. 

Staff’s general focus was at a market level, comparing the spot 

clearing prices with underlying input costs. Staff concludes that input 
Chapter VI 

 

Docket No. PA02-2-000 VI-48 Price Manipulation in Western Markets 

costs and market fundamentals do not explain the excessive rise in 

clearing prices during the summer of 2000. The California Parties 

submitted an analysis of certain large market participants during this 

time period and reached similar conclusions. 

The California Parties’ Analysis of Bidding Practices by In-State 

Generators and Certain Importers 

The California Parties submitted an analysis of the five large in-state 

generators together with an analysis of the bidding behavior of five 

importers: BPA, LADWP, Enron, Idaho Power, and Powerex. Staff’s 

analysis of generation input costs and spot market-clearing prices is 

largely consistent with the California Parties’ analysis. Based in large 

part on actual bid data that were submitted to the Cal ISO, Mirant, 

Williams, Dynegy, and Reliant had patterns of bidding units into the 

real-time market at or near $750 in May and June 2000, while the 

same units were bid at below $200 during September, after the Cal 

ISO cap was lowered to $250. The California Parties allege that these 

data indicate that the bid prices for these units in May and June 

exceeded costs by at least $500. 

The California Parties state that the bid data indicate that Duke 

submitted bids during the summer of 2000 that were more consistent 

with actual marginal costs and contrast Duke’s bidding behavior with 

the other market participants. However, Duke’s bids in the Cal ISO’s 

real-time market increased dramatically after the Commission’s 

December 8, 2000 decision to allow sellers with bids over the price 

cap that were accepted by the Cal ISO to be paid their bid price. The 

California Parties also argue that this pattern continued during the 

subsequent period when spot sales were made directly to CERS. 

The California Parties allege that other sellers in their study 

demonstrated noncompetitive bidding patterns consisting of bid price 

spikes and prolonged elevation of bid prices. In particular, they note 

that the Cal ISO declared a system emergency on 6 different days in 

June 2000 (June 13, 14, 26, 27, 28, and 29) and that bid price spikes 

were submitted during these emergencies by Williams, Dynegy, 

Mirant, Reliant, Powerex, LADWP, Idaho Power, and BPA. Similar 

results were shown for the 11 days on which the Cal ISO declared 

system emergencies in May, July, and August 2000. The California 

Parties also allege that on various days, two or more of these sellers 

submitted bid price spikes. The following is a summary of the 

California Parties’ analysis of the various market participants. 
Chapter VI 

 

Docket No. PA02-2-000 VI-49 Price Manipulation in Western Markets 

Reliant 

The California Parties allege that Reliant submitted pronounced 

hockey stick bids for four of its units during the May-June period. The 

average bid spans (the price difference between the lowest-priced bid 

segment and the highest-priced bid segment) were as high as 

$186/MWh. An example of bid price spikes occurred between May 22 

(the day of the Cal ISO-declared emergency) and May 24. In June, 

there were bid price spikes on days when the Cal ISO declared 

emergencies: June 13, 14, 26, 27, 28, and 29, and June 21-22 

(Reliant’s withholding period). Reliant’s bids reached the price cap 

levels of $750, $500, and $250. 

Mirant 

The California Parties characterize Mirant’s bidding behavior during 

the summer of 2000 as persistently high for some of its units and 

hockey stick bidding for other units. For example, Mirant’s Potrero 

Units 4, 5, and 6 were bid at or near the price cap in most hours. In 

other words, the units were bid with a pattern that simply tracked the 

price caps, i.e., near $750 at first, then near $500, and, starting in 

August, near $250. According to the California Parties, Mirant 

increased its bid prices on all or a large number of bid quantities on 

May 2-5, 15-16, 19-21, 22 (Cal ISO-declared emergency), 23, 28, and 

31. The California Parties identify other similar examples and 

examples of persistent high bidding patterns throughout the summer of 

2000. 

Dynegy 

 

The California Parties allege that Dynegy generally bid its combustion 

turbines into the real-time market at very high prices, especially during 

June and July 2000. They also allege that during May through July, 

hockey stick bidding was used with an average bid span (price 

difference between the lowest-priced bid segment and the highestpriced bid segment) in excess of $300. Examples of high spikes in bid 

prices occurred on May 4-5, 21-27, and 30-31. Overall, in June, 

Dynegy submitted very high bid prices for its units. Only 3 of its 22 

units bid into the real-time market had an average bid price of below 

$200, while others averaged close to $700. Other examples of 

noncompetitive bidding throughout the summer were identified. 
Chapter VI 

 

Docket No. PA02-2-000 VI-50 Price Manipulation in Western Markets 

Williams 

Overall, the California Parties allege that Williams bid very high 

prices for all of its units. Also, substantially similar units are bid in 

different ways that cannot be explained on a cost basis. For example, 

in May Alamitos Unit 5 was bid at an average price of $668/MWh, 

whereas Redondo Unit 7 was bid at an average price of $234/MWh. 

During May 2000, the California Parties allege that Williams’ bid 

prices spiked on May 1, 3-5, 6, 10, and 21-23 (including during the 

Cal ISO-declared emergency on May 22). Bid price spikes in June 

included June 3, 12, 13-14 (Cal ISO-declared emergencies), 20-22, 

and 26-29 (Cal ISO-declared emergencies). Similarly, during July, bid 

price spikes were alleged to have occurred on July 7, 13-14, 18, and 

26, and during declared emergencies on July 19-20, 24-25, 27, 28, and 

31. 

Enron 

The California Parties allege that from January to April 2000, Enron 

bid into the real-time market almost exclusively at the then-prevailing 

Cal ISO cap of $750. This pattern appears to persist through the 

summer of 2000 but with more variability. 

Powerex 

The California Parties allege that during the Cal ISO-declared 

emergency on May 22, 2000, Powerex withdrew approximately 1,000 

MW of energy that it typically offered to the real-time market, and 

therefore allegedly played a role in causing this emergency. On other 

days, Powerex’s bids would vary by 1,500 to 2,000 MW from hour to 

hour. On June 15, 2000, Powerex submitted large, infeasible schedules 

over various interfaces into California (over 10,000 MW) into the realtime market for several hours at or near $750. Powerex changed the 

nature of its bids in the following hour and bid almost 5,000 MW but 

at negative $750 (meaning that a reduction of generation will cost 

$750). This pattern was repeated later in the day. 

On December 12, 2000, following the Commission’s order to institute 

a soft cap in place of the $250 cap, Powerex increased its bids by 

approximately $500 to an average of approximately $750, with a 

number of bids being submitted over $1,100. 
Chapter VI 

 

Docket No. PA02-2-000 VI-51 Price Manipulation in Western Markets 

LADWP 

According to the California Parties, LADWP employed bidding 

patterns that removed supply from the real-time market for small 

periods, and spiked the bid prices on all or a large number of its bid 

quantity for small periods. For example, on May 21, 2000, the day 

preceding the Cal ISO-declared emergency, LADWP raised all bids 

into the real-time market reaching $750/MWh. Then on May 23-24, 

LADWP’s bid prices dropped to $200/MWh. LADWP submitted bid 

price spikes on 6 other days that were Cal ISO-declared emergencies 

(June 14, 27, 28, and 29, and July 24 and 25). The California Parties 

cite other nonemergency days on which LADWP submitted bid price 

spikes, again reaching the bid cap. 

Idaho Power Company 

According to the California Parties, the bidding strategies of Idaho 

Power resembled those of LADWP and Powerex. From May to July, 

the California Parties identified 23 days, including 8 days that are Cal 

ISO-declared emergencies, on which Idaho Power submitted bid price 

spikes. Idaho Power’s bids reached the $750, $500, and $250 levels 

established by the price caps during this period. 

BPA 

According to the California Parties, BPA was an active participant in 

the real-time market through the summer of 2000. Bid price spikes 

were observed on May 23-25 and 27; June 1-3, 28-29 (Cal ISOdeclared emergencies), and 30; and July 1. Starting after the May 22 

emergency, BPA submitted bids at the $750, $500, and $250 cap 

levels during the various price cap periods. 

Responses Filed by the InState Generators and 

Importers 

The in-state generators and importers filed reply comments and 

rebuttal testimony and exhibits. These entities raise various objections 

and argue that there was no requirement under the Cal ISO or Cal PX 

tariffs or protocols or Commission regulations in effect that generators 

bid at their marginal cost of production. They conclude that the 

California Parties have failed to demonstrate that any of the bidding 

practices constitutes withholding. Similarly, there were no restrictions 

on a seller’s ability to bid high. Mirant states that after the 
Chapter VI 

 

Docket No. PA02-2-000 VI-52 Price Manipulation in Western Markets 

Commission issued the April 26, 2001 Order, it stopped using hockey 

stick bidding. 

In response to the California Parties’ allegations of noncompetitive 

bidding behavior by these entities, they renew arguments previously 

made in various proceedings before the Commission in an effort to 

justify their high bids. Their explanations include: (1) the difficulty in 

determining the marginal cost of a unit, particularly with respect to 

startup costs; (2) because there is no capacity market in California, 

using a marginal cost standard is inappropriate; and (3) a marginal cost 

standard does not recognize market uncertainty, “scarcity rents,” and 

legitimate opportunity costs during the summer of 2000. Examples of 

plants with opportunity costs are limited run-time units, including 

fossil-fuel plants in California that have operating time limits in their 

air emissions permits or that must acquire scarce emissions credits. 

The generators maintain that such units should be bid at the price one 

would expect to receive during the highest-priced period in the future. 

They also argue that hockey stick bidding is appropriate for the last 

increment of a unit because it recognizes the risk of a forced outage. In 

this event, the seller must purchase replacement energy to meet its 

commitment. They also argue that it is appropriate to hold units in 

reserve as a physical hedge against the unexpected loss of a unit. 

Staff finds that these arguments are unpersuasive and do not 

adequately explain the dramatic rise in prices starting in May 2000. 

Such high bids and clearing prices far exceed the level needed to 

recover the capacity costs of generation. Market uncertainty existed 

prior to and after the summer of 2000, and this does not explain the 

price spike. The argument regarding opportunity costs is not 

persuasive because the units were first bid at $750 and then 

progressively lower through the summer of 2000. Using hockey stick 

bidding plus a physical hedge as insurance for a possible forced outage 

appears duplicative. Finally, Staff has explained that the MMIP was 

part of the Cal ISO’s and Cal PX’s filed rate schedules. 

Recommended Commission Responses 

Staff recommends that the Commission issue an order to LADWP, 

Dynegy, Mirant, Reliant, Williams, BPA, Powerex, Enron, and Idaho 

Power directing them to show cause why their behavior during May 

2000 through October 2, 2000 does not constitute a violation of the 

Cal ISO or Cal PX tariffs, with disgorgement of unjust profits 

associated with the violation or other appropriate remedies. 

 

The market participants discussed in this section of the Report 

displayed bidding patterns that were higher early in the summer (May 

and June) than in subsequent summer months even though input costs 
Chapter VI 

 

Docket No. PA02-2-000 VI-53 Price Manipulation in Western Markets 

(such as the cost of natural gas) nearly doubled during that same time 

period. The data suggest that these market participants’ high bidding 

behavior was not disciplined by their cost inputs; they simply bid the 

then-existing price cap—riding the cap from $750 to $500 and then to 

$250. Taking the example of a hypothetical unit with a 15,000 

Btu/kWh heat rate, a bid of $250/MWh in September when gas costs 

were $6/MMBtu would generate $90 for the cost of fuel and $160 as a 

margin to recover fixed costs, scarcity, etc. A $250 bid in May for the 

same unit when gas costs were $3.72/MMBtu would generate $56 for 

the cost of fuel and $194 as a margin to recover fixed costs, scarcity, 

etc. Conversely, a $750 bid in May would produce a margin of 

approximately $700. 

Staff notes that during the summer of 2000, legitimate scarcity costs 

should have increased from May to September as the California ISO 

weather-dependent demand increased. Yet, bidding patterns of these 

generators show that their bids were not directly related to load levels 

and associated scarcity levels. Staff also notes that the creditworthiness 

issue did not arise until after the summer period, so credit risk is not 

valid support for anomalous bids during this period. Similarly, the 

emission costs rose steadily in 2000 as the year progressed. If suppliers 

were willing to voluntarily supply at $250 in August and September as 

cost inputs rose dramatically, their bids above this level earlier in the 

summer (when cost inputs were far less) are highly questionable. 

However, Staff believes that there is reasonable support for prices that 

include a scarcity premium above marginal costs to reflect the severe 

scarcity that occurred during the summer of 2000. Bids at the $250 

level during August and September reflect the supply/demand 

imbalance in the Western markets, emission restrictions in the 

California market, and risks involved in pushing older generating units 

to their operating limits day after day. Given these circumstances, Staff 

recommends that the Commission investigate all bids over $250 

during the period May 1 through October 1, 2000. 

During the summer of 2000, Staff notes that one large in-state 

generator (Duke) submitted bids that appear to be more representative 

of its actual generation input costs. A possible explanation is that 

during this time period, unlike the other four large in-state generators, 

Duke was not heavily exposed to the spot market. During this period, 

Duke had committed a large amount of its generation to forward 

purchases. While Duke may have benefited during this period, like all 

other entities that received a clearing price above their bid, this does 

not constitute a violation of the Cal ISO or Cal PX tariffs. As noted, 

Duke’s high bids are covered by the refund proceeding. 
Chapter VI 

 

Docket No. PA02-2-000 VI-54 Price Manipulation in Western Markets 

Staff notes that the transactions with the Cal ISO during the October 2, 

2000 forward period are already subject to refunds. This appears to be 

an appropriate remedy for excessively high bidding. The 

Commission’s June 19, 2001 Order discussed an example of Duke’s 

high bidding behavior in February 2001. In that order, the Commission 

noted that Duke had bid $3,880/MWh. Duke maintained that this bid 

was a negotiating tool to recover payment for prior transactions and 

that it included a credit premium. The Commission noted that this 

premium exceeded Duke’s variable costs by an order of magnitude. 

The Commission found that Duke’s bidding at multiples of its 

marginal costs in an attempt to recover past-due amounts can in no 

way be found to be just and reasonable. The entire period in which 

Duke submitted high bids to the ISO is covered by the refund 

proceeding. 

Finally, as for any transactions with CERS, Staff notes that such 

transactions are not under the Cal ISO tariff and are therefore not 

subject to the MMIP. The California Parties submitted a 

comprehensive list of all transactions with CERS in Exhibit No. CA197. Staff’s review of these data indicates that Duke’s transactions, 

like most transactions with other parties, were under the Western 

Systems Power Pool Agreement. Therefore, Staff recommends that 

Duke not be subject to a show cause order. 

Physical Withholding of 

Generation 

During two days in June 2000, certain Reliant employees reduced the 

quantity of megawatts offered to the Cal PX on a day-ahead basis 

below the amount that normally would have been offered under the 

existing market conditions. Specifically, on Monday, June 20, Reliant 

reduced the capacity it bid into the Cal PX for delivery on June 21 by 

approximately 1,000 MW. Reliant increased only slightly the amount 

of capacity it bid into the Cal PX on June 21 for delivery on June 22. 

Reliant elected to perform discretionary maintenance on generating 

units whose output otherwise would have been offered to the Cal PX 

for those days. 

By order dated January 31, 2003, in Docket No. PA02-2-001, the 

Commission approved a Stipulation and Consent Agreement 

(Agreement) between Staff conducting the investigation in this 

proceeding and Reliant resolving the actions taken on these two days 

with respect to sales that would have occurred in the Cal PX market. 

Under the Agreement, Reliant agreed to pay approximately $13.8 

million directly to customers of the Cal PX that purchased energy in 

the Cal PX’s day-ahead market on June 21 and 22. As explained in the 
Chapter VI 

 

Docket No. PA02-2-000 VI-55 Price Manipulation in Western Markets 

order, the payment reflects the worst-case scenario of the maximum 

effect of Reliant’s withholding on the California market. 

Since the issuance of this order, various entities have submitted 

evidence regarding other alleged incidents of physical withholding by 

various market participants in the California markets. These 

allegations are not dealt with in this Staff Report. The issue of 

potential physical withholding is the subject of a separate and ongoing 

investigation. 

Reliant and BP Energy 

Traders Appear To Have 

Engaged in Coordinated 

Efforts To Manipulate Market 

Prices 

In the course of the investigation, Staff uncovered instances of traders 

from Reliant and BP Energy (BP) apparently coordinating their efforts 

to manipulate western electricity prices. Specifically, on three 

occasions a trader from BP contacted a Reliant trader and asked him to 

buy electricity from an offer he was going to place on an electronic 

trading platform (Bloomberg). The BP trader would then sell the 

power back to the Reliant trader at the same price, but the transaction 

would not take place on the electronic trading platform. 

On at least one of the occasions, the BP trader is seemingly manipulating 

the market price (in this case, electricity delivered at Palo Verde, a large 

trading hub in Arizona) in order to affect the value of his trading 

position for mark-to-market accounting purposes. The Reliant trader 

appears to have no particular interest in manipulating the market price; 

he simply goes along with the BP trader’s scheme. The evidence comes 

from recorded telephone conversations and transcripts provided to Staff 

by Reliant under Docket No. PA02-2-000. 

Staff has evidence that in April 2000, the BP trader contacted the 

Reliant trader and asked him to do him a favor. The BP trader (1) will 

offer to sell electricity on the Bloomberg electronic platform, (2) the 

Reliant trader will buy at the posted price, and (3) the BP trader will 

buy back the power (off the exchange) at the same price to negate the 

deal. The BP trader goes on to explain that he is trying to move the 

market price to $43.10 but no one will buy it at that price, so he needs 

the Reliant trader to “lift his offer” in order to increase the price. 

Our evidence indicates that several days later, the same BP trader 

contacted the same Reliant trader and offered him a similar proposal. 

Again, the BP trader is trying to manipulate the price in order to 
Chapter VI 

 

Docket No. PA02-2-000 VI-56 Price Manipulation in Western Markets 

increase the value of his trading position under the company’s markto-market accounting. 

The BP trader goes on to explain that they are marking their books on 

the October Palo Verde price. He notes that power for delivery in 

October at Palo Verde had traded as high as $44. He wants to move 

the price even higher because of his long position. He indicates that he 

will post an offer to sell at $44.15 and asks the Reliant trader to lift 

that offer and then he will buy it back from him at the same price. The 

BP trader then posts the offer on Bloomberg. 

Later that day, the BP trader instructs the Reliant trader to lift the offer 

because he senses the market beginning to move. The Reliant trader 

lifts the offer and asks the BP trader what they should do next. The 

evidence indicates that the BP trader informed the Reliant trader that 

he will buy the power back at the same price. 

Significantly, when Staff asked BP for information and telephone 

transcripts of these events, BP simply stated that it had no information 

regarding the activity of its trader. 

One of the concerns regarding the apparent price manipulation 

described above is that it occurred at an important trading hub (Palo 

Verde) that was presumed to be very liquid and thus not subject to 

price manipulation. Electricity price indices are a critical part of the 

market price formation process, and this market was clearly being 

manipulated. 

Therefore, Staff recommends that the Commission initiate proceedings 

to revoke Reliant’s and BP’s ability to sell power at market-based 

rates. 

Spot Prices in the Pacific 

Northwest—Docket No. 

EL01-10-000, et al. 

 

The proceeding in Docket No. EL01-10-000, et al. was established to 

“facilitate development of a factual record on whether there may have 

been unjust and unreasonable charges for spot market bilateral sales in 

the Pacific Northwest” for the period December 25, 2000 through June 

20, 2001. On September 24, 2001, the presiding Administrative Law 

Judge (ALJ) issued her proposed findings of fact and recommendations. 

The ALJ found that while California spot electricity prices affected 

electricity prices in the Pacific Northwest, prices in the region were 

driven up by a combination of factors, including reduced hydro 

generation due to the drought, increased demand, and relatively high 
Chapter VI 

 

Docket No. PA02-2-000 VI-57 Price Manipulation in Western Markets 

natural gas prices. In essence, the ALJ concluded that the record did not 

support allegations of market manipulation. 

 

In numerous orders, the Commission has stated that the spot markets 

in the West are integrated. Staff’s Final Report concludes that the 

California spot electricity markets were manipulated. This chapter 

explains that a variety of strategies were used by Enron and various 

market participants in an effort to manipulate various market outcomes 

in California. The manipulations used a variety of techniques, 

including submitting false information, creating false transmission 

congestion, and importing and exporting power into and out of 

California. All of these manipulations may have affected spot prices in 

the Pacific Northwest. 

During the course of its investigation, Staff sent a blanket data request 

to all sellers of electricity in the West for specific transaction data, 

including actual monthly sales data for bilateral transactions at the 

Mid-Columbia (Mid-C) trading hub and the California-Oregon Border 

(COB) trading hub. These are the two primary trading locations in the 

Pacific Northwest for bilateral electric sales and purchases. These 

transaction data indicate that, especially during the refund period 

(January 2001 to June 2001), there was a significant increase in spot 

prices in the Pacific Northwest similar to the rise in spot prices in 

California. Because there are no single clearing price markets in the 

Pacific Northwest, Staff has used bilateral sales of 1 month or less that 

are entered into no more than 1 month in advance of delivery for spot 

transactions. Staff has calculated average monthly implied heat rates 

based on the cost of gas at Malin and Sumas (the two main gas hubs 

that correspond to power delivered at Mid-C and COB). To perform 

this calculation, Staff divided the average cost of spot sales 

(approximately 650 transactions) by the average monthly cost of gas. 

Table VI-2 illustrates Staff’s results. 
Chapter VI 

 

Docket No. PA02-2-000 VI-58 Price Manipulation in Western Markets 

Table VI-2. Implied Heat Rate 

Delivery Month Cost of Gas 

($/MMBtu) 

Average Spot Price 

($/MWh) 

Implied Heat Rate 

January 2001 $9.08 $393 43,282 

February 2001 $7.99 $275 34,418 

March 2001 $6.20 $291 46,935 

April 2001 $7.32 $293 40,137 

May 2001 $4.79 $318 66,388 

June 2001 $3.33 $285 85,585 

Staff’s preliminary analysis indicates that the run-up of spot prices in 

the Pacific Northwest region is not fully explained by input prices such 

as the cost of natural gas. The transaction data reviewed by Staff 

indicate that during the previous 7 months (May to December 2000) 

there were approximately 2,000 transactions with average monthly 

prices ranging from $51/MWh to $167/MWh. 

Staff has also analyzed the spot sales transaction data in order to 

estimate the variable cost of production and the remainder, which 

could be considered the capital cost recovery of the generation plant. 

As previously discussed, the capital recovery requirement of a new 

combined cycle gas turbine is between $85 and $100/kW per year, or 

approximately $16 to $19/MWh at a 60-percent plant factor (see Table 

VI-3). 

Table VI-3. Estimated Capital Cost Recovery 

Delivery Month 

Cost of Gas 

($/MMBtu) 

Average 

Spot Price 

($/MWh) 

Cost Recovery at 

15,000 Heat Rate 

Remainder 

for Capital 

Cost 

January 2001 $9.08 $393 $136.20 $256.80 

February 2001 $7.99 $275 $119.85 $155.15 

March 2001 $6.20 $291 $93.00 $198.00 

April 2001 $7.32 $293 $109.80 $183.20 

May 2001 $4.79 $318 $71.85 $246.15 

June 2001 $3.33 $285 $49.95 $235.05 

An analysis of the transaction data indicates that, assuming a heat rate 

of 15,000 Btu/kWh to generate the spot sales, the average monthly 
Chapter VI 

 

Docket No. PA02-2-000 VI-59 Price Manipulation in Western Markets 

sales prices recover the cost of gas and the remainder (the last column 

of the table) would far exceed the capital costs needed for the plant. 

Recommended Commission Responses 

Based on Staff’s preliminary analysis, Staff recommends that the 

Commission remand this proceeding back to the ALJ in order to 

consider the additional evidence received after her initial findings. 
Chapter VII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VII-1

VII. Wash Trading on EnronOnline 

Several energy trading companies, including CMS Energy, Dynegy, 

Williams, and Reliant, have admitted publicly to engaging in “wash 

trades.” As a result of our analysis of EnronOnline (EOL) data, Staff, 

with assistance from Hendrik Bessembinder, Blaine Huntsman Chair 

in Finance, Eccles Business School, University of Utah, has also 

identified Enron and others as participants in wash trading activities. 

In fact, Enron’s use of its EOL platform created a fertile ground for 

wash trading that resulted in multiple forms of manipulation in energy 

markets. 

The term “wash trade” is generally defined as a prearranged pair of 

trades of the same good between the same parties, involving no 

economic risk and no net change in beneficial ownership. These trades 

expose the parties to no monetary risk and serve no legitimate business 

purpose. Potential motives for wash trading are numerous. Wash 

trades might be used to create the illusion that a market is liquid and 

active, or to increase reported trading revenue figures. Wash trades 

might be arranged at prices that diverge from the prevailing market in 

an attempt to send false signals to other market participants. 

Alternatively, the intent might be to affect the average or index price 

reported for a market, which in turn could benefit a derivatives 

position or affect the magnitude of payments on a contract linked to 

the index price. 

In general, wash trading is viewed as damaging to the integrity of a 

market and has the potential to mislead a host of market stakeholders 

(including competitors, regulators, analysts, and investors) through the 

various forms of manipulation outlined above. Although the 

Commission has no regulations on wash trading, wash trades are 

prohibited in markets regulated by the Commodity Futures Trading 

Commission. This chapter provides statistical evidence indicating that 

wash trading in energy products was more common than previously 

recognized. 

Wash Trading on 

EnronOnline 

The statistical portion of this chapter describes wash trades in natural 

gas and electricity products on the EOL trading platform from January 

2000 to November 2001. This study focuses on EOL trades in which 

both the buy and sell transactions were recorded in a single database. It 

seems likely, though, that market participants who intend to use wash 
Chapter VII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VII-2

trades for illegitimate purposes would be inclined to use methods that 

did not create a single electronic record of both transactions. The 

alternatives might include direct bilateral negotiation of both trades by 

telephone, or completion of one leg by telephone or an alternate 

electronic platform while completing the other leg on EOL. Our 

definition of wash trading considers trades that occurred within the 

same product, at the same price, in the same volume, and at nearly the 

same time (within 2 minutes of one another). 

It should be recognized that a company might enter an offsetting pair 

of trades on EOL for legitimate business purposes. For example, a 

company anticipating unseasonably warm weather might purchase a 

quantity of power, only to resell it later as actual weather conditions 

are milder. Therefore, it is possible that this report includes some 

“false positives”—paired trades that appear to be inappropriate wash 

trades but were not. However, given the facts in the specific examples 

of wash trading described herein, we believe the manipulative nature 

of these examples is obvious. 

Choice Markets 

EOL market makers are traders assigned to always quote both a bid 

price and an offer price, representing Enron’s willingness to always 

buy or sell gas during market hours. Our data analysis and interviews 

with market makers indicate that they sometimes elected to set the bidoffer spread to zero, which they referred to as making a “choice 

market.” Choice markets may, in effect, have been an invitation to 

EOL customers to engage in wash trading. The raw data used in our 

analysis do not include bid and ask quotes, so it is not possible to 

directly identify periods of choice (zero spread) markets. However, 

Staff identified all sequences of trades that occurred during likely 

choice markets based on the following criteria: (1) all trades in the 

sequence occurred at identical prices, (2) at least one trade in the 

sequence was an EOL buy and at least one was an EOL sell, (3) the 

sequence contained at least four trades, and (4) all trades in the 

sequence are for the same product at the same volume. 

Tables VII-1 and VII-2 provide information about EOL trading 

activity during choice market periods. Table VII-1 reports activity by 

calendar month, revealing that choice market trading on EOL 

increased steadily over time. In fact, 45 percent of all choice market 

trading in gas products and 54 percent of all choice market trading in 

electricity markets occurred during the last 3 months (September to 

November 2001) of the 21-month sample. These 3 months coincide 

with the period of time leading up to Enron’s filing for bankruptcy. 
Chapter VII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VII-3

The reasons for this upward trend in choice market trading activity are 

unclear; however, it may have been an attempt to prop up or otherwise 

maintain Enron’s presence in the market. 

Table VII-1. Trades Completed During Choice Markets, by Month 

Gas Trades Power Trades 

Year Month 

Choice 

Trades 

Percent 

of Total Year Month 

Choice 

Trades 

Percent 

of Total 

2000 1 749 1.4 2000 1 82 0.5 

2000 2 1024 1.9 2000 2 134 0.8 

2000 3 1835 3.4 2000 3 195 1.2 

2000 4 958 1.8 2000 4 101 0.6 

2000 5 887 1.7 2000 5 41 0.2 

2000 6 776 1.5 2000 6 23 0.1 

2000 7 754 1.4 2000 7 102 0.6 

2000 8 1209 2.3 2000 8 222 1.3 

2000 9 1046 2.0 2000 9 268 1.6 

2000 10 1126 2.1 2000 10 513 3.1 

2000 11 1256 2.4 2000 11 165 1.0 

2000 12 707 1.3 2000 12 36 0.2 

2001 1 1218 2.3 2001 1 344 2.1 

2001 2 1314 2.5 2001 2 378 2.3 

2001 3 2844 5.3 2001 3 536 3.2 

2001 4 1656 3.1 2001 4 412 2.5 

2001 5 2015 3.8 2001 5 452 2.7 

2001 6 2117 4.0 2001 6 614 3.7 

2001 7 2129 4.0 2001 7 1129 6.7 

2001 8 3721 7.0 2001 8 1894 11.3 

2001 9 6859 12.8 2001 9 2366 14.1 

2001 10 10511 19.7 2001 10 4534 27.0 

2001 11 6734 12.6 2001 11 2231 13.3 

Total 53,445 Total 16,772 

Choice market trades were identified as a sequence of at least four consecutive trades at the same 

price, with at least one buy and one sell included in the sequence. The table reports the number of 

EOL gas and power trades completed during choice markets, by trading month, from January 2000 

to November 2001.

Table VII-2 reports the number of choice market trades completed by 

several individual Enron market makers. Our analysis indicates that 

certain market makers created choice markets rather frequently. In gas 

products, 19,564 choice market trades (36.6 percent of the total) were 

executed by a single EOL market maker, and 6,285 choice market 

trades (11.8 percent of the total) were executed by a second EOL 

market maker. In power products, the most choice market trades 

executed by any single EOL market maker was 1,814, which was 10.8 

percent of the total choice market trades. It is important to note that the 

total gas trades in choice markets exceed the power trades by greater 

than 3 to 1. This could be explained by the greater volume of gas 

trading that occurred on EOL as compared to power trading. 
Chapter VII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VII-4

Wash Trades Within Choice 

Markets 

Using the choice market data shown above, Staff identified all wash 

trade pairs that occurred within these choice market events based on 

the additional criteria that both legs of potential wash trades involved 

the same counterparty and occurred within 2 minutes of each other. 

Since these trades occurred during choice markets, the previously 

mentioned criteria that these trades involve the same product, same 

price, and same volume also apply. 

By focusing only on wash trades that occurred within choice markets 

and within a sequence of at least four trades, we significantly limited 

the total number of wash trades identified. For example, a deliberate 

wash trade that included only a single pair of trades between two 

divergently priced transactions would not have met our criteria for a 

choice market nor, consequently, for a wash trade. However, by 

focusing on wash trades that occur within choice markets and within a 

sequence of four or more trades, we significantly increase the 

likelihood that the trades we select are indeed wash trades—a single 

pair of trades not part of a sequence of four or more trades would not 

be considered. 

Tables VII-3 through VII-8 provide information about wash trades 

completed during periods of choice markets. It is important to note that 

each wash trade represents a matching pair of trades. Therefore, for a 

Table VII-2. Trades Executed During Choice Markets, by Trader 

Gas Trades Power Trades 

Enron Trader 

Total Trades During 

Choice Markets Enron Trader 

Total Trades During 

Choice Markets 

Trader A 19,564 Trader K 1814 

Trader B 6285 Trader L 1373 

Trader C 2567 Trader M 1219 

Trader D 2431 Trader N 1159 

Trader E 2382 Trader O 1008 

Trader F 1710 Trader P 934 

Trader G 1608 Trader Q 861 

Trader H 1127 Trader R 834 

Trader I 884 Trader S 731 

Trader J 823 Trader T 612 

All Traders 53,445 All Traders 16,772 

The table reports the top 10 Enron gas and electricity traders in terms of the total trades executed during choice 

markets between January 2000 and November 2001. 
Chapter VII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VII-5

trader to complete 10 wash trades, he would actually need to execute 

20 trades (10 buys and 10 sells). These trade pairs all involved the 

same counterparty, the same quantity, and the same product, and 

occurred within 2 minutes of each other. Also, since they occurred 

during a period of choice markets as previously defined, each leg of 

the wash trade as well as any intervening trades occurred at a common 

price. The fact that these trades occurred during choice markets makes 

it likely that they were intended to inflate reported trading volumes 

and/or influence market indices. 

Table VII-3 reports the number of wash trades by month. In general, 

these data reveal a trend in which more wash trades occurred later in 

time. Only 5 percent of gas wash trades and 1 percent of power wash 

trades occurred during the first 4 months (January to April 2000) 

examined, while 42 percent of gas wash trades and 46 percent of 

power wash trades occurred during the last 4 months (August to 

November 2001) examined. An exception is the month of October 

2000 (highlighted in bold), when 27.5 percent of power wash trades 

occurred.1

 

1

This cluster of wash trading is linked to a previously noted promotional campaign in 

which a big screen television was awarded as a prize to the counterparty that 

generated the most trading activity. See “Initial Report on Company-Specific 

Separate Proceedings and Generic Reevaluations: Published Natural Gas Price Data 

and Enron Trading Strategies,” Federal Energy Regulatory Commission Staff 

Report, August 2002, p. 54. 
Chapter VII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VII-6

Table VII-3. Wash Trades Completed During Choice Markets, by Month 

Gas Trades Power Trades 

Year Month 

Wash 

Trades 

Percent 

of Total Year Month 

Wash 

Trades 

Percent 

of Total 

2000 1 1 0.3 2000 1 0 0.0 

2000 2 4 1.1 2000 2 3 0.8 

2000 3 6 1.6 2000 3 1 0.3 

2000 4 8 2.1 2000 4 1 0.3 

2000 5 3 0.8 2000 5 0 0.0 

2000 6 2 0.5 2000 6 0 0.0 

2000 7 1 0.3 2000 7 11 2.8 

2000 8 11 2.9 2000 8 10 2.6 

2000 9 8 2.1 2000 9 5 1.3 

2000 10 5 1.3 2000 10 106 27.5 

2000 11 11 2.9 2000 11 0 0.0 

2000 12 19 5.0 2000 12 1 0.3 

2001 1 6 1.6 2001 1 5 1.3 

2001 2 13 3.4 2001 2 5 1.3 

2001 3 38 10.1 2001 3 13 3.4 

2001 4 13 3.4 2001 4 6 1.6 

2001 5 15 4.0 2001 5 8 2.1 

2001 6 29 7.7 2001 6 12 3.1 

2001 7 25 6.6 2001 7 23 6.0 

2001 8 35 9.3 2001 8 42 10.9 

2001 9 42 11.1 2001 9 46 11.9 

2001 10 50 13.2 2001 10 49 12.7 

2001 11 33 8.7 2001 11 39 10.1 

Total 378 Total 386 

The table reports the number of wash EOL gas and power trades completed during choice markets, 

by trading month, from January 2000 to November 2001.
Chapter VII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VII-7

Table VII-4 reports the EOL market makers involved in the most wash 

trades. In gas products, 1 trader executed 111 wash trades (29.4 

percent of the total) and a second trader executed 73 wash trades (19.3 

percent of the total). In power markets, 1 EOL market maker executed 

102 wash trades (26.4 percent of the total), a second market maker 

executed 36 wash trades (9.3 percent of the total), and a third 

completed 32 wash trades (8.3 percent of the total). The fact that an 

individual trader would be linked to more than 25 percent of all wash 

trades in a product is significant evidence that wash trading on EOL 

was not simply a coincidence or a random occurrence. 

Table VII-5 reports the counterparties who engaged in the largest 

numbers of EOL wash trades. In gas products, Entergy-Koch Trading, 

LP completed 61 wash trades (16.1 percent of the total). In power 

products, Aquila Energy Marketing Corporation completed 112 wash 

trades (29 percent of the total). Again, the high percentage of 

involvement in wash transactions is significant evidence that certain 

EOL counterparties regularly and knowingly participated in wash 

trades. 

Table VII-4. Wash Trades Completed During Choice Markets, by Trader 

Gas Trades Power Trades 

Enron Trader 

Total Wash Trades 

During Choice 

Markets 

Percent 

 of Total Enron Trader

Total Wash Trades 

During Choice 

Markets 

Percent 

of Total 

Trader A 111 29.4 Trader K 102 26.4 

Trader B 73 19.3 Trader L 36 9.3 

Trader C 24 6.3 Trader M 32 8.3 

Trader D 16 4.2 Trader N 16 4.1 

Trader E 13 3.4 Trader O 15 3.9 

Trader F 11 2.9 Trader P 13 3.4 

Trader G 11 2.9 Trader Q 12 3.1 

Trader H 10 2.6 Trader R 12 3.1 

Trader I 10 2.6 Trader S 11 2.8 

Trader J 9 2.4 Trader T 10 2.6 

All Traders 378 All Traders 386 

The table reports the numbers of wash trades during choice markets between January 2000 and November 2001 

for the 10 most frequent Enron traders. 
Chapter VII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VII-8

Table VII-6 reports delivery locations for wash trades. Some (34 

percent of gas and 17 percent of power) wash trades were for financial 

products without physical delivery locations. Henry Hub was by far 

the most common delivery point for gas wash trades (31 percent of the 

total), while Mid-Columbia (24 percent), Cinergy (17 percent), and the 

California-Oregon Border (14 percent) were the most frequent delivery 

points for power wash trades. 

Table VII-5. Wash Trades Completed During Choice Markets, by Counterparty 

Gas Trades Power Trades 

Counterparty 

Total Wash 

Trades During 

Choice Markets

Percent 

of Total Counterparty 

Total Wash 

Trades During 

Choice Markets

Percent 

of Total 

Entergy-Koch Trading, LP 61 16.1 

Aquila Energy Marketing 

Corporation 112 29.0 

Reliant Energy Services, 

Inc. 25 6.6 

Williams Energy Marketing 

& Trading Comp 27 7.0 

Cook Inlet Energy Supply 

L.L.C. 22 5.8 

Idaho Power Company, dba 

IDACORP Energy 25 6.5 

AEP Energy Services, Inc. 21 5.6 Cinergy Services, Inc. 13 3.4 

MidAmerican Energy 

Company 21 5.6 

American Electric Power 

Service Corporat 9 2.3 

Mieco Inc. 19 5.0 Dynegy UK Limited 9 2.3 

PG&E Energy Trading-Gas 

Corporation 15 4.0 

EPMI Short Term New 

England (Enron Affiliate) 9 2.3 

Coral Energy Holding, L.P. 11 2.9 

El Paso Merchant Energy, 

L.P. 8 2.1 

Aquila Energy Marketing 

Corporation 9 2.4 IDACORP Energy L.P. 8 2.1 

Other Companies 174 46.0 Other Companies 166 43.0 

Total 378 Total 386 

The table reports the top Enron counterparties in terms of the total wash trades completed during choice markets between 

January 2000 and November 2001. 
Chapter VII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VII-9

Table VII-7 reports the individual trading days with the most wash 

trades in a single product and involving a single counterparty. The 

heaviest wash trading of gas products occurred on March 26, 2001, 

when Entergy-Koch Trading, LP completed 12 pairs of wash trades in 

the next-day contract for physical delivery at Henry Hub. The details 

of this series of wash trades are provided as an example in Table VII8, which focuses on a series of 24 trades that occurred in a 5-minute 

interval on March 26, 2001. With respect to this occurrence, it is 

interesting that no counterparty other than Entergy-Koch Trading, LP 

completed any transactions in this EOL product within ±30 minutes of 

the wash trades. It is difficult to identify any legitimate business reason 

why Entergy-Koch Trading, LP would need to complete 12 buys and 

12 offsetting sells in the same gas product in a period of less than 10 

minutes, especially when no other company made any EOL trades in 

this product and the price remained unchanged. Our analysis also 

revealed that the trades were executed by three separate Entergy-Koch 

Trading, LP traders. One of the three Entergy-Koch Trading, LP 

traders always acted as the buyer or seller in every pair of wash trades, 

but never completed both sides of the transaction. The other two 

traders took turns completing the opposite side of each wash 

transaction. This suggests that the first trader may have recruited other 

Table VII-6. Wash Trades Completed During Choice Markets, by Delivery Location 

Gas Trades Power Trades 

Location 

Wash Trades 

at Location 

Percent at 

Location Location 

Wash Trades 

at Location 

Percent at 

Location 

Financial 129 34.1 Mid Columbia 92 23.8 

HHub 118 31.2 Financial 66 17.1 

NGPL NICOR 24 6.3 Cinergy 54 14.0 

SoCal Topock 

EPNG 20 5.3 

COB 

North/South 49 12.7 

NBP 11 2.9 Palo Verde 30 7.8 

Opal 10 2.6 German Grid 23 6.0 

ANR SE 

Transmission 8 2.1 

PJM Western 

Hub 18 4.7 

NIT - AECO 8 2.1 Entergy 13 3.4 

NNG Demarc 8 2.1 

NEPOOL-PTF 

Power (3/1/00) 11 2.8 

EPNG 

Keystone Pool 6 1.6 NBP Trans Inc 10 2.6 

Other 

Locations 39 9.5 

Other 

Locations 20 5.2 

Total 378 Total 386 

The table reports the 10 most common delivery locations for EOL gas and electricity wash trades completed during 

choice markets between January 2000 and November 2001. The label “Financial” is used for any wash trades in 

which a delivery point was not specified. 
Chapter VII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VII-10

Entergy-Koch Trading, LP traders to participate in these wash trades 

in an effort to avoid detection. Finally, it is interesting to note that 

every wash trade pair occurred within 5 seconds of each other, while 

two pairs actually occurred simultaneously. The coordinated nature of 

the transactions leaves no doubt as to the prearranged nature of these 

wash trades. 

Table VII-7. Days in Which Individual Counterparties Conducted the Most 

Wash Trades During Choice Markets 

Gas Trades 

Counterparty 

Wash Trade 

Pairs Date Product 

Entergy-Koch Trading, LP 12 26-Mar-01 

US Gas Phy HeHub 

28Mar01 

Entergy-Koch Trading, LP 7 24-Aug-01 

US Gas Phy HeHub 

25-27Aug01 

ENA - IM West 4 30-Aug-00 

US Gas Phy Index IF EP 

Perm 

Nov00-Mar01 

Reliant Energy Services, Inc. 4 7-Dec-00 

US Gas Phy EPNG SoCal 

Topk 08Dec00 

Reliant Energy Services, Inc. 4 8-Dec-00 

US Gas Phy EPNG SoCal 

Topk 

09-11Dec00 

Calpine Energy Services, L.P. 3 27-Sep-01 

US Gas Swap Nymex 

Jan-Dec02 

Coral Energy Holding, L.P. 3 5-Oct-01 

US Gas Swap Nymex 

Nov01 

Entergy-Koch Trading, LP 3 20-Jul-01 

US Gas Phy HeHub 

21-23Jul01 

Entergy-Koch Trading, LP 3 27-Jul-01 

US Gas Phy HeHub 

28-30Jul01 

Entergy-Koch Trading, LP 3 5-Sep-01 

US Gas Phy HeHub 

06Sep01 

Power Trades 

Counterparty 

Wash Trade 

Pairs Date Product 

Aquila Energy Marketing 

Corporation 48 6-Oct-00 

US Pwr Phy Firm Mid-C 

Peak Dec00 

Aquila Energy Marketing 

Corporation 45 6-Oct-00 

US Pwr Phy Firm COB N/S 

Peak Nov00 

Dynegy UK Limited 4 14-Aug-01 

US Pwr Phy Firm Mid-C 

Peak 15Aug01 

Idaho Power Company, dba 

IDACORP Energy 3 28-Jul-00 

US Pwr Phy Firm PALVE 

Peak Oct00 

Idaho Power Company, dba 

IDACORP Energy 3 6-Nov-01 

US Pwr Fin Swap ISO NE 

HE11-23 EPT 

06Nov01 

The table reports the days with the most frequent wash trading with a single counterparty and in a single 

product. 
Chapter VII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VII-11

Table VII-8. Example of a Wash Trade Sequence for 

Trades Between EOL and Entergy-Koch Trading, LP 

Trade Time Wash Trade Pairs EOL Buy or Sell 

11:53:13 1 Sell 

11:53:14 1 Buy 

11:53:39 2 Sell 

11:53:39 2 Buy 

11:54:33 3 Sell 

11:54:33 3 Buy 

11:55:11 4 Sell 

11:55:13 4 Buy 

11:55:27 5 Buy 

11:55:28 5 Sell 

11:55:38 6 Sell 

11:55:41 6 Buy 

11:55:53 7 Sell 

11:55:57 7 Buy 

11:56:17 8 Sell 

11:56:18 8 Buy 

11:56:32 9 Buy 

11:56:37 9 Sell 

11:57:00 10 Buy 

11:57:02 10 Sell 

11:57:17 11 Sell 

11:57:20 11 Buy 

11:57:38 12 Buy 

11:57:39 12 Sell 

The table reports a series of trades occurring on EOL on March 26, 2001. 

Each trade is for physical delivery of gas at Henry Hub on March 28, 2001, 

and each was completed at a price of $5.235. 

The heaviest wash trading in power products, and the most blatant 

overall wash trading event, occurred on October 6, 2000, when a trader 

for Aquila Energy Marketing Corporation (Aquila) completed 48 wash 

trades for December 2000 power delivery at Mid-Columbia and 45 

wash trades for November 2000 power delivery at the CaliforniaOregon Border. As mentioned in our Initial Report, an Enron trader 

attributed this trading activity to the fact that Aquila’s trader was 

participating in a promotional campaign run by Enron. In an effort to 

promote the use of its EOL platform, Enron offered a prize to the 

trader with the highest volume of trades. In response to this campaign, 

the Aquila trader attempted to benefit personally by recording the 

largest volume of trades. An Enron trader verified that choice markets 

were created at both locations, which enabled Aquila’s trader to 

complete these trades at no cost. Through this 40-minute series of 93 

wash trades, the counterparty trader won and was awarded a bigscreen television as the prize. The combined volume of trades involved 

in this incident was approximately 1.6 million MWh at a total value of 

$180 million, but at a net cost of $0. It is not known to what extent 

these data may have been reported in market indices or financial 

statements. 
Chapter VII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VII-12

The above transactions by Entergy-Koch Trading, LP and Aquila both 

appear to have occurred at or near prevailing market prices. However, 

even a few wash trades at any price other than the average index price 

could have a substantial, manipulative effect on prices because the 

index would be skewed in the direction of the wash trades. The impact 

would be even more profound if the trades occurred at an illiquid 

location or if a larger number of wash trades occurred. In addition, 

creating the illusion of liquidity could distort markets, increase prices, 

and hurt customers. 

Affiliate Price Manipulation 

In many contexts, the definition of a wash trade has been limited to 

pairs of trades occurring simultaneously and at exactly the same price. 

Despite the occasional existence of choice markets, the EOL platform 

is normally characterized by a positive bid-ask spread, in which the 

ask (or offer) quote exceeds the bid quote. In this case, simultaneous 

buy and sell orders would be completed at slightly different prices. In 

order to determine the frequency of divergently priced wash trades, 

Staff analyzed data based on the criteria that both legs of the wash 

trade involved the same product, the same volume, and the same 

counterparty and occurred within 2 minutes of each other; however, 

Staff did not require prices to be identical or to occur during a choice 

market. Staff’s analysis identified numerous apparent wash trades at 

divergent prices between Enron and other nonaffiliated companies, but 

we were most concerned with trades that occurred between Enron and 

its affiliates. In fact, as the owner of EOL, Enron had the ability to act 

as both buyer and seller on a given transaction and use a series of buys 

and sells with a net cost of zero to manipulate the market. As part of 

our analysis, Staff identified suspicious trading activity for off-peak 

delivery of power at Palo Verde for the month of January 2002 (see 

Table VII-9). 

All trades in this sequence involved EPMI Long Term Southwest (an 

Enron affiliate) trading on EOL and occurred on August 14, 2001, 

over a 5-minute period. At 16:59:49 EPMI sold on EOL at a price of 

$18. Four seconds later EPMI purchased on EOL at a price of $40. At 

17:02:22 EPMI sold on EOL at a price of $15, before purchasing 3 

seconds later at a price of $25. Thirty-three seconds later EPMI sold 

on EOL at $25, and 13 seconds after that EPMI purchased on EOL at 

$15. At 17:03:46 EPMI sold at $40, and at 17:04:30 the sequence was 

completed with EPMI purchasing on EOL at $18. Note that the entire 

sequence of trades examined here is zero-sum. Therefore, collectively, 

these trades “washed.” The average price of the sequence was $24.50. 
Chapter VII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VII-13

Possible reasons for entering into these trades would be to give the 

impression of volatility or to affect average prices reported through 

market indices. In either event, affiliate trades completed at prices 

different from the true market would involve no net gain or loss to 

Enron as a whole. Under no circumstances can we comprehend any 

legitimate business reason to enter into such a string of transactions. 

The fact that these trades have a zero-sum gain to both parties also 

demonstrates how the price (or volume) of a transaction could be 

varied to make a wash trading effort less obvious, which may have 

been the case in this instance. Based on our analysis, we conclude that 

this activity was for no other reason than as a self-serving experiment 

to create volatility and manipulate industry data. 

Table VII-9. Affiliate Trading Between EOL and Enron Affiliate 

EPMI Long Term Southwest 

Time Wash Trade Pairs EOL Buy EOL Sell 

16:59:49 1 $18 

16:59:53 1 $40 

17:02:22 2 $15 

17:02:25 2 $25 

17:02:58 3 $25 

17:03:11 3 $15 

17:03:46 4 $40 

17:04:30 4 $18 

Average Price $24.50 $24.50 

The table reports August 14, 2001 power trades for off-peak physical delivery of 

power at Palo Verde during January 2002. 

One-to-Many Versus Manyto-Many Trading Platforms 

The design of EOL alone greatly lends itself to trading abuses and 

gave Enron unprecedented influence over energy markets. Using 

choice markets, wash trading, and other strategies, EOL’s one-to-many 

trading platform (in which EOL was the counterparty on every trade) 

enabled Enron to send false signals, including volume and pricing, to 

the marketplace. Because the platform was operated entirely under 

Enron’s discretion, Enron was able to present or influence the market 

in any way it wished. Specifically, Enron used its wash trading 

activities to deceive EOL users by giving the impression of a much 

deeper and more developed market, thus increasing the industry’s faith 

in EOL. Overall, these false signals increased Enron’s ability to 

unilaterally manipulate industry data and price indices under EOL’s 

guise as a legitimate exchange measuring real market activity. 

On the other hand, exchanges designed using a many-to-many 

platform better reflect legitimate bargaining between a willing buyer 
Chapter VII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VII-14

and seller and have the transparency necessary to instill confidence in 

the market. Staff believes the industry has already recognized the 

inherent advantages of many-to-many platforms over one-to-many 

platforms, resulting in the IntercontinentalExchange (ICE) becoming 

an industry leader. However, even these platforms are not immune to 

manipulation. In Chapter IX, Staff identifies circumstances on manyto-many platforms in which companies use the creditworthiness of 

counterparties to restrict trading activity to a single counterparty only. 

This enables two counterparties to complete prearranged wash trades 

over a many-to-many platform because only the counterparty they 

designate as having a sufficient level of credit would have the ability 

to qualify as an acceptable counterparty and complete the trade at the 

specific bid or offer price. 

Summary and Conclusions 

Regarding Wash Trades on 

EnronOnline 

The Trade Press has reported that, like a casino, Enron had the “house” 

advantage by trading on EOL in energy markets. Based on our analysis 

of the archived EOL database, Staff concludes that this is a flawed 

analogy. For example, a card game in a casino has set rules and all 

players can clearly see who they are competing against. On EOL, 

Enron had access to trading histories, limit orders, and volumes of 

trades, and therefore understood the liquidity of the market. In 

contrast, an unaffiliated trader on EOL was only able to see the 

activity that was posted electronically on the EOL screen. More 

significantly, when bid and ask prices were changed, the trader was 

unable to know if it was due to a legitimate trade or if prices were 

being manipulated. Unlike a casino game, this lack of transparency 

prevented the trader from knowing with whom he was competing. 

Moreover, because the EOL platform was wholly controlled by Enron, 

there were no fixed rules. The EOL operator had an infinite ability to 

manipulate what was posted in any of the ways described above. 

Simply put, the use of EOL enabled Enron to post any price it wanted. 

Staff concludes that wash trading was commonplace on the EOL 

trading platform between January 2000 and November 2001, and was 

more prevalent in the later months of this period. The wash trades 

considered here were identified by statistical criteria. Although it is 

unlikely that every pair of trades identified here meets the criteria of 

being prearranged and involving no economic risk, the overall 

evidence (including the use of choice markets, the volume of actual 

and apparent wash trades, and the existence of affiliate wash trades) 

supports the conclusion that trading abuses and market manipulation 

occurred on EOL. 
Chapter VII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VII-15

The Enron market maker may have taken positions that favored higher 

or lower prices. As such, we do not know whether the wash trades 

pushed gas or electric prices higher or lower. 

Recommendations 

Staff recommends that future trading platforms be designed to provide 

a sufficient level of transparency to enable users to understand the 

movements of the market. This transparency includes the disclosure of 

specific bids and offers and associated volumes for each product. Staff 

discourages any exchanges or trading platforms from being managed 

by any market participant, or combination thereof, in order to avoid 

the inevitable conflict of interest between the roles of brokers and 

traders. Finally, Staff recommends that the Commission establish 

specific rules banning any form of prearranged wash trading activities 

and prohibiting the reporting of any affiliate trading activities through 

industry indices. Strict adherence to these rules should be a condition 

of market-based rate or gas certificate authority. 

Staff also recommends that the Commission condition blanket gas 

certificates, as well as electric power market-based rates, to require 

that sellers who use trading platforms use only those trading platforms 

that employ a “credit change monitor” that would be used to help 

evaluate unusual patterns in credit changes in the platform. The reason 

for this requirement is that the credit structure could be used to 

manipulate access to other traders and, therefore, the perceived market 

pricing. In addition, the Commission should disallow market-based 

rates for public utilities that use trading platforms unless the owners or 

operators of those platforms agree to provide the Commission Staff 

with full access to trade reporting and order book information for the 

trading systems. 

Given the relative ease with which EOL manipulated the market and 

deceived its users, we do not believe a one-to-many trading platform is 

acceptable. We recognize that electronic trading on the EOL platform 

offered many advantages over historical voice trading. Even with its 

disadvantages, traders embraced EOL because it was faster, more 

convenient, and gave a widely accepted point of reference. A 

combination of our analysis and the further evolution of many-tomany platforms and their inherent advantages over EOL should render 

the one-to-many platform obsolete. Finally, we note that UBS 

Warburg, which now operates the EOL platform, suspended its use on 

December 10, 2002, due to a lack of trade volume. In any event, Staff 

recommends that market-based rates and gas certificate authority be 

conditioned on sellers not using their own one-to-many platform. 
Chapter VII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VII-16

Further, Staff recommends that Congress consider giving direct 

authority to a Federal agency to ensure that electronic trading 

platforms for wholesale sales of electric energy and natural gas in 

interstate commerce are monitored and provide market information 

that is necessary for price discovery in competitive energy markets. 
Chapter VIII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VIII-1

VIII. The Profitability of EnronOnline Information Advantage 

Staff, with assistance from Hendrik Bessembinder, Blaine Huntsman 

Chair in Finance, Eccles Business School, University of Utah, 

analyzed the profits earned by EnronOnline (EOL) market makers in 

five key product categories. As noted previously in this Report, the 

EOL platform was characterized by a one-to-many structure in which 

Enron was the counterparty to all customer trades. The EOL platform 

was quite successful for a period of time, attracting a substantial 

portion of overall trading in gas and power products. A question that 

arises is whether Enron was able to use its position as a market maker 

and counterparty to a substantial portion of industry trading activity to 

create monopoly profits for itself, at the expense of its trading partners. 

The answer to this question is of interest in terms of understanding 

how energy trading, and the trading of commodities and financial 

products in general, should optimally be structured. The one-to-many 

structure used by EOL is relatively rare. Most markets for energy 

products, including TradeSpark and the IntercontinentalExchange 

(ICE), are structured on a many-to-many basis. At ICE, disparate 

traders transact directly with each other and the role of the exchange is 

mainly limited to disseminating quotations and facilitating trade 

processing. However, other situations arise in which a single 

intermediary acts as the counterparty to a substantial portion of 

customer trades. For example, a New York Stock Exchange (NYSE) 

specialist may interact with the majority of customer orders in the case 

of thinly traded stocks. In this case, however, a specialist is subject to 

substantial affirmative obligations and oversight by the NYSE to 

ensure that the monopoly position is not used to earn unusual profits at 

the expense of customers. EOL market makers were subject to no such 

regulations. 

EOL market makers may have been able to earn monopoly profits by 

either of two complementary methods. First, they could have 

maintained wide bid-ask spreads. Second, they could have exploited 

the information advantage gained from seeing all customers’ orders 

and trades (while each customer saw only their own orders and trades) 

to speculate profitably. Any speculative profit accruing to Enron 

would have been earned at the expense of its counterparties. 
Chapter VIII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VIII-2

Measuring Trading Profits 

Consider a market maker who hypothetically begins a trading session 

with no cash and no inventory. Each purchase by the market maker 

expends cash but adds to inventory, while each market maker sale adds 

to cash but deletes inventory. Since market-maker purchases do not 

need to equate to market-maker sales over any given time interval, the 

accumulated market-making profit after t periods is measured not by 

the accumulated cash balance, but by the sum of cash accumulated and 

the value of inventory, as: 

Πt = Ct + It Vt

where Ct is the cash balance, It is inventory in physical units (It > 0 

implying that the market maker has accumulated the product and It < 0 

implying that the market maker has a net obligation to deliver the 

product), and Vt is the market value per unit of inventory. To measure 

inventory gains requires an assessment of the fair market value per 

unit of inventory, Vt. The approach used here is to rely on the final 

EOL trade price as a proxy for market value at the end of trading 

period t in each contract.1

This measure of total market-making profit can be restated in a more 

useful way. Let Bt and St denote the quantity bought and the quantity 

sold, respectively, by the market maker from the start of trading until 

time t. The lesser of Bt and St represents the amount of customer buy 

(or sell) orders that can be paired or matched with corresponding sell 

(or buy) orders, while the difference between Bt and St is the 

unmatched order flow that becomes the market maker’s net inventory, 

It, i.e., either increases or decreases in inventory. For example, if Bt = 

70 and St = 50, the lesser of Bt and St, or min(Bt,St) = 50, and It = 20. 

Let PB denote the average price for market-maker purchases and let PS

denote the average price for market-maker sales.2

 The market maker’s 

trading profit can be measured as: 

TPt = (min(Bt,St)) × (PS - PB). 

The market maker earns a trading profit if the average selling price 

exceeds the average purchase price. This price differential will reflect, 

 

1

Using the final trade price as a proxy for fair market value introduces some 

measurement error. The final trade may occur at either the ask or the bid, while fair 

value presumably lies between the bid and the ask quotes. However, this 

measurement error is likely to average to nearly zero across the many individual 

products studied. 

2

Each price is computed as the volume-weighted average across trades. 
Chapter VIII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VIII-3

but is not limited to, the bid-ask spread. It will also include speculative 

profits if the market maker is able to attract customer buy orders prior 

to price declines and customer sell orders prior to price increases. 

Trading profits depend on the excess of the average sell price over the 

average buy price and on the quantity of matched order flow, i.e., the 

lesser of Bt and St. In addition to this trading profit, total marketmaking profit will reflect gains and losses on the net order imbalances 

(i.e., inventory). If purchases exceed sales (i.e., inventory is positive), 

the inventory gain as of period t can be measured as: 

IGt = (Bt - St) × (Vt - PB). 

This reflects that the market maker gains from a long inventory 

position if the inventory is worth more than his average acquisition 

price. In cases where sales exceed purchases so that the market maker 

is net short, the inventory gain can be computed as: 

IGt = (St - Bt) × (PS - Vt), 

reflecting that a market maker gains on a short inventory position if the 

market value falls below his average sales price. Total market-making 

profit can then be measured as the sum of trading profits and inventory 

gains:3

Πt = TPt + IGt. 

This study estimates EOL market-making profits for five important 

energy product categories: power trades for physical delivery at the 

California-Oregon Border (COB); power trades for physical delivery 

at Palo Verde, Arizona; natural gas trades for physical delivery at 

Topock, California; natural gas trades for physical delivery at Henry 

Hub, Louisiana; and trades in the New York Mercantile Exchange 

(NYMEX) look-alike swap, which is a financial contract that mimics 

the NYMEX Henry Hub futures contract. The data cover the period 

January 1, 2000 to December 31, 2001. 

Profits are measured for each individual product in these categories 

from the time of the first trade in the product until the last trade. An 

individual product is distinguished by the product to be delivered, the 

period during which delivery is to take place, and the firmness of the 

obligation to deliver. For example, a “next-day” contract to deliver gas 

at Topock on September 27, 2001 would be evaluated separately from 

a “rest-of-month” contract to deliver gas on all remaining days during 

 

3

It can be verified that market-making profits measured as the sum of trading profits 

and inventory gain are algebraically identical to profits measured as the sum of cash 

balance and inventory value. 
Chapter VIII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VIII-4

September 2001. Trading profits are measured based on balanced 

trades (the minimum of EOL purchases and sales) from the first trade 

until the final trade in each individual product. Inventory profits are 

measured by comparing the average inventory acquisition price with 

the final EOL price for the product. Trading profits and inventory 

gains are then summed across all products within a category.4 

To demonstrate the calculation of market-making profit for a specific 

product, consider the contract for delivery of Topock gas on February 

28, 2001. This contract traded 44 times, all on February 27, 2001. 

Enron recorded purchases (Bt) of 195,000 MMBtu and sales (St) of 

210,000 MMBtu. Enron’s average purchase price (Pb) was $12.1795, 

while its average sales price (Ps) was $12.7976. The final trade in the 

product on EOL (Vt) was at a price of $12.75. The lesser of purchases 

or sales, representing matched order flow, is calculated as min(Bt,St) 

and equals 195,000 MMBtu. Net inventory is calculated by the 

equation St - Bt and represents a short position (sales exceeded 

purchases) of 15,000 MMBtu. 

Using the equation TPt = (min(Bt,St)) × (PS - PB), trading gains are 

195,000 × (12.7976 - 12.1795) = $120,530. Meanwhile, using the 

equation IGt = (St - Bt) × (PS - Vt), inventory gains are 15,000 × 

(12.7976 - 12.75) = $714. This reflects that in accumulating its short 

position, Enron sold at an average price (PS) slightly above the final 

price (Vt) for the product. The reasoning is that the short position must 

be covered from somewhere, and the final price is an estimate of the 

cost of doing so. Therefore, using the equation Πt = TPt + IGt, total 

market-making profit in the product defined as delivery of Topock gas 

on February 28, 2001 is $120,530 + $714 = $121,244. 

 

4

Physical purchases Bt, sales St, and inventory It = Bt - St depend on both the 

contracted quantity and the delivery horizon. For gas products, this is the product of 

the number of MMBtu and the number of days for which delivery is required. For 

power contracts, this is the number of MWh times the number of delivery days times 

the number of delivery hours (8 for off-peak contracts and 16 for on-peak contracts). 
Chapter VIII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VIII-5

EOL Market-Making Profits 

Table VIII-1 reports market-making profits in the five product 

categories described above. EOL market making was highly profitable 

in aggregate. Across the five product categories and the 2 years of 

data, trading profits exceeded $641 million. Estimated inventory gains 

were negative $54 million, leaving $587 million in combined marketmaking profit. This equated to an average market-making profit of 

$1,200 for each of the 507,000 trades, or profits that were 0.08 percent 

of the $506.7 billion in trading activity. 

The profitability of EOL market making varied dramatically across 

product categories. Trading of NYMEX look-alike swaps (financially 

settled swaps whose value is determined based on the settlement of 

NYMEX futures contracts) was immensely profitable, with trading 

gains exceeding $764 million and estimated gains on inventory 

amounting to another $156 million. This equates to a total marketmaking profit of $2,300 for each of the 400,000 EOL trades in 

NYMEX look-alike swaps. 

In contrast to the profitability of this swap trading, EOL market 

makers took losses in the other four product categories. COB power 

contracts yielded a trading gain of $10.3 million, but this was more 

than offset by estimated inventory losses of $25.7 million. Market 

making in Palo Verde power, Topock gas, and Henry Hub gas led to 

both trading losses and estimated losses on inventory. Trading losses 

on Palo Verde power contracts exceeded $128 million, while trading 

losses in Topock gas and Henry Hub gas were more moderate, 

amounting to $0.9 million and $3.8 million, respectively. Estimated 

inventory losses for Palo Verde power were also large, at $168 

million, while inventory losses for Topock and Henry Hub gas were 

estimated at $14 million and $2 million, respectively. 

Finding trading losses for these physical delivery contracts is 

surprising. EOL market makers generally charged a positive bid-ask 

spread, which provided positive trading profits, other things being 

equal. Measured trading profits were negative for all physical delivery 

products except COB power. This implies that the average price at 

which EOL sold was less than the average price at which EOL 

purchased. 

Finding the average EOL selling price to be less than the average EOL 

purchase price is surprising, considering that a positive bid-ask spread 
Chapter VIII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VIII-6

was charged. The following example illustrates how this occurred. 

Suppose that the EOL market maker initially posts an ask (willing to 

sell) quote of $3.02 and a bid (willing to buy) quote of $3.00. A 

customer buys (EOL sells) at the ask quote of $3.02. Shortly 

thereafter, the EOL market maker elects (perhaps after learning of 

bullish fundamental information) to update his quotes to $3.06 ask and 

$3.04 bid. A customer then sells at the $3.04 bid price, leaving EOL 

with a trading loss of $.02 in the matched pair of trades comprising 

this example. The key feature of this example is the upward movement 

of quotes after the customer purchase. The trading losses observed in 

this study for the Palo Verde, Topock, and Henry Hub products imply 

that adverse (to EOL) price changes between trades occurred 

systematically and more than offset the positive bid-ask spread. 

The negative estimates of inventory gain for the four physical delivery 

product categories imply that the EOL market maker tended to 

accumulate inventory at prices that exceed the eventual, final EOL 

price and tended to enter short inventory positions at prices below the 

eventual, final EOL price. These results with respect to both trading 

losses and inventory losses are the opposite of what would be expected 

if the EOL market maker were able to extract useful information from 

an observation of customer orders and trades. 

There are at least three possible explanations for the results observed 

here. One possibility is that EOL market makers, with the exception of 

the market maker in the NYMEX look-alike swap, were not as skilled 

at trading as their customers and thus were unable to earn trading 

profits despite the advantages of a positive bid-ask spread and superior 

information about customers’ orders and trades. However, this 

explanation does not seem plausible. A second possibility is that the 

EOL market makers in the physical delivery products were skilled and 

able to exploit their information advantage, but executed their most 

profitable trades on platforms other than EOL. This also seems highly 

unlikely. A third possibility is that EOL market makers used the 

information obtained from observing customers’ orders and trades in 

the physical markets not to trade profitably in those markets, but to 

trade profitably in various financial markets (futures, options, swaps, 

etc.) whose prices depend on fundamental factors in the physical 

markets. The large profits observed for the financial NYMEX lookalike swap are certainly consistent with this reasoning. It is also 

consistent with the manipulation strategies of the physical markets to 

profit in the financial markets (an issue described elsewhere in this 

Report). 

Tables VIII-2 through VIII-6 provide more detail on market-making 

profits in the individual categories, including profits by calendar 
Chapter VIII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VIII-7

month and profits on short-term (delivery horizon of 3 days or less), 

medium-term (delivery horizon between 4 and 31 days), and long-term 

(delivery on more than 31 days) contracts. A few results are notable. 

First, trading profits are highly variable over time. NYMEX look-alike 

swaps provide the most dramatic example. Trading profit exceeded 

$270 million in October 2001 (although this was dwarfed by an 

estimated inventory loss of $808 million during the same month). 

Trading losses of $270 million were incurred in December 2000, 

followed by trading gains of $166 million in January 2001. Similar 

variation on a smaller scale is observed in other markets. For example, 

COB power trading yielded profits of $30 million in January 2001 and 

losses of $19 million in May 2001. This type of variation in trading 

gains demonstrates that EOL market makers were active (and 

sometimes unsuccessful) speculators, not passive market makers 

earning a living from the bid-ask spread. This, in turn, exacerbates 

concerns that the market maker in a one-to-many platform could use 

the information in orders and trades to the detriment of customers. 

Conclusions 

The EOL platform had a large market share for trading energy 

products and was characterized by a one-to-many structure that 

allowed the EOL market maker to see all customer orders and trades, 

while each customer saw only its own orders and trades. These 

considerations lead to the possibility that the EOL market maker 

possessed a degree of monopoly power and would be able to earn 

monopoly profits at the expense of its customers. 

This chapter reports on market-making profits in five important energy 

product categories, including physical power for delivery at COB and 

Palo Verde, physical gas for delivery at Henry Hub and Topock, and 

financial swaps based on the NYMEX Henry Hub contract. In 

aggregate, EOL earned market-making profits in excess of $587 

million during 2000 and 2001 for these five product categories. The 

magnitude and time series variability of these profits suggest that EOL 

market makers did not simply act as passive suppliers of liquidity, i.e., 

one who stands ready to buy or sell and earn a moderate but steady 

profit from the bid-ask spread. Rather, EOL market makers were 

active and, on average, successful speculators. Somewhat surprisingly, 

market-making profits were concentrated in the only financial contract 

studied; EOL market makers actually sustained losses in the four 

physical delivery contracts examined. This result is consistent with the 

reasoning that EOL market makers used the information advantage 

gained from their central position in physical markets not to trade 

profitably in those markets, but to earn speculative profits in 

associated financial markets (futures, options, swaps, etc.). 
Chapter VIII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VIII-8

 

This analysis highlights the importance of structuring markets to create 

effective competition for customer orders. A one-to-many format with 

an unregulated and unconstrained market maker is unlikely to lead to 

efficient outcomes. Many markets around the world are changing to a 

many-to-many format in which customers interact directly with each 

other. In a many-to-many format, customer limit orders compete to 

win customer market orders. Alternately, competitive market 

outcomes might be attained by having numerous potential market 

makers compete for order flow, as on the Nasdaq Stock Market and in 

the brokered “upstairs markets” that often accompany formal 

exchanges. In the few situations where a one-to-many structure is still 

observed (for example, in thinly traded NYSE stocks where the 

specialist participates in most trades), the specialist is subject to 

numerous affirmative obligations to protect customers and to oversight 

by the Exchange. To summarize, efficient market structures require 

either vigorous competition among potential suppliers of liquidity or 

oversight of the designated liquidity supplier. 

Recommendation 

Staff recommends that the Commission condition market-based rates 

and blanket gas certificates to require that sellers who use electronic 

platforms use only those platforms that agree to provide the 

Commission with full access to trade and order book information and 

agree to appropriate monitoring requirements. 
Chapter VIII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VIII-9

 

Table VIII-1. Profits to Enron From EOL Market Making in Five Key Products 

Product Trading 

Profit 

Gain on 

Inventory

Total 

Profit 

Profit per 

Trade 

Profit as 

Percent of 

Trading 

Total 

Dollars 

Transacted

Number 

of Trades

 

COB Power Physical 10.3 -25.7 -15.4 -3.0 -0.58 2,637.5 5,099 

Palo Verde Power 

Physical -128.8 -168.5 -297.3 -11.4 -1.81 16,460.8 26,164 

Topock Gas Physical -0.9 -13.7 -14.6 -0.7 -0.42 3,496.3 21,928 

Henry Hub Gas 

Physical -3.8 -2.0 -5.8 -0.1 -0.09 6,606.1 52,828 

NYMEX Gas LookAlike Swaps 764.5 155.7 920.2 2.3 0.13 710,836.0 400,663 

 

Total of Five Products 641.3 -54.2 587.1 1.2 0.08 740,036.9 506,682 

Trading profit reflects the excess of the average Enron sell price over the average Enron buy price times the quantity of 

matched EOL trading. Gain on inventory reflects profits on the net EOL order imbalance, measured by the differential 

between the final EOL price for the contract and the average inventory acquisition price. Total profit is the sum of 

trading profit and gain on inventory. Total dollars transacted is the sum of total purchases and total sales on EOL. Profit 

as a percent of trading is total profit relative to total dollars transacted. Dollar amounts are in millions except for profit 

per trade, which is in thousands. The interval studied is January 2000 to December 2001. 
Chapter VIII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VIII-10

Table VIII-2. Profits to Enron From EOL Market Making: 

Trades for Physical Delivery of Power at the California-Oregon Border

Trading 

Profit 

Gain on 

Inventory

Total 

Profit 

Profit per 

Trade 

Profit as 

Percent of 

Trading 

Total 

Dollars 

Transacted

Number of 

Trades 

All Trades 10.3 -25.7 -15.4 -3.0 -0.58 2,637.5 5,099 

 

By Contract Term 

Long Term -10.9 -3.7 -14.6 -42.7 -1.13 1,292.2 342 

Medium Term 20.6 -20.6 0.0 0.0 0.00 1,127.5 959 

Short Term 0.5 -1.4 -0.8 -0.2 -0.39 217.8 3,798 

 

By Calendar Month 

January 2000 0.0 0.0 0.0 -0.2 -0.19 2.3 18 

February 2000 0.2 -0.2 -0.1 -0.3 -0.08 109.8 272 

March 2000 -0.6 -0.7 -1.3 -6.9 -1.44 92.1 193 

April 2000 0.4 -0.1 0.3 1.3 0.45 61.8 219 

May 2000 4.0 -16.7 -12.8 -133.3 -18.23 70.2 96 

June 2000 -4.2 -6.8 -11.0 -123.6 -19.19 57.3 89 

July 2000 -2.9 -8.9 -11.9 -54.4 -11.35 104.5 218 

August 2000 -4.1 0.4 -3.7 -13.1 -0.83 446.3 284 

September 2000 -0.3 -0.5 -0.8 -2.9 -0.35 230.3 275 

October 2000 -1.6 -1.6 -3.2 -6.0 -1.01 314.6 529 

November 2000 3.5 11.2 14.7 42.6 5.72 257.5 346 

December 2000 3.5 -12.8 -9.3 -174.8 -21.07 44.0 53 

January 2001 29.7 -68.6 -39.0 -299.9 -29.86 130.6 130 

February 2001 1.0 4.5 5.5 44.2 6.90 80.1 125 

March 2001 -1.8 -7.8 -9.6 -42.1 -3.59 266.7 227 

April 2001 0.0 0.6 0.6 3.0 1.15 51.6 196 

May 2001 -18.9 66.1 47.2 186.6 32.06 147.2 253 

June 2001 13.7 -0.5 13.2 54.4 25.59 51.4 242 

July 2001 -7.8 12.4 4.6 14.3 13.87 33.2 321 

August 2001 -2.6 2.3 -0.3 -1.0 -2.17 15.5 336 

September 2001 -1.2 2.5 1.3 4.1 7.70 16.9 317 

October 2001 0.0 -0.6 -0.6 -2.4 -5.35 10.8 244 

November 2001 0.5 0.2 0.7 6.1 1.65 42.9 116 

December 2001 0 0 0 0 0 0 0 

Trading profit reflects the excess of the average Enron sell price over the average Enron buy price times the quantity of 

matched EOL trading. Gain on inventory reflects profits on the net EOL order imbalance, measured by the differential between 

the final EOL price for the contract and the average inventory acquisition price. Total profit is the sum of trading profit and gain 

on inventory. Total dollars transacted is the sum of total purchases and total sales on EOL. Profit as a percent of trading is total 

profit relative to total dollars transacted. Dollar amounts are in millions except for profit per trade, which is in thousands. Shortterm contracts involve delivery periods of 3 days or less. Medium-term contracts involve delivery periods of 4 to 31 days. Longterm contracts involve delivery periods over 31 days. 
Chapter VIII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VIII-11

Table VIII-3. Profits to Enron From EOL Market Making: 

Trades for Physical Delivery of Power at Palo Verde, Arizona

Trading 

Profit 

Gain on 

Inventory

Total 

Profit 

Profit per 

Trade 

Profit as 

Percent of 

Trading 

Total 

Dollars 

Transacted

Number of 

Trades 

All Trades -128.8 -168.5 -297.3 -11.4 -1.81 16,460.8 26,164 

 

By Contract Term 

Long Term -55.7 -100.0 -155.7 -75.3 -2.13 7,293.9 2,069 

Medium Term -74.3 -60.5 -134.8 -17.1 -1.59 8,502.7 7,896 

Short Term 1.2 -8.0 -6.8 -0.4 -1.03 664.1 16,199 

 

By Calendar Month 

January 2000 0.0 0.0 0.0 -0.1 -0.07 3.6 25 

February 2000 0.3 -1.1 -0.9 -2.1 -0.60 141.6 411 

March 2000 -0.8 -0.9 -1.8 -3.9 -0.97 180.7 446 

April 2000 0.5 3.3 3.8 8.9 1.49 253.8 426 

May 2000 -0.9 36.0 35.1 155.9 18.35 191.1 225 

June 2000 33.8 3.2 36.9 95.4 6.81 542.0 387 

July 2000 0.0 13.3 13.4 26.1 3.27 408.6 511 

August 2000 -13.4 -34.4 -47.8 -60.3 -4.12 1,159.1 793 

September 2000 16.8 4.7 21.5 25.9 2.61 822.6 828 

October 2000 -8.2 0.7 -7.5 -6.6 -1.06 712.5 1,137 

November 2000 24.7 -77.1 -52.4 -37.9 -5.40 969.8 1,382 

December 2000 10.2 -290.0 -279.8 -690.7 -94.38 296.4 405 

January 2001 13.7 263.9 277.6 488.8 35.89 773.6 568 

February 2001 -115.5 91.2 -24.3 -42.9 -2.45 990.3 566 

March 2001 39.3 58.3 97.6 97.0 7.49 1,302.7 1,006 

April 2001 36.7 -158.1 -121.4 -83.9 -6.78 1,789.5 1,446 

May 2001 -27.2 -90.0 -117.3 -72.0 -6.29 1,863.6 1,628 

June 2001 -93.9 34.1 -59.7 -27.2 -4.24 1,408.4 2,198 

July 2001 0.5 -61.3 -60.8 -31.6 -12.62 481.9 1,921 

August 2001 -11.6 5.2 -6.4 -2.1 -0.99 648.4 3,021 

September 2001 -19.4 15.0 -4.4 -2.0 -1.32 332.4 2,217 

October 2001 -4.6 -12.9 -17.4 -6.1 -3.45 505.8 2,865 

November 2001 -9.9 28.6 18.7 10.7 2.74 682.1 1,752 

December 2001 0 0 0 0 0 0 0 

Trading profit reflects the excess of the average Enron sell price over the average Enron buy price times the quantity of 

matched EOL trading. Gain on inventory reflects profits on the net EOL order imbalance, measured by the differential between 

the final EOL price for the contract and the average inventory acquisition price. Total profit is the sum of trading profit and gain 

on inventory. Total dollars transacted is the sum of total purchases and total sales on EOL. Profit as a percent of trading is total 

profit relative to total dollars transacted. Dollar amounts are in millions except for profit per trade, which is in thousands. Shortterm contracts involve delivery periods of 3 days or less. Medium-term contracts involve delivery periods of 4 to 31 days. Longterm contracts involve delivery periods over 31 days. 
Chapter VIII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VIII-12

Table VIII-4. Profits to Enron From EOL Market Making: 

Trades for Physical Delivery of Gas at Topock, California 

Trading 

Profit 

Gain on 

Inventory

Total 

Profit 

Profit per 

Trade 

Profit as 

Percent of 

Trading 

Total 

Dollars 

Transacted

Number of 

Trades 

All Trades -0.9 -13.7 -14.6 -0.7 -0.42 3,496.3 21,928 

 

By Contract Term 

Long Term 0 0 0 0 0 0 0 

Medium Term 2.1 -6.6 -4.5 -3.8 -0.40 1,115.8 1,179 

Short Term -3.0 -7.2 -10.2 -0.5 -0.43 2,380.5 20,749 

 

By Calendar Month 

January 2000 0 0 0 0 0 0 0 

February 2000 0.0 0.0 0.0 0.0 0.09 3.7 199 

March 2000 0.0 0.0 0.0 0.0 -0.12 10.8 497 

April 2000 0.0 0.0 0.0 0.0 -0.10 10.3 445 

May 2000 0.0 -0.1 -0.1 -0.1 -0.10 62.8 1,129 

June 2000 0.0 0.0 -0.1 0.0 -0.07 74.9 1,305 

July 2000 0.0 0.0 0.0 0.0 -0.03 67.7 1,145 

August 2000 -0.6 0.5 -0.1 -0.1 -0.09 162.1 1,236 

September 2000 0.0 0.0 0.0 0.0 0.02 127.5 1,222 

October 2000 -2.3 0.7 -1.6 -1.4 -0.73 224.5 1,156 

November 2000 -2.1 -3.3 -5.3 -3.1 -1.34 398.9 1,703 

December 2000 2.6 -5.8 -3.2 -1.3 -0.35 902.4 2,434 

January 2001 0.2 -2.4 -2.2 -1.3 -0.69 314.2 1,623 

February 2001 3.0 -0.1 2.9 1.9 0.66 440.3 1,557 

March 2001 0.0 -1.9 -1.9 -6.4 -2.46 76.6 296 

April 2001 -0.6 -0.2 -0.8 -1.0 -0.45 184.9 865 

May 2001 0.1 1.0 1.1 1.2 0.78 138.1 921 

June 2001 -0.7 0.2 -0.5 -0.4 -0.44 111.6 1,315 

July 2001 -0.2 -1.0 -1.2 -1.4 -1.77 66.5 841 

August 2001 -0.3 -1.2 -1.5 -1.9 -2.92 51.6 787 

September 2001 0.0 0.0 0.0 -0.1 -0.17 25.8 577 

October 2001 0.0 0.0 0.0 0.0 0.02 29.9 442 

November 2001 0.0 0.0 0.0 -0.2 -0.33 11.3 233 

December 2001 0 0 0 0 0 0 0 

Trading profit reflects the excess of the average Enron sell price over the average Enron buy price times the quantity of 

matched EOL trading. Gain on inventory reflects profits on the net EOL order imbalance, measured by the differential between 

the final EOL price for the contract and the average inventory acquisition price. Total profit is the sum of trading profit and gain 

on inventory. Total dollars transacted is the sum of total purchases and total sales on EOL. Profit as a percent of trading is total 

profit relative to total dollars transacted. Dollar amounts are in millions except for profit per trade, which is in thousands. Shortterm contracts involve delivery periods of 3 days or less. Medium-term contracts involve delivery periods of 4 to 31 days. Longterm contracts involve delivery periods over 31 days. 
Chapter VIII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VIII-13

Table VIII-5. Profits to Enron From EOL Market Making: 

Trades for Physical Delivery of Gas at Henry Hub, Louisiana 

Trading 

Profit 

Gain on 

Inventory

Total 

Profit 

Profit per 

Trade 

Profit as 

Percent of 

Trading 

Total 

Dollars 

Transacted

Number 

of Trades

All Trades -3.8 -2.0 -5.8 -0.1 -0.09 6,606.1 52,828 

 

By Contract Term 

Long Term 0 0 0 0 0 0 0 

Medium Term -1.8 0.4 -1.5 -0.4 -0.08 1,819.5 3,524 

Short Term -1.9 -2.4 -4.3 -0.1 -0.09 4,786.6 49,304 

 

By Calendar Month 

January 2000 0.0 0.0 0.0 0.0 -0.20 0.3 14 

February 2000 0.0 -0.1 -0.1 -0.2 -0.53 13.0 328 

March 2000 0.0 0.0 0.0 0.0 0.04 36.9 570 

April 2000 0.0 -0.1 -0.1 -0.1 -0.15 48.4 750 

May 2000 -0.1 -0.2 -0.2 -0.2 -0.12 209.4 1,050 

June 2000 -0.4 0.0 -0.4 -0.2 -0.09 432.1 1,864 

July 2000 -0.1 -0.1 -0.2 -0.2 -0.12 209.8 1,237 

August 2000 0.1 -0.1 0.0 0.0 -0.01 309.5 1,546 

September 2000 0.0 -0.2 -0.2 -0.1 -0.08 242.2 1,225 

October 2000 -0.1 -0.2 -0.4 -0.2 -0.11 336.4 1,972 

November 2000 -0.3 0.6 0.3 0.1 0.04 741.2 3,309 

December 2000 -1.6 0.6 -1.0 -0.4 -0.20 474.3 2,327 

January 2001 0.0 -0.6 -0.5 -0.2 -0.14 374.0 2,328 

February 2001 0.3 -0.2 0.2 0.1 0.04 393.4 2,579 

March 2001 -0.3 0.0 -0.3 -0.1 -0.07 414.5 3,386 

April 2001 -0.2 -0.3 -0.5 -0.1 -0.13 394.6 3,477 

May 2001 -0.2 -0.2 -0.4 -0.1 -0.10 396.7 3,540 

June 2001 -0.5 -0.4 -0.9 -0.2 -0.17 568.7 4,579 

July 2001 -0.1 0.0 -0.1 0.0 -0.04 290.6 3,855 

August 2001 -0.5 -0.2 -0.7 -0.2 -0.26 267.8 3,625 

September 2001 0.0 0.1 0.2 0.1 0.13 132.0 2,603 

October 2001 0.2 -0.1 0.1 0.0 0.04 245.3 4,698 

November 2001 -0.1 -0.3 -0.4 -0.2 -0.57 75.2 1,966 

December 2001 0 0 0 0 0 0 0 

Trading profit reflects the excess of the average Enron sell price over the average Enron buy price times the quantity of 

matched EOL trading. Gain on inventory reflects profits on the net EOL order imbalance, measured by the differential between 

the final EOL price for the contract and the average inventory acquisition price. Total profit is the sum of trading profit and gain 

on inventory. Total dollars transacted is the sum of total purchases and total sales on EOL. Profit as a percent of trading is total 

profit relative to total dollars transacted. Dollar amounts are in millions except for profit per trade, which is in thousands. Shortterm contracts involve delivery periods of 3 days or less. Medium-term contracts involve delivery periods of 4 to 31 days. Longterm contracts involve delivery periods over 31 days. 
Chapter VIII 

Docket No. PA02-2-000 Price Manipulation in Western Markets VIII-14

Table VIII-6. Profits to Enron From EOL Market Making: 

Trades in NYMEX Look-Alike Swaps

Trading 

Profit 

Gain on 

Inventory

Total 

Profit 

Profit per 

Trade 

Profit as 

Percent of 

Trading 

Total 

Dollars 

Transacted

Number of 

Trades 

All Trades 764.5 155.7 920.2 2.3 0.13 710,836 400,663 

 

By Contract Term 

Long Term 252.8 900.0 1152.8 14.0 0.39 294,442 82,220 

Medium Term 511.7 -744.3 -232.6 -0.7 -0.06 416,394 318,443 

Short Term 0 0 0 0 0 0 0 

 

By Calendar Month 

January 2000 0.3 -0.3 0.1 0.4 0.05 175 195 

February 2000 2.6 7.2 9.8 2.6 0.27 3,624 3,770 

March 2000 -2.2 16.3 14.1 2.6 0.20 7,127 5,461 

April 2000 4.6 11.8 16.4 3.2 0.24 6,696 5,166 

May 2000 42.7 9.5 52.2 4.4 0.29 18,183 11,781 

June 2000 12.6 -31.6 -19.0 -1.1 -0.07 28,197 17,750 

July 2000 58.9 -54.4 4.5 0.4 0.03 17,044 12,315 

August 2000 15.0 206.1 221.1 15.8 0.91 24,395 13,962 

September 2000 45.6 43.8 89.4 7.0 0.33 26,913 12,852 

October 2000 67.6 -257.3 -189.7 -12.6 -0.54 35,143 15,081 

November 2000 -108.8 49.0 -59.8 -2.7 -0.11 53,659 22,453 

December 2000 -269.9 120.0 -149.9 -7.7 -0.33 45,577 19,437 

January 2001 165.6 -41.0 124.6 6.2 0.30 42,151 20,037 

February 2001 120.5 -62.0 58.5 3.2 0.16 35,480 18,502 

March 2001 46.9 -1.3 45.6 2.4 0.11 41,031 19,251 

April 2001 18.9 28.4 47.3 2.4 0.12 39,621 19,466 

May 2001 106.9 69.4 176.3 7.9 0.41 43,254 22,238 

June 2001 1.2 150.6 151.8 5.7 0.33 46,339 26,413 

July 2001 75.3 -61.9 13.3 0.5 0.03 39,619 26,231 

August 2001 10.0 431.8 441.8 16.0 1.07 41,228 27,630 

September 2001 32.1 217.6 249.7 12.4 0.91 27,391 20,124 

October 2001 270.8 -807.8 -537.1 -15.1 -1.05 50,999 35,559 

November 2001 40.2 57.9 98.1 3.9 0.27 36,933 24,954 

December 2001 7.1 54.0 61.1 1744.9 104.67 58 35 

Trading profit reflects the excess of the average Enron sell price over the average Enron buy price times the quantity of 

matched EOL trading. Gain on inventory reflects profits on the net EOL order imbalance, measured by the differential between 

the final EOL price for the contract and the average inventory acquisition price. Total profit is the sum of trading profit and gain 

on inventory. Total dollars transacted is the sum of total purchases and total sales on EOL. Profit as a percent of trading is total 

profit relative to total dollars transacted. Dollar amounts are in millions except for profit per trade, which is in thousands. Shortterm contracts involve delivery periods of 3 days or less. Medium-term contracts involve delivery periods of 4 to 31 days. Longterm contracts involve delivery periods over 31 days. 
Chapter IX 

Docket No. PA02-2-000 IX-1 Price Manipulation in Western Markets

IX. Enron’s Manipulation of the Natural Gas Markets, Portions 

of the Enron Online Black Box Revealed, and Forward Looking 

Recommendations1

Background 

Financial energy products are used to hedge risk on physical energy 

products, and the two are interrelated. Physical transaction prices 

dictate the pricing of financial products, i.e., financial products derive 

their value from the underlying physical market. The depth and 

liquidity of financial energy markets are far greater than those of 

physical markets. 

The relationship between financial and physical energy products and 

the relatively thinner and less liquid physical markets provides 

opportunities to manipulate the physical markets and profit in the 

financial markets. This is true regardless of whether the manipulation 

in the physical market raises or lowers prices for the physical 

commodity. 

This chapter analyzes an experiment to test a manipulation strategy 

and an actual manipulation by Enron using EnronOnline (EOL). Enron 

manipulated the price of physical gas upward, then downward. 

Although the price change in the physical markets was only about 

$0.10/MMBtu, Enron profited due to the effect that this small change 

in the physical price had on its large financial position. Enron earned 

more than $3 million from this manipulation. 

FERC Staff obtained information indicating that Enron traders 

potentially manipulated the price of natural gas at the Henry Hub in 

Louisiana to profit from positions taken in the over-the-counter (OTC) 

financial derivatives markets (OTC markets). Through interviews, 

depositions, document review, and data analysis, Staff found 

substantial evidence corroborating the initial information.2

 It is Staff’s 

opinion that Enron traders, through transactions falling within the 

Commission’s jurisdiction and authorized through a blanket certificate, 

 

1

This section was prepared by FERC Staff with the assistance of outside consultant 

Chester Spatt, Mellon Bank Professor of Finance, Graduate School of Industrial 

Administration, Carnegie Mellon University. 

2

During the investigation into Enron and EnronOnline, FERC provided the 

Commodity Futures Trading Commission (CFTC) with access to the electronic 

databases that FERC Staff relied on to generate the analysis for this and other 

chapters of the Report. FERC provided the CFTC, Department of Justice (DOJ), and 

Securities and Exchange Commission (SEC) with a preliminary draft of this Report 

on March 3, 2003, asking for comments and concerns. FERC then met with the 

CFTC, DOJ, and SEC on March 10, 2003 to discuss this Report prior to its issuance. 
Chapter IX 

Docket No. PA02-2-000 IX-2 Price Manipulation in Western Markets

successfully manipulated the physical natural gas markets. The 

manipulation yielded profits in the financial OTC markets.3 

Staff reviewed documents disclosed by Enron describing the same 

strategy hypothetically in a memorandum predating the manipulation 

that Staff discovered.4 This caused concerns that Enron traders 

executed this strategy at other times and in other locations. As part of 

its research into the market manipulation, Staff identified key elements 

relating to the execution of the market manipulation strategy. Using 

this information, Staff proceeded to search for additional occurrences 

of manipulations at other times and in other locations. Staff’s search 

resulted in the discovery of trading behavior executed by Reliant that 

involved a different strategy but used similar techniques regarding the 

physical purchase of gas. As described in Chapter II, this trading 

behavior caused at least a portion of the increase in gas prices at the 

Southern California Border from December 2000 through February 

2001. In the following sections, Staff describes the financial and 

physical gas markets, necessary conditions for manipulation, 

manipulation strategies, and an actual manipulation of Henry Hub 

prices by Enron traders. 

The Relationship Between 

Natural Gas Financial 

Derivatives and the 

Underlying Physical Gas 

Contracts 

General Purpose for Physical and Financial Natural Gas Markets 

Natural gas traders and marketers in the United States use many 

different physical and financial natural gas products to absorb the risks 

associated with fluctuating natural gas prices. For example, traders can 

purchase gas each day in the spot markets or they can agree in advance 

 

3

Commission jurisdiction is pursuant to the Commission’s authority under the 

Natural Gas Act (NGA) of 1938, particularly Sections 1(b), 4(a), and 5(a). The 

blanket certificate is provided in Parts 284.284 and 284.402 of this Commission’s 

Regulations.

4

The following excerpt is a hypothetical example extracted from an Enron document 

to which Enron waived privileges: “Leveraged Trading – Trading Company (“TC”) 

is short fixed-price physical gas. TC is long financial Gas Daily through gas swap 

agreements. TC starts buying physical gas and goes beyond what is necessary to 

cover its short position; prices in the cash market increase and prices reported in Gas 

Daily are much higher. What are the legal issues? Are the risks greater if the swap 

reference price is the “average of the last three days of the month” or “average of all 

the days in a calendar month”?” Bates # EC001653170; “Discussion of Hypothetical 

Trading Strategies,” January 3, 2001. 
Chapter IX 

Docket No. PA02-2-000 IX-3 Price Manipulation in Western Markets

to purchase gas based on a daily index. Traders also can lock in an 

average gas price through monthly or longer term physical contracts. 

Alternatively, these fixed-price contracts can be replicated or achieved 

through the combined execution of physical index purchases, basis 

swaps, Gas Daily swaps, and NYMEX futures or swaps. Depending 

on whether the trader needs to buy or sell gas in the future, the trader 

would buy or sell the above products. Based on the risks the trader is 

most concerned about, the trader may enter some or all of these 

transaction types or the trader may choose to defer trading until prices 

become more favorable. 

The availability of diverse types of instruments for bearing risk 

facilitates the allocation of risk to those best situated to bear these 

risks, increasing the efficiency of the capital market and lowering the 

cost of risk bearing. Financial services and energy firms that operate 

across the relevant markets are potentially willing to intermediate 

(transform) risks because of their own ability to hedge or offset the 

underlying exposure. 

Importance of Liquidity in the Natural Gas Markets 

Liquidity refers to the ability to sell an asset and convert it into cash, at 

a price close to its fundamental value, in a short period of time. 

Generally, liquid markets form when a large number of buyers and 

sellers trade substantial volumes of a product. In the natural gas 

marketplace, the “gold standard” instruments are the physical products 

traded for delivery at the Henry Hub location, where many pipelines 

converge near the supply region in Louisiana. In the financial markets, 

the most important instruments are the NYMEX futures contracts, 

which settle based on the price of physically delivered natural gas at 

the Henry Hub. The settlement of the monthly NYMEX futures is 

determined 3 days from the end of the prior month.5

 Because of the 

direct linkage between Henry Hub and important delivery points in the 

Northeast and Midwest, the Henry Hub physical market (relative to 

other physical markets) and the NYMEX futures market both tend to 

be relatively deep or liquid, thereby providing attractive instruments 

for many market participants. These instruments correlate reasonably 

with the hedging needs of many individual market participants. 

Consequently, although Henry Hub-related markets expose many 

individual participants to basis risk relative to gas price risk at other 

locations, the relative attractiveness of the Henry Hub to many of the 

market participants leads to a concentration of trading activity in 

Henry Hub-based physical and financial products. 

 

5

A NYMEX futures contract is based on the delivery of 10,000 MMBtu. See 

www.nymex.com.
Chapter IX 

Docket No. PA02-2-000 IX-4 Price Manipulation in Western Markets

The activity and depth on the NYMEX (next month) futures contract is 

much greater than that for the Henry Hub next-day physical contract 

because of the longer 1-month term associated with the contract, 

which reflects planned gas needs as opposed to marginal unanticipated 

changes to needs; the attractiveness of financial settlement; and the 

credit risk reduction associated with daily mark-to-market settlement.6

The liquidity of the Henry Hub next-day physical market is greater 

than the liquidity of physical markets in other locations. Because of the 

differing liquidities in these markets, the price impact of trading 

positions of a given size in these instruments can be relatively less than 

for instruments traded in smaller, less active products. As in various 

market settings, liquidity is self-reinforcing because market 

participants have a strong incentive to trade using the deepest and most 

liquid markets. Trading activity attracts trading activity and liquidity 

concentrates at the deepest markets. Traders often use the NYMEX 

futures to hedge overall market conditions because of its liquidity. 

Physical Transaction Values Dictate the Pricing of Financial Derivatives 

Natural gas financial derivatives “derive” their value from transaction 

prices at major receipt and delivery points for natural gas. A 

significant variety of natural gas financial derivatives exist. 

The most commonly traded natural gas financial derivative is the 

NYMEX futures contract, which derives its value from physical 

transactions occurring at Henry Hub in Louisiana.7 The other primary 

financial derivatives are Gas Daily swaps and basis swaps, which are 

traded in the OTC markets. These products relate to the Henry Hub 

and many other locations in North America. The Gas Daily swap 

hedges the price risk between the price quoted in Inside FERC (whose 

settlement is determined by the average price for next-month gas at the 

specified location over the last 5 trading days for the current month) 

and the price quoted in the Gas Daily index. Basis swaps provide a 

hedge against relative price changes between two different locations 

(primarily the Henry Hub and another location), swapping the prices 

posted as the last-day NYMEX settlement price and the price quoted 

in Inside FERC for the location being hedged (adjusted by a market 

premium). One of the most common OTC derivative products is 

known as the “OTC swap,” also known as the NYMEX look-alike 

 

6

Daily “mark-to-market” settlement is the daily cash flow system used by U.S. 

futures exchanges to maintain a minimum level of margin equity for a given futures 

or options contract position by calculating the gain or loss in each contract position 

resulting from changes in the price of the futures or options contracts at the end of 

the trading day. See www.nymex.com. 

7

The specific delivery location is the Sabine Pipe Line Co.’s Henry Hub in 

Louisiana. See www.nymex.com. 
Chapter IX 

Docket No. PA02-2-000 IX-5 Price Manipulation in Western Markets

swap. This swap derives its value from the price of the NYMEX 

natural gas futures contract. 

Henry Hub physical transactions strongly correlate with the NYMEX 

futures and the related OTC NYMEX look-alike swaps because the 

NYMEX futures directly settle based on the Henry Hub physical 

delivery price. The correlation between the NYMEX futures and nextday physical gas at Henry Hub is not perfect (although it is very high) 

because of various timing differences between the futures contract and 

the next-day physical contract. In particular, the futures contract 

represents delivery in the following month and the Henry Hub physical 

contract represents next-day delivery.8 The volatility of Henry Hub 

should be greater to reflect the inherent volatility in the value of a 

next-day product (which reflects unanticipated demands) versus the 

volatility in a monthly futures contract (which reflects anticipated 

demand). This is reinforced by the mean reversion of commodity spot 

prices. 

Many other financial derivative contracts relate in similar ways to 

underlying physical transactions of varying terms. The direct and 

indirect relationships between financial derivatives and physical 

transactions provide the linkage needed to exercise particular 

manipulation strategies. Generally, the dependence of financial 

derivative products on physical transaction values results in a strong 

correlation between changes in the value of the physical product and 

the financial derivatives. For example, if next-day physical gas (gas 

that will be delivered the next day) trades at a high level on a particular 

day, this affects the settlement of the portion of a Gas Daily financial 

swap that settles the next day. Looking forward, the increase in spot 

prices for gas indicates an increase in demand for gas (or a decrease in 

inventory) and may change expectations for prices of gas in the future 

as well. A change in expectations for future natural gas prices will 

affect the value of financial derivative transactions designed to settle 

on those future days. It is this interrelationship that provides an 

opportunity for manipulation. 

 

8

Delivery under NYMEX contracts shall take place no earlier than the first calendar 

day of the delivery month and shall be completed no later than the last calendar day 

of the delivery month. All deliveries shall be made at an hourly and daily rate of flow 

that is as uniform as possible over the course of the delivery month. See 

www.nymex.com. 
Chapter IX 

Docket No. PA02-2-000 IX-6 Price Manipulation in Western Markets

Relative Differences in Liquidity Across Markets Combined With 

Correlated Values Between Those Markets Provides an Opportunity for 

Profitable Manipulation 

Although there are strong inherent advantages to the diverse ways in 

which risks are packaged in the marketplace, the presence of 

alternative instruments reflecting similar risks generates a need for 

correct relative pricing to avoid the ability to generate arbitrage profits. 

Arbitrage profits are riskless profits generated by simultaneously 

selling an overpriced asset while purchasing an underpriced 

substantively equivalent asset.9 For example, if two marketplaces 

existed for the same commodity and the first market offered to buy the 

commodity at $5.00 while the other market offered to sell the 

commodity at $4.00, an opportunity to simultaneously buy from the 

$4.00 market and sell to the $5.00 market would arise, yielding a $1.00 

profit as long as prices remained the same. As traders take advantage 

of the arbitrage opportunity, buying pressure in the cheaper market and 

selling pressure in the expensive market brings the markets in line, 

resulting in correct relative prices. For similar, but not substantively 

identical products, these correct relative prices are also expected. 

However, any substantive differences in the products create some risk 

that variations may occur or persist. 

The expectation that related products exhibit correct relative prices 

results in a strong correlation between prices. This creates the potential 

to manipulate the related products for a profit. This potential arises 

when, in the short run, transactions of the same size affect prices in the 

two markets differently. One factor that distinguishes between markets 

is relative liquidity. If a market involved a much larger daily 

transactional volume and a greater number of buyers and sellers 

relative to another market, the price impact of individual trades might 

be less in the first market. To take advantage of the different impact, a 

trader could first take a long (or short) position in the market with 

greater liquidity. A long position would rise in value as the relevant 

gas prices rise, while a short position would rise in value as those gas 

prices fall.10 The trader could then attempt to increase (or decrease) the 

 

9

See The Relative Pricing of High Yield Debt: The Case of RJR Nabisco Holdings 

Capital Corporation,” R. Dammar, K. Dunn, and C. Spatt, American Economic 

Review, Vol. 83, Issue 5 (Dec. 1993) pp. 1090-1111. 

10A “long position” is a financial stake that increases in value when the price level or 

quoted rate of an asset, index, or product rises. A “short position” is a financial stake 

that increases in value when the price level or quoted rate of an asset, index, or 

product falls. A “short sale” is a short position that arises from the sale of a product 

not owned by the seller. Here, the seller borrows and sells another’s asset with an 

obligation to return the asset. To close the short sale, the seller buys back the same 
Chapter IX 

Docket No. PA02-2-000 IX-7 Price Manipulation in Western Markets

price of the product in the less liquid market in order to increase (or 

decrease) the price in the related more liquid market, benefiting the 

trader’s position. On a net basis, the trader would profit from the 

manipulation strategy if the absolute value of the gains in the more 

liquid market exceeds the losses in the less liquid market. 

The necessity for relative differences in liquidity is illustrated in a case 

where a market exists for a single asset in which purchases and sales 

affect the trading price. In this market, the trader can push up prices 

with additional purchases; however, when he attempts to realize profits 

at the higher prices, his sales depress the price, eliminating his ability 

to generate a positive return through the manipulation. This 

emphasizes the importance of markets with different liquidity. 

In the presence of two assets with different price sensitivities, price 

manipulation is possible under the following conditions: First, we 

suppose that the change in the value of the financial derivative product 

is sensitive to changes in the value of the physical spot product (e.g., 

changes in the price of the physical spot product affect the market 

value of the derivative instrument as a consequence of the correlation 

between the two). Second, the market for the physical spot product is 

less liquid than the market for the associated financial derivative 

instrument (i.e., there is a greater price impact for a given purchase of 

the physical spot product than there would for the associated derivative 

security). Under these assumptions the loss from manipulating the 

physical price (due to the direct price impact) would be less than the 

potential profit on the derivative because of the difference in depths 

between the two markets and the ability to implement a large-scale 

futures trade. As this discussion suggests, the physical spot and 

derivative instruments are correlated, and the spot market has less 

depth than the market for the derivative security, thus generating the 

ability to manipulate the physical spot market to profit in the financial 

derivatives markets.11

Interesting perspectives about these features are included in the 

depositions of Enron’s natural gas traders. The trader that evidence 

indicates planned the manipulation stated in a deposition that: 

“ ...there tends to be more of a correlation between people 

watching the Henry Hub than any other location because that is 

the physical delivery point of the [NYMEX] futures contract. 

 

asset and returns it to the owner. The short sale is profitable if the price of the asset 

falls, allowing the short seller to buy back the asset at a lower price. 

11Futures Manipulation with “Cash Settlement,” P. Kumar and D. Seppi, The Journal 

of Finance, Volume 47, Issue 4 (Sep. 1992), pp. 1485-1502 provides a formal 

analysis of the manipulation of a futures contract in this manner. 
Chapter IX 

Docket No. PA02-2-000 IX-8 Price Manipulation in Western Markets

So people watch that much more often than they watch any 

other point in the United States.” 12 

Of course, the correlation reflects the settlement procedure for the 

futures contract. 

Another trader, who worked on the same team as the above trader, 

provided further detail on the correlation of the Henry Hub next-day 

physical market and the NYMEX futures contract. When asked, “in 

your expertise as a gas trader, how large do you expect that correlation 

to be, based on your historical knowledge of correlations between the 

[NYMEX and the Henry Hub spot market]?”, he stated: 

“I am not a statistician, but I would think that it’s probably 

higher than 80 percent.”13

Another element necessary to the manipulation is that the financial 

derivatives markets must have greater liquidity than the physical 

markets. The relative illiquidity in the physical market provides the 

trader with the opportunity to push the price up (or down) with his 

purchases (or sales). The liquidity of the financial market allows the 

trader to take a relatively larger position in that market without 

pushing prices up or down when entering or exiting that market. The 

financial markets are generally known to be far more liquid than the 

spot physical markets. Regarding the issue of relative liquidity, one 

Enron trader who worked on the team that manipulated the Henry Hub 

next-day market stated: 

“The volume of cash that is trading is insignificant compared to 

the amount of futures contracts that are trading.”14

The questioner then asked, “So you would say that the NYMEX 

futures market is far deeper or more liquid than [the Henry Hub nextday market]?” The trader responded: 

“Extraordinarily.”15

 

12For the analyses provided in this chapter, Staff primarily used data extracted from 

Enron databases. Staff also used data provided directly by Enron to FERC in various 

electronic and printed formats. Other than data, Staff primarily discovered the 

reported information from interviews and depositions with natural gas traders and 

managers and from discovery provided by Enron. Because of ongoing investigations 

by other agencies, the confidential and proprietary nature of information provided in 

discovery, and the forward-looking nature of this investigation, Staff recommends 

that the Commission not provide sources for the information generated through 

interviews and depositions at this time. 

13Id. 

14Id. 

15Id. 
Chapter IX 

Docket No. PA02-2-000 IX-9 Price Manipulation in Western Markets

These elements provide the foundation for the manipulation of the 

natural gas physical markets in order to generate net positive returns 

by relatively larger investments in the financial markets. 

The General Strategy of 

Manipulating the Financial 

Markets Through Trading in 

the Physical Markets 

Overview of Manipulation Strategies 

The relationship between derivatives transactions and the underlying 

physical products provides opportunities to profitably manipulate the 

natural gas markets. During the investigation, Staff recognized trading 

methods used to manipulate the physical markets to profit in the 

financial markets. 

A number of variations are described in the following paragraphs. 

These variations do not exhaust the possibilities but are intended to 

provide a general framework to help the reader understand the actual 

manipulation that took place. 

Strategy To Profit From Upward Movement in Natural Gas Prices 

In the first and most straightforward example, a trader enters a 

relatively large long position in natural gas financial derivative 

contracts that will settle in the near future (within the month). This 

position reflects a “bet” that the expected price of natural gas will rise. 

Once the large position is in place, the trader aggressively purchases 

physical natural gas in the spot market, causing an actual increase in 

the spot price for natural gas and increasing the expected price of gas 

in the near future as well. The change in expected future prices causes 

a rise in the market value for financial derivative contracts settling on 

or near those future dates. To be profitable, it is essential that the 

trader place a larger position in the financial market compared with 

purchases in the physical market. As long as the trader obtained a large 

enough long position (a large enough “bet” on rising prices) prior to 

the physical purchase of gas, profits from the long position should 

exceed losses from buying the physical gas aggressively to push up 

prices. 

Once prices are lifted, the trader must close out or neutralize the long 

position in financial derivative contracts by settling the contracts or by 

entering offsetting short financial transactions. Once the trader realizes 
Chapter IX 

Docket No. PA02-2-000 IX-10 Price Manipulation in Western Markets

profits, the physical long position is reduced to match actual needs. 

The sale of gas necessary to reduce the position creates downward 

price pressure, just as the initial purchase of the gas created upward 

price pressure. This may cause the trader to sell the physical gas at a 

loss. However, the loss is expected to be more than offset by profits in 

financial derivative markets, where the desk manager held relatively 

larger positions. 

Additional Profit Potentially Yielded From Cornering the Market 

As discussed above, when selling the physical spot gas the trader will 

likely push down the price and potentially sell the gas at a loss. 

However, in some cases, the trader attempts to benefit from “cornering 

the market.” The trader just purchased a large amount of the gas 

available in the next-day physical market. That trader may attempt to 

extract monopoly profits by demanding a premium from those who 

need the gas. The trader would attempt to do this by selling gas at a 

premium, late in the trading day, to purchasers who are unaware of the 

manipulation. This would presumably defer the expected drop in 

prices to a point after the purchasers are satisfied. 

Earlier, as prices were rising, those purchasers sold gas into the market 

and expected to buy the gas back cheaper later in the day. However, 

late in the trading day, those who sold gas that they needed or those 

who delayed purchasing due to the high prices might be willing to 

purchase the gas at a premium if they fear that prices will not fall by 

the end of the trading day and if they have no reasonable alternatives 

to secure physical gas supplies (such as withdrawing gas from storage 

or drawing extra gas from the pipeline, which creates an imbalance 

and potentially generates imbalance penalties). These traders might be 

willing to purchase gas at premium prices because of the potential that 

the price of gas will not fall before the trading day ends, to avoid 

penalties, to run generators, or to fulfill unavoidable delivery 

obligations. 

Strategy To Profit From Downward Movement in Natural Gas Prices 

An opposite strategy can be executed with the goal of pushing down 

prices. The trader can enter a short position in natural gas financial 

derivatives that will settle in the near future. Following the placement 

of the short position, the trader sells natural gas in the spot market, 

which pushes down the spot price. The lower spot price is expected to 

reduce the expected gas prices for delivery in the near future. 

Assuming this happens, as the price goes down, the value of the short 

derivative position rises. To realize profits, the trader would close out 

or neutralize the short financial position by settling the financial 

contracts or by entering new, offsetting long financial transactions. 
Chapter IX 

Docket No. PA02-2-000 IX-11 Price Manipulation in Western Markets

After closing the derivative position, the trader purchases back the 

physical gas to cover his short physical position. The purchase of the 

physical gas may generate a loss, however, if the trader executed a 

large enough financial derivative position to generate profits that 

exceed these losses; the strategy then remains profitable on a net basis. 

This strategy underscores the point that profitable market 

manipulations can involve what, in isolation, appear to be a beneficial 

drop in the price of physical gas. 

An Alternative Variation in Which the Trader Gains Profits From the 

Downward Movement in Prices 

The first manipulation strategy described above, in which the trader 

attempts to profit from rising prices, can also generate profits from the 

downward motion of prices following the trader’s aggressive purchase 

of gas. When the trader pushes up the physical gas price by buying 

physical gas, he expects that prices will reverse after the manipulation 

ceases. In addition, if the trader did not obtain a short physical position 

prior to the manipulation, he will need to sell the physical position he 

acquired. This selling pressure will enhance the downward price 

movement following the manipulation. 

In this variation, the trader does not need to enter a derivative position 

at the outset. Instead, the trader first purchases physical spot gas 

aggressively to push up the spot price. Then, while prices are high, the 

trader enters or increases short financial positions. Once the short 

position is in place, the trader sells the long physical position, thereby 

causing prices to decrease again and increasing the value of the short 

financial position. 

The apparent benefit of this strategy is that the trader can increase the 

derivative positions after or while affecting the market prices of the 

physical product. This provides the trader with the opportunity to test 

market strength and gain information regarding the market’s potential 

response. For example, the trader might learn that there is no interest 

in buying at certain levels, outside of the trader’s own purchases, 

verifying the increased potential for downward pressure when the 

trader stops buying and especially when the trader sells. 
Chapter IX 

Docket No. PA02-2-000 IX-12 Price Manipulation in Western Markets

The Central Desk 

Manipulation 

Enron’s central desk was primarily responsible for trading gas and 

making markets for locations in the central United States. However, 

that desk was not responsible for making markets at the Henry Hub; 

Enron gas traders were generally allowed to trade all locations in 

North America. 

According to information gained through interviews, depositions, data 

analysis, and document review, the desk manager apparently 

performed a market test to move Henry Hub natural gas prices and, 

soon after, executed an actual market manipulation. The market test 

occurred on June 14, 2001 and the market manipulation occurred on 

July 19, 2001. On both occasions, the desk manager manipulated the 

price of the Henry Hub next-day physical gas product. The 

manipulations differed in approach and resulted in somewhat different 

outcomes. 

The manipulation relates to the strategy described above. Staff 

believes the manipulation was intended to first increase the market 

price of natural gas at the Henry Hub, then enter short financial 

positions while the market was artificially high, and then push the 

market down. In an interview, an Enron trader admitted to a 

manipulation of the Henry Hub market to profit in the derivatives 

markets in the spring of 2001. Details of that manipulation and its 

design arose from additional interviews and depositions. An analysis 

of the Enron database isolated June 14, 2001 and July 19, 2001 as the 

dates of the potential manipulations. The July 19, 2001 manipulation 

was further supported by additional corroborating evidence, including 

a transfer of funds that, according to the depositional testimony of 

Enron traders, related to the manipulation. The patterns of the 

manipulations revealed in the data are further supported by the unusual 

role changes and actions of particular Enron traders. Staff first 

discusses these role changes and actions and then reports the 

manipulations in detail. 

Unusual Circumstances Surrounding the Trading Activity 

Because of the desk manager’s regional trading desk management 

position and the manner in which he executed the trades, these 

transactions are highly suspect. During the market experiment and the 

manipulation, the desk manager traded a next-day physical product, an 

unusual act for a person in his position. In the normal course of 
Chapter IX 

Docket No. PA02-2-000 IX-13 Price Manipulation in Western Markets

business, the trades would have been executed by someone in a 

subordinate position. Moreover, the next-day physical product of one 

region typically would not be transacted by traders making markets or 

scheduling gas for a different region. 

The desk manager did not trade the physical product to satisfy actual 

physical needs. During the June 14, 2001 market experiment, within 

the trading day, he first sold and then bought 360,000 MMBtu. The 

resulting net purchase of physical gas amounted to zero, reflecting no 

actual need for gas by the end of the day. 

A very liquid financial derivatives market existed for exactly the 

location in which the desk manager chose to trade physically. If he had 

intended to take a position in anticipation of a value change for the 

Henry Hub location, the far more liquid August OTC swap (NYMEX 

look-alike swap) would have been the likely vehicle because of its 

financial settlement, liquidity, and direct dependence on the Henry 

Hub location. Transactions of the size traded by the desk manager 

would not have affected the OTC swap price by as much, or at all, 

because of the greater depth or liquidity of that market. 

 

On July 19, 2001, the date of the actual manipulation, the desk 

manager took a relatively large long position in the Henry Hub 

physical markets and then completely reversed the position a short 

time later, reflecting a need to sell gas by the end of the day. 

According to depositional testimony, on July 19 the desk manager 

took this position while unofficially acting as market maker for the 

Henry Hub. The market maker is the Enron trader assigned to always 

quote both a bid and an offer price, representing Enron’s willingness to 

always buy or sell gas during market hours. The desk manager took 

over the chair of the Henry Hub next-day physical market maker and 

executed his transactions directly with EOL counterparties. Other 

Enron traders testified that the desk manager’s action was unusual; in 

addition, the temporarily displaced market maker was officially 

supervised by a different desk manager. 

 

The actions of the desk manager on July 19 generated losses in the 

book of the market maker whom he unofficially displaced. 

Depositional testimony revealed that a transfer of $86,000 to the 

market maker on the day of the manipulation covered the losses to the 

market maker generated by the desk manager. 

 

Trading large amounts at once or, alternatively, trading many times 

over a short period, can create supply/demand imbalances and can 

cause executions at relatively bad prices. During both of the 

manipulations, the desk manager traded many times and in a short time 
Chapter IX 

Docket No. PA02-2-000 IX-14 Price Manipulation in Western Markets

interval. He could have traded at a slower pace, allowing the market to 

absorb the additional supply or demand. However, on June 14 he 

purchased a large amount of gas in a very short period and on July 19 

purchased and sold relatively larger amounts at an equally fast pace, 

generating losses on both days by this manner of trading. 

The June 14, 2001 Market Test 

During a search for what turned out to be the July 19, 2001 

manipulation described in the next section, Staff discovered an earlier 

apparent market experiment or test that involved smaller physical 

volumes and relatively small financial derivative positions. In 

executing this test of the next-day physical Henry Hub price, the desk 

manager sold 360,000 MMBtu slowly on the EOL trading platform 

during the earlier half of the trading day, obtaining a net short position 

of 360,000 MMBtu. He then purchased the same amount in just 19 

minutes, driving the price up significantly. The NYMEX price rose 

along with the next-day physical gas price. 

For a short period following the desk manager’s purchases, an Enron 

trader assigned to that desk manager entered short positions that would 

profit from a drop in the NYMEX swap price. Staff believes that the 

Enron trader may have placed his short position with the expectation 

that prices would return to premanipulation levels after the desk 

manager ceased generating the appearance of excess demand. Staff 

views the physical and financial trades as suspicious because of the 

involvement of these traders in the July 19, 2001 manipulation and 

concerns regarding the actions of the desk manager described above. 

 

Staff views the June 14, 2001 manipulation as a market test or learning 

experience. Staff found only a small amount of financial derivative 

transactions acquired in a manner consistent with foreknowledge that a 

manipulation would occur. It is Staff’s opinion that the manipulation 

may have been a test of the market or a learning experience for the 

manipulators. Staff believes that the market test was profitable, but 

generated minimal profits. The trader (trader 1), whose position 

changes were consistent with participation in the manipulation and 

who claimed to plan the strategy, earned approximately $55,025 in 

financial trading profits while the losses generated from the physical 

manipulation amounted to $36,500, resulting in net profits of $18,525. 

According to depositional testimony, trader 1 claimed to have devised 

the scheme but denied implementing the strategy. Trader 1 worked 

directly for the desk manager. 
Chapter IX 

Docket No. PA02-2-000 IX-15 Price Manipulation in Western Markets

The details of the June 14 market test are as follows.16 On June 14, 

2001, between 7:39 and 9:04 a.m., the head of the Central desk (the 

desk manager), in 12 separate transactions, sold a total of 360,000 

MMBtu of Henry Hub next-day physical gas to the EOL market maker 

for that product. During this period the price of the next-day natural 

gas fell slightly, from $3.93/MMBtu to $3.91/MMBtu. The desk 

manager accumulated a net short position of 360,000 MMBtu of 

Henry Hub next-day physical gas during this time. 

Between 9:42 and 10:01 a.m., the desk manager completely reversed 

the position by purchasing a total of 360,000 MMBtu in eight 

transactions. As the desk manager aggressively bought back the gas he 

had sold, the market price rose significantly. His first purchase of 

50,000 MMBtu at 9:42 cost $3.97/MMBtu and his last purchase in the 

19-minute timeframe cost $4.06/MMBtu. The desk manager lost a 

total of $36,500 executing these trades.17

Figure IX-118

The Relevant Hours: Comparison of Spot and Short Term Henry Hub Based Physical and 

Financial Product Prices on June 14, 2001*

3.85

3.9

3.95

4

4.05

4.1

4.15

7:12 8:09 9:07 10:04 11:02 12:00 12:57

Time

Price ($ per MMBtu)

June Gas Daily Financial July OTC Swap (NYMEX look-alike) Henry Hub Next Day Physical

Desk Manager Sells Physical Desk Manager Buys Physical

*Larger sized points reflect that Desk Manager's average purchase size equalled 45,000 MMBtu and Desk Manager's 

average sale size equalled 30,000 MMBtu, while non-Desk Manager trades averaged 13,806 MMBtu.

 

16For a detailed description of trader 1’s financial trading positions and profits for the 

June 14, 2001 market testing manipulation, see Appendix IX-A. 

17Average sale price less average purchase price multiplied by the total volume 

purchased (which equaled the total volume sold exactly) equals $36,500. 

18With regard to all figures in this chapter, color prints are necessary to fully 

understand the details of the manipulations. 

The Relevant Hours: Comparison of Spot and Short-Term Henry Hub Based 

Physical and Financial Product Prices on June 14, 2001* 
Chapter IX 

Docket No. PA02-2-000 IX-16 Price Manipulation in Western Markets

 

Although it took 1 hour and 25 minutes to obtain the short position, it 

took only 19 minutes to reverse the short position. After 10:01, the 

price of the next-day gas increased further, to a high of $4.10/MMBtu, 

before the last trade at 10:45 at the price of $4.06/MMBtu. 

Trader 1 was positioned to profit from this market test. Trader 1 

entered into a short financial derivative position that would profit from 

a downward movement in prices. He then substantially increased a 

short position in OTC swaps during the brief time period when the 

Henry Hub physical markets pulled up the related OTC swap 

transaction prices. Trader 1 then closed most of the position at a point 

where the market price for the OTC swap briefly jumped up, reducing 

the profitability of trader 1’s positions. Trader 1 continued to hold the 

remainder of his position through the close of trading on EOL, when 

the OTC swap traded down to near the opening price for the day, thus 

increasing trader 1’s profits. 

Figure IX-2 

Comparison of Spot and Short Term Henry Hub Based Physical and Financial Product Prices 

on June 14, 2001*

3.85

3.9

3.95

4

4.05

4.1

4.15

3:30 4:27 5:25 6:22 7:20 8:18 9:15 10:13 11:10 12:08 13:06 14:03 15:01 15:58 16:56 17:54 18:51 19:49 20:46

Time

Price ($ per MMBtu)

June Gas Daily Financial July OTC Swap (NYMEX look-alike) Henry Hub Next Day Physical

Desk Manager Sells Physical Desk Manager Buys Physical

*Larger sized points reflect that Desk Manager's average purchase size equalled 45,000 MMBtu and Desk Manager's 

average sale size equalled 30,000 MMBtu, while non-Desk Manager trades averaged 13,806 MMBtu.

The market test generated an insignificant amount of profit. However, 

in terms of moving the market price, the scheme proved successful. 

More importantly, this scheme preceded a greatly expanded scheme 

that occurred about 1 month later and generated significant profits. 

 

Comparison of Spot and Short-Term Henry Hub Based Physical and Financial 

Product Prices on June 14, 2001* 
Chapter IX 

Docket No. PA02-2-000 IX-17 Price Manipulation in Western Markets

The July 19, 2001 Manipulation 

Overview 

The July 19, 2001 market manipulation is most similar to the strategy 

described in this chapter in the section titled “An Alternative Variation 

in Which the Trader Gains Profits From the Downward Movement in 

Prices.” The July 19 manipulation involved the desk manager, a 

number of traders, and the EOL Henry Hub next-day gas market 

maker. 

A number of traders entered relatively large short positions in the 

financial markets through OTC swaps and Gas Daily financial swaps. 

These traders continued to increase the short positions throughout the

initial phase of the manipulation, which was the period when the EOL 

market maker (who was, at times, the desk manager) quickly and 

steadily raised prices on EOL, resulting in the purchase of a very large 

amount of next-day physical gas. This purchasing caused prices in the 

financial markets to rise, but by a lesser amount. 

The financial traders stopped increasing their short positions near the 

end of the EOL market maker’s buying streak at a point when the EOL 

market maker stopped raising prices and began to hold prices steady at 

the high levels. Once the EOL market maker leveled out prices, the 

OTC swap began to fall. The EOL market maker then began to lower 

the prices and sold a very large amount of gas at rapidly falling prices. 

The falling of the physical price then further pushed down the OTC 

swap price, generating significant profits for the financial traders. 

These profits greatly exceeded the losses that were generated from the 

impatient buying and selling of the physical gas. 

The physical volumes associated with the above physical manipulation 

were as follows. Prior to the manipulation, the market maker first 

accumulated a net short position of 124,613 MMBtu. Then the desk 

manager, acting as the market maker, drove up the price of gas by 

buying physical gas at higher and higher purchase prices, generating a 

net long position of 587,237 MMBtu. This reflects that Enron’s net 

position changed by 711,850 MMBtu. The selling streak that followed 

resulted in a net short position of 315,191 MMBtu, or a net change of 

902,428 MMBtu. The larger amount of sales on a net basis indicates 

that Enron intended to ultimately push the price down. 

According to the financial data, at least eight traders from the Central 

and East desks (eight traders) positioned themselves to profit from the 

manipulation in a very timely manner. In the prior June 14, 2001 
Chapter IX 

Docket No. PA02-2-000 IX-18 Price Manipulation in Western Markets

market testing manipulation, the desk manager traded gas with the 

EOL market maker. In the July 19, 2001 manipulation, the desk 

manager took direct control of the EOL Henry Hub next-day physical 

market by taking over the market maker function and posting bids and 

offers directly, on behalf of EOL, and in the name of the displaced 

market maker.19 This direct control of the price setting function 

provided the desk manager with an ability to manipulate the market 

more precisely. 

Just after 9:20 a.m., the desk manager began to raise the price of Henry 

Hub next-day physical gas. During this time, the eight traders 

significantly increased or obtained net short financial derivative 

positions. When the desk manager stopped raising the purchase price 

for a short period and then began lowering the price, the OTC swaps 

began to drop (reflecting downward movement in the NYMEX). The 

desk manager then began to aggressively sell off the gas he had just 

acquired, strengthening the downward movement. By the end of the 

day, Enron had obtained a significantly large net short position as EOL 

continued to sell more physical gas on a net basis after already having 

sold off the net long position. The OTC swaps and the Gas Daily

balance-of-the-month contracts fell significantly past the opening 

price, generating profits for those traders who entered or maintained 

short positions. 

Details of the July 19, 2001 Market Manipulation 

The day began with the physical book slowly growing short. In other 

words, by 9:22 a.m., Enron sold 124,613 MMBtu more of the next-day 

gas than it had bought. During this period, which lasted almost 2 

hours, the price of gas rose a net $0.01/MMBtu from an opening first 

trade of $3.02 to $3.03/MMBtu at 9:22 a.m. 

 

19According to depositional testimony and verified by electronic financial records, 

the desk manager agreed to cover the losses that he would generate in the name of 

the market maker. See footnote 11. 
Chapter IX 

Docket No. PA02-2-000 IX-19 Price Manipulation in Western Markets

Figure IX-3 

July 19, 2001 Morning Hours: EOL Henry Hub Next Day Physical Market Maker Activity and 

EOL Based Transaction Prices for Related Financial Products

2.9

2.95

3

3.05

3.1

3.15

7:55:12 8:24:00 8:52:48 9:21:36 9:50:24 10:19:12 10:48:00

Time

Price ($ per MMBtu)

August OTC Swap (NYMEX look-alike) July Gas Daily EOL Market Maker Buys Physical EOL Market Maker Sells Physical

At 9:22, the selling ended and the market maker began a buying streak. 

The market maker raised the price at which it was willing to buy the 

next-day gas. Many sellers came in to take advantage of the increasing 

prices. The EOL market maker offered such a generous price that, in 

just 19 minutes, the next-day gas platform purchased gas 43 times 

while selling gas only a single time. The price peak was reached at 

9:35, just 13 minutes after the buying streak began. From 9:35 through 

9:40, the next-day gas bounced along a ceiling of $3.10/MMBtu, 

creating an apparent top. The NYMEX crept upward from $3.00 to 

$3.02 from 9:22 through 9:36, but then began to decline a few minutes 

after the ceiling at $3.10/MMBtu had formed. 

A very interesting phenomenon occurred at this point. The EOL 

market maker began reducing the price at which it purchased gas, but 

continued to only buy gas. By reviewing the trading behavior in Figure 

IX-3 in detail, Staff identified this strange pattern in which the EOL 

market maker drove the price up by offering a strong bid price and 

then creating a top, and then began a downward slide, all while selling 

gas only once.20

 

20See the section below for a more detailed description of the physical manipulation. 

July 19, 2001 Morning Hours: EOL Henry Hub Next-Day Physical Market Maker 

Activity and EOL-Based Transaction Prices for Related Financial Products 
Chapter IX 

Docket No. PA02-2-000 IX-20 Price Manipulation in Western Markets

Following this unusual buying behavior, at 9:41 the market maker 

ended the buying streak and began strongly selling gas. Just prior to 

the selling streak, the market maker held a net long position in the 

next-day gas of 587,237 MMBtu. 

During the market maker’s buying streak, prices in the financial 

markets followed the physical markets upward but to a lesser extent. 

This emphasizes the unusual and puzzling nature of the market 

maker’s behavior; he continued to buy the physical product even as it 

became extremely expensive and disconnected from the financial 

product. However, the EOL market maker now had a huge store of 

physical gas that it could sell to move the physical price down. During 

his deposition, trader 1 denied manipulating the market but claimed to 

have devised the manipulation strategy consistent with the facts of the 

July 19, 2001 manipulation. With regard to that strategy, trader 1 

stated: 

“[W]e were trying to find out if this strategy would work and if 

Enron would make money if this strategy worked. So if prices 

went up and [the market maker] would make money by people 

buying the gas back at a higher price, if they didn’t go up then 

she had to sell it. There is a chance you could sell OTC 

[NYMEX] swaps and benefit from the downward movement in 

the Henry Hub physical and that would offset the losses of 

selling the actual physical at a lower price.”21 

In the next 8 minutes, by 9:49, the market maker sold gas 31 times in a 

row without buying gas once. The price of the next-day gas at this 

point fell to $2.935/MMBtu. By 9:54, through these sales, the market 

maker had reversed the intraday long position to a short position. The 

price for the next-day gas at this time equaled $2.915/MMBtu. More 

important for the success of the manipulation, the NYMEX would 

need to follow and it did so. The OTC swap traded at $2.925/MMBtu 

at 9:54, which was down from the peak of $3.015 during the earlier 

part of the manipulation. Until 10:42, the last trade of the day, the 

market maker continued to be a net seller of gas. By the last trade of 

the day, the next-day gas traded for $2.905/MMBtu and the EOL nextday gas market maker closed for the day with a net short position of 

negative 315,191 MMBtu. At 10:42, the OTC swap traded at 

$2.945/MMBtu. The OTC swap continued to trade in a range from 

$2.915 to $2.96/MMBtu. At 2:30, the end of the NYMEX futures 

exchange trading day, the OTC swap traded at $2.935/MMBtu. 

 

21See footnote 11. 
Chapter IX 

Docket No. PA02-2-000 IX-21 Price Manipulation in Western Markets

Traders’ Positions and Profits 

Figure IX-4 shows the positions of a number of traders who knew or 

may have known about the manipulation of the Henry Hub next-day 

physical gas product. The manager of the Central desk and trader 1 are 

represented by the colors pink and yellow, respectively. Each of the 

traders represented in the figure worked on either the Central desk or 

the East desk (the desk of the official market maker for the Henry Hub 

next-day physical product). Each of the traders was positioned to profit 

if the NYMEX fell. These traders increased their short positions 

during the manipulation. 

Figure IX-4 

Net August OTC Swap Positions and July Gas Daily Financial Position Changes for Trades 

on July 19, 2001

-10000000

-8000000

-6000000

-4000000

-2000000

0

2000000

3:32:08

3:40:115:00:09

6:01:41

8:29:25

8:44:00

8:50:44

8:52:35

9:08:06

9:12:019:16:36

9:23:01

9:32:14

9:35:25

9:38:31

9:40:52

9:41:41

9:47:469:51:42

10:01:1710:16:34

10:23:0210:28:2010:34:2510:40:2910:49:0411:21:0512:39:5614:09:34

14:39:55

20:24:39

20:25:24

8:33:50

9:34:30

Trader 2 Trader 1 Desk Manager Trader 3 Trader 4 Trader 5 Trader 6 Trader 7

As shown in the figure, the traders began the day with a net short 

position and the position grew shorter between approximately 8:40 and 

10:00 a.m. We combined the trades of the eight traders in Figure IX-5 

so that the financial position changes could be seen clearly in an 

aggregated manner. 

Net August OTC Swap Positions and July Gas Daily Financial Position Changes 

for Trades on July 19, 2001 
Chapter IX 

Docket No. PA02-2-000 IX-22 Price Manipulation in Western Markets

Figure IX-5 

OTC Swap Trading 

-40,000,000

-35,000,000

-30,000,000

-25,000,000

-20,000,000

-15,000,000

-10,000,000

-5,000,000

0

3:32:08

5:47:45

6:41:22

7:25:11

8:01:04

8:20:20

8:39:36

8:51:33

8:54:24

8:57:59

9:07:14

9:23:01

9:35:13

9:39:33

9:44:33

9:50:53

9:55:35

10:03:48

10:20:09

10:33:20

10:59:57

11:51:16

13:02:53

13:44:49

14:07:55

14:42:35

17:03:58

Time

MMBtu

2.85

2.9

2.95

3

3.05

3.1

3.15

$/MMBtu

Aggregated Positions for Financial Traders OTC Swap Price

Staff calculated that these eight traders generated a total profit of 

$3,181,756 during the day from their net short positions in the August 

NYMEX contract and the balance-of-the-month July Gas Daily

financial swap.22 

Regarding the losses that accrued on the physical side, the EOL market 

maker for the physical Henry Hub next-day gas product lost 

approximately $86,000 during the manipulation, but was made whole 

by a payment from the desk manager.23 

 

22Deciding where profits continue to arise from a manipulation and where they cease 

to arise is a difficult and somewhat arbitrary task. The profit calculation values 

existing positions at the first transaction price posted for the day. The calculation 

values all positions that remain open at the end of the day at the price of the last 

transaction of that day. Other than considering existing positions at the start of the 

day, profits were calculated in the manner described in Appendix X-A for the June 

14, 2001 manipulation. 

23See footnote 19. 
Chapter IX 

Docket No. PA02-2-000 IX-23 Price Manipulation in Western Markets

Understanding the Market Maker’s Physical Transactions 

The description of the July 19, 2001 trading day revealed a strange 

pattern in which the market maker began to strictly purchase gas and 

dictate the upward movement of the price, the price ceiling, and the 

initial downward movement. Then through sales, the market maker 

dictated the larger downward movement of the price. Finally, at the 

end of the trading day, the market maker maintained a low price 

through pricing with a bias toward sales by the market maker. 

The market maker’s function is to make a market in a product by 

putting out both an offer to buy gas (bid price) and an offer to sell gas 

(ask or offer price). The market maker generates profit from a spread 

between the bid price and the ask price. The ask price should always 

exceed the bid price because for the market maker to be profitable, he 

needs to sell gas at prices that exceed the price at which he is willing 

to buy gas.24 The market maker generally seeks to post a spread that 

values the product fairly. As supply and demand change, the market 

maker modifies the spread. For example, if more buyers come to the 

market than sellers, the market maker raises the price of the product to 

reduce the demand to buy the product by making it more expensive. If 

the market maker fails to adjust the spread to raise the price, the 

market maker will sell too much gas and fall short. To buy back the 

gas, the market maker will have to raise the price at which he is 

willing to buy gas, unless market conditions change. This would 

generate a loss. In illiquid markets, market makers will tend to set 

wider spreads to generate larger returns in return for taking on greater 

risk that the market maker will not be able to find buyers and sellers at 

all times and therefore may need to hold product for longer periods 

than he would like. With this understanding of market making, 

consider the market maker’s trading on July 19, 2001, as seen in 

Figure IX-3. 

In Figure IX-3, the market maker’s actions are intentional. This is not 

a case in which the market maker passively failed to adjust prices 

given changing market conditions. In this case, the market maker 

raised the price significantly, attracting more and more sellers to the 

market. The market maker is informed that he or she is the cause of the 

market price change, but the others are uninformed. They might 

assume that a large buyer (or buyers) is pushing up the price of gas. 

 

24If the bid price exceeded the ask price, it would be profitable for traders to buy 

from the market maker and immediately sell back to the market maker. Therefore, 

whenever transactions do not occur, the ask price must strictly exceed the bid price. 
Chapter IX 

Docket No. PA02-2-000 IX-24 Price Manipulation in Western Markets

The market maker is offering a price that is so far beyond the market’s 

supply and demand conditions that traders only sell to the market 

maker for an extended period of time. Yet, interestingly, the price 

continues to rise. Next, the price begins to form a top where sales to 

the market maker continue for about 5 minutes, at or near 

$3.10/MMBtu. The market maker could have chosen to raise the price 

higher if he or she were willing to pay the price to the incoming 

sellers. 

The market maker, after forming the top, chose to bring the price 

down. The data reflect that the market maker did not want prices to fall 

too quickly, so while prices were still above the fair market price, the 

market maker offered a bid that continued to solely attract sellers. 

Finally, as the price fell in a series of seven transactions from 

$3.10/MMBtu to $3.055/MMBtu, the market maker began to offer an 

ask price that solely attracted buyers. At this point the market maker 

sold the large amount of gas it had just purchased at steeply falling 

prices. The willing buyers began to come in at $3.015/MMBtu. The 

market maker sold off far more gas than he or she had acquired. The 

peak intraday volume of gas purchased by the market maker amounted 

to 587,237 MMBtu. By 9:54, the price had fallen to $2.915 and the 

market maker’s intraday MMBtu position fell to just below zero. By 

the last trade, the market maker was short 315,191 MMBtu and the last 

physical trade was at $2.905/MMBtu, with a low of $2.89/MMBtu. 

Description of EnronOnline 

and Its Main Features 

In this section, Staff discusses the design of EOL and how it facilitated 

manipulation of the market, the economics of trading, alternative 

trading systems, and some forward-looking recommendations 

concerning energy trading mechanisms.25

 

25This section was prepared by FERC Staff with the assistance of outside consultant 

Chester Spatt, Mellon Bank Professor of Finance, Graduate School of Industrial 

Administration, Carnegie Mellon University. Comments and contributions were also 

provided by Professor Hendrik Bessembinder, Blaine Huntsman Presidential Chair 

in Finance, David Eccles School of Business, University of Utah. 
Chapter IX 

Docket No. PA02-2-000 IX-25 Price Manipulation in Western Markets

The EOL Trading Platform 

The EOL system was the first broadly successful Internet-based 

system for trading energy products. Enron established this trading 

platform so that it could serve as market maker in a broad range of 

physical and financial energy instruments. During the trading hours 

established for specific products, EOL offered (two-way) bid and ask 

quotes over the Internet. The quotes could be executed over the 

Internet directly by those entities with an EOL trading account. 

Outside traders continuously observed the posted two-sided quotes at 

specified volumes. These traders could instantaneously execute 

transactions at those quoted prices. As this suggests, the EOL platform 

was a one-to-many platform in which many counterparties (customers) 

were able to access the liquidity or apparent liquidity that Enron 

supplied. 

The EOL system allowed the Enron market maker in a particular 

product to set up a schedule of prices (known as the “stack”) from 

which customers could execute buy or sell orders. The customers can 

only see the top of the stack, which shows the current quoted bid and 

ask prices. Using a tool called the “stack manager,” EOL is set up for 

Enron to be able to easily modify the stack that it offers on both sides 

of the market. For example, EOL may have offered gas at a particular 

location for $4.00 ask and $3.95 bid. In this case, an EOL customer 

could buy gas at $4.00 from EOL and sell gas to EOL at $3.95. As 

customers executed transactions on EOL for a particular product, the 

quoted ask and bid prices would be replaced with the next set of prices 

and quantities found in the stack. Different portions of the stack would 

be used, depending on whether an EOL customer bought from EOL 

(“lifted the offer”) or sold to EOL (“hit the bid”). The Enron market 

maker specified the total volume of a particular product that he would 

be willing to buy or sell at the scheduled prices. The market maker 

could continuously alter the stack in response to both market 

information and the arrival of orders. 

Alternatively, the market maker could set a function that increased 

prices by fixed increments as customers purchased gas and decreased 

prices by fixed increments as customers sold gas. For example, if EOL 

quoted an ask price of $4.00 for gas at a particular location and a bid 

price of $3.95, the EOL market maker could set a fixed increment at 

plus or minus $0.05. If this were the case, then if two customers 

bought gas consecutively, the ask price would rise to $4.05 after the 

first buyer lifted the offer of $4.00 (and the bid price would rise to 

$4.00). When the second buyer purchased gas, the ask price would rise 
Chapter IX 

Docket No. PA02-2-000 IX-26 Price Manipulation in Western Markets

to $4.10 (and the bid price would rise to $4.05) following the 

purchase. If a customer then sold gas while the ask price was $4.10 

and the bid was $4.05, that customer would receive $4.05 for the gas 

he sold and the ask price and bid price would fall to $4.05 and $4.00, 

respectively, following the sale. If the EOL market maker had created 

a schedule of price changes depending on whether customers bought 

from or sold to EOL, it is likely that prices would rise as customers 

bought and prices would fall as customers sold. However, as seen in 

the July 19 manipulation, the EOL market maker could choose what

prices to post and mislead customers regarding the state of supply and 

demand. 

The versatility of the EOL system also gave the EOL market maker the 

ability to automatically accommodate larger orders at less favorable 

prices. Large orders can potentially “walk up” or “walk down” the 

EOL stack established by the market maker. For example, a trader may 

pay a progressively higher price to purchase a large amount of a 

product through a series of transactions.26 Additionally, the EOL 

market maker could instantaneously cancel liquidity offered by the 

EOL platform by modifying the quoted prices to unattractive levels 

(setting a very high asking price and a very low bid price). 

The Lack of Transparency on the EOL Platform 

Unlike the NASDAQ, from which timely electronic trade reports had 

been available to the public even prior to its transparency enhancing 

reforms in 1997, EOL did not offer timely reporting of executions. 

This means that EOL provided no data regarding recently executed 

transactions. Consequently, the market would not be viewed as “ex 

post transparent,” i.e., even after the trades, basic market information 

was not provided to market participants. This made it difficult for 

traders to judge the current state of the market and forced traders to 

position their orders in a somewhat “blind” context. 

 

As described above, EOL did not show the stack of prices and 

volumes. EOL only showed the best bid and the best offer for a 

specified relatively small volume of a product. This aspect of the EOL 

market design is similar to the former NASDAQ system, as that 

system lacks “ex ante” transparency. EOL did not display the potential 

liquidity available for orders of various sizes. 

The absence of both ex ante and ex post transparency made it difficult 

for outside traders to understand both their potential trading 

opportunities and how well they did on past trades. Under the EOL 

 

26The trading patterns of Reliant at the Topock Southern California Border point, 

described in Chapter II, reflect the “walking up” of the price of natural gas. 
Chapter IX 

Docket No. PA02-2-000 IX-27 Price Manipulation in Western Markets

system, Enron had complete information on past executions on both 

sides of the market as well as the current liquidity being offered to 

Enron that it has elected to not execute immediately when it does not 

at least match the current EOL quote. Indeed, all of this detail is 

known by Enron at a completely disaggregated level by counterparty. 

This may have made traders reluctant to provide orders for execution. 

The lack of information makes formulating one’s trading strategy 

particularly difficult. However, despite these imperfections, EOL 

improved market transparency (relative to voice brokers) by making 

continuous two-sided quotes available to all for the first time. 

In the EOL system the EOL market maker was asymmetrically 

(extremely well) informed. In this system Enron had complete 

information on past executions on both sides of the market (including 

the participants associated with each transaction) and control over 

future quotes. This made many traders reluctant to trade on the 

platform. EOL was similar to the problematic pre-1997 NASDAQ 

system in which all customer trades in the NASDAQ equity market 

were executed with dealers and the quotes displayed were the best 

market-maker quotes.27 Public limit orders, i.e., price-contingent 

orders from the public,28 that would improve the quote were not 

displayed in the basic EOL design and such potential liquidity could 

not be accessed, except by trading with Enron. 

Limit Orders on EOL 

During the later portion of its operation, EOL accepted limit orders 

placed by its customers for inclusion in the EOL stack. These limit 

orders reflected customer willingness to provide liquidity, through 

offers by customers to buy or sell a product from or to Enron, at 

specific maximum or minimum prices and volumes not currently 

available on the EOL platform. These limit orders provided Enron 

with information on liquidity at the specified price levels by specified 

counterparties. When such limit orders were executed, Enron acted as 

the counterparty rather than matching the trade directly with another 

EOL customer. Effectively, all trades were still cleared using Enron as 

 

27The inadequacy of that system and the collusion among dealers that was 

documented economically in “Why Do NASDAQ Market Makers Avoid Odd-Eighth 

Quotes?” W. Christie and P. Schultz, Journal of Finance, Volume 49, Issue 5 (Dec. 

1994), pp. 1813-1840 and “Why Did NASDAQ Market Makers Stop Avoiding OddEighth Quotes?” W. Christie, J. Harris, and P. Schultz, Journal of Finance, Volume 

49, Issue 5 (Dec. 1994), pp. 1841-1860 led to the 1997 adoption of “order-handling 

rules” that facilitated the display and execution of public limit orders within a 

modification of the prior design as well as a $1 billion class-action lawsuit 

settlement. Unlike the NASDAQ system, EOL had a single market maker (Enron) as 

the counterparty on all trades, which is why we call it a one-to-many platform. 

28A limit order to buy would specify a maximum purchase price, while a limit order 

to sell would specify a minimum selling price. 
Chapter IX 

Docket No. PA02-2-000 IX-28 Price Manipulation in Western Markets

the counterparty so that the platform still essentially functioned as a 

one-to-many platform.29

EOL began to accept limit orders from its customers to enhance the 

attractiveness of its trading platform and increase the flow of 

information available to it by providing a vehicle for potential orders 

by outside traders who did not want to execute at the current prevailing 

price. Enron did not bypass the limit orders provided to it (e.g., it did 

not sell from its own account at a higher price when a limit order to 

sell from an outside trader existed in the EOL stack at a lower price) 

and would execute these orders prior to executing orders from its own 

book at inferior prices, i.e., the platform executed positions at more 

favorable prices first and followed “price priority.” 

The limit orders offered by outside traders provided to Enron an option 

to meet demands for immediate execution by others using these limit 

orders as a source of liquidity. The EOL market maker could also step 

ahead of the limit orders and trade from his own account, with the 

comfort that the additional demand to trade reflected in the limit orders 

would potentially move the price in a favorable direction. This would 

allow the EOL market maker to profit by positioning in the market 

prior to the impact on prices that the limit orders would generate when 

executed. These EOL customers, who provided limit orders to EOL, 

were not able to trade directly with one another using the platform. 

When matching buy and sell limit orders were provided to EOL, EOL 

would act as the counterparty to both. 

 

The nature of the platform’s structure, particularly the absence of 

transparency (both with respect to trade reporting and the lack of 

knowledge by outside investors of the limit order book), the effective 

inability of public orders to trade directly with one another, and 

Enron’s inherent last-mover advantage (except for orders at the 

automatically executed quote), all contributed to Enron’s overall 

advantage vis-à-vis the limit orders supplied to it. 

 

29The caveat with this interpretation is that investors placing orders on EOL derived 

a benefit from public limit orders during the period they were allowed, as if the 

public investors are trading directly with one another. 
Chapter IX 

Docket No. PA02-2-000 IX-29 Price Manipulation in Western Markets

The Role of EOL in Enron’s 

Strategy and Market Power 

At a fundamental level, EOL was an important part of Enron’s 

business strategy. Prior to EOL, voice broker trading dominated the 

market. The use of the EOL platform provided a way to benefit from 

its willingness to make a market and supply liquidity. EOL offered a 

way for Enron to “market” its products, including positions that it had 

acquired through these trading activities. In addition, by operating a 

trading platform, Enron obtained considerable market information on 

resource flows and trader valuations from other market participants. 

Given Enron’s substantial overall market position, its decision to 

concentrate its own trading (about 25 percent of the market) through 

EOL (thereby dramatically reducing its involvement in the voice 

broker markets) changed the industrial organization of those trading 

markets. Its decision to substantially reduce its participation in the 

voice broker markets reduced the information and liquidity available 

there. 

A variety of advantages accrued to Enron from its operation of the 

EOL platform, many of which exploited its position as the dominant 

electronic platform. The platform met the need in the marketplace for 

an electronic platform that provided quick and easy trade executions. 

Through the broad acceptance of the EOL platform, EOL gained a 

successful first-mover advantage in which EOL was well positioned to 

exercise market power in the quoting process and earn rents in the 

form of wide spreads, or by exploiting its informational advantage. 

This market power could also create benefits for Enron in its ability to 

extract information from trading firms, both about the level of demand 

for different instruments and the location and distribution of various 

energy products (which may be useful in working to meet future 

unanticipated needs).30 Enron was also in a better position to capture 

profits in the financial derivatives markets using this information. 

More generally, Enron’s information advantage would be valuable in 

helping it assess the information content of trades and orders. 

Another example of the value of Enron’s information advantage is the 

potential assistance it provided in deciding when conditions were ripe 

for a market corner or manipulation or helping it implement the 

manipulation or corner quickly. A final example of the value of 

 

30Analogously, one of the advantages often attributed to Michael Milken’s high-yield 

(“junk”) bond group at Drexel Burnham in the 1980s was its knowledge of the 

ownership of most high-yield bonds. 
Chapter IX 

Docket No. PA02-2-000 IX-30 Price Manipulation in Western Markets

information to Enron is in helping it identify “stale” orders with which 

it could execute opportunistically. The monopoly position even 

increased EOL’s ability to undertake market experiments to further 

enhance its ability to extract information from its quoting behavior.31

Indeed, these sorts of informational advantages are particularly strong 

when a platform possesses a large market share. 

 

Even after the introduction of competing platforms (such as 

DynegyDirect and the IntercontinentalExchange (ICE)), much of 

EOL’s earlier monopoly advantage continued because outside traders 

had become familiar and comfortable with the EOL platform. The 

effective cost to traders of learning a new platform gave EOL a 

considerable first-mover advantage that continued after competing 

platforms arose. These switching costs and the importance of a 

successful platform possessing considerable liquidity act as barriers to 

the entry of competing platforms. Consequently, the initial advantages 

of being the first successful platform to introduce electronic trading 

continued for EOL even after it faced competing platforms (even if 

they had potentially superior market designs). 

The Role of EOL in 

Facilitating Market 

Manipulation 

In earlier chapters of this Report, we described a market test and a 

market manipulation at the Central desk and also discussed the impact 

of Reliant’s purchases of next-day natural gas at Topock during the 

winter of 2000–2001 on the markets. These examples illustrate how 

the design of the EOL electronic platform facilitated and contributed to 

these behaviors. As market maker, Enron observed the depth available 

in the order book across the relevant markets, unlike other traders, 

because of the absence of ex ante transparency. This allowed Enron to 

determine when conditions were ripe for a prospective manipulation, 

without this knowledge being available to other market participants. 

Furthermore, the lack of transparency reduced the likelihood that other 

participants would understand contemporaneously that the market was 

being manipulated. The lack of transparency limited the competition 

that Enron faced and enhanced its ability to exploit transitory changes 

in the depth across markets. The trading system provided Enron a 

continuous option to access liquidity through the orders provided by its 

clients. This gave Enron the option to move prices quickly if it chose 

 

31An illustration of how experimentation in the quoting process in some markets can 

be used to create valuable information flow is shown in “Price Experimentation and 

Security Market Microstructure,” C. Leach and A. Madhavan, Review of Financial 

Studies, Volume 6, Issue 2 (1993), pp. 375-404. 
Chapter IX 

Docket No. PA02-2-000 IX-31 Price Manipulation in Western Markets

to do so, as it did in some of the instances of manipulation described in 

this Report. This seemed crucial to the implementation of this 

manipulation. 

Enron gained considerable informational advantages from EOL. It 

alone observed the identities of the counterparties to all trades and, 

therefore, could observe the volumes and net purchases of every 

product by counterparty. For example, during the winter of 2000–

2001, Enron observed the huge trading volume and net purchases of 

next-day natural gas at Topock by Reliant. This provided Enron a 

strong advantage in understanding the market dynamics. Enron would 

uniquely understand the extent to which the Reliant orders would be 

more informative and therefore would offer these orders relatively less 

depth, which means Enron would raise the price by a greater amount 

after Reliant purchased gas. Enron would do this in anticipation of 

additional purchases by Reliant, arising out of Enron’s knowledge of 

Reliant’s historical gas usage at the Topock point. This informational 

advantage was a consequence of the one-to-many structure, but would 

not be available to other potential liquidity suppliers to Reliant. 

Outside traders of a particular product potentially possess more 

information than market makers. For example, a trader who needs to 

buy large amounts of gas is fully informed about his own remaining 

needs and possibly has other information that motivates his purchase 

of a large amount of the product. The market maker generally does not 

have this information. This suggests that rational market makers set 

their bid and ask quotations to reflect the information known about the 

corresponding bid and ask orders. When a rational market maker 

offers a two-sided quote, this dealer takes into account the information 

known about his customer’s order in setting the quote and quoting 

higher prices to buyers than sellers. The market maker generally 

quotes less favorable prices for larger (more informed) orders. 

Market makers are often viewed as having a distinct advantage with 

respect to their knowledge of the short-term price dynamics because of 

their direct observation of supply and demand (trading conditions).32

This is especially true when liquidity supply is concentrated so that the 

information is not too dispersed. In the EOL system, where ex post or 

 

32An interesting empirical study of this advantage is the study of the Chicago futures 

pits by “Life in the Pits: Competitive Market Making and Inventory Control,” S. 

Manaster and S. Mann, Review of Financial Studies, Volume 9, Issue 3 (1996), pp. 

953-975. In that study the advantage to the market maker from observing the flow of 

information arises in a situation with competing market makers. Of course, the 

advantages from observing the short-term liquidity dynamics will be much greater 

when that information is concentrated in a single dominant market maker, even if 

that market maker does not attempt to exploit its potential monopoly power, as with 

the EOL platform. 
Chapter IX 

Docket No. PA02-2-000 IX-32 Price Manipulation in Western Markets

ex ante trade information is not provided to customers, the advantages 

to EOL market makers increase because none of the advantageous 

information is shared with others. Of course, it is precisely when 

liquidity provision is concentrated that there is also the greatest scope 

for monopoly power. This can manifest itself as the market maker 

setting relatively wide spreads between bid and ask prices and the 

extent to which the market maker extracts information from the flow 

of orders. 

ICE and TradeSpark: An 

Alternative Type of 

Electronic Platform33

The Basic Structure of the Electronic Markets 

The introduction of the EOL platform in late 1999 generated 

tremendous interest and attention, bringing electronic trading to the 

commodity markets.34 It emerged as a very popular platform and 

appears to have facilitated Enron’s ability to increase its market share. 

The EOL system itself was quite easy to use and provided quick 

executions (immediate trading). EOL brought a “screen” to the OTC 

energy market at a time when trading occurred through telephone 

“voice brokers.” The voice brokers performed a matching function and 

would often need to search for liquidity by “working the market.” In 

contrast, Enron’s willingness to offer continuous liquidity to the 

marketplace (e.g., by maintaining two-sided quotes) was very 

attractive to market participants. From the perspective of many 

participants, the system provided a form of “price discovery” through 

the continuous availability of two-sided quotes, even though the quotes 

certainly reflected Enron’s business interests. The ease of using EOL 

presumably helped contribute to the growth of the market by 

simplifying the ability to trade. Indeed, when EOL “went dark,” the 

trading activity at ICE doubled as traders sought alternative electronic 

platforms.35 36

 

33Information about IntercontinentalExchange (ICE) and TradeSpark was primarily 

provided by interviews with their respective personnel. 

34Many equity markets around the globe (such as Toronto and Paris) moved to 

electronic platforms during the late 1980s and the 1990s (e.g., as illustrated by the 

analysis of the provision of liquidity in the electronic limit order market in Paris by 

“An Empirical Analysis of the Limit Order Book and the Order Flow in the Paris 

Bourse,” B. Biais, P. Hillion, and C. Spatt, Journal of Finance, Volume 50, Issue 5 

(Dec. 1995), pp. 1655-1689). In fact, the Toronto market licensed its electronic 

market structure to a number of other markets. 

35When EOL closed, it is likely that many types of trading entities (including voice 

brokers and even alternative one-to-many platforms, such as Dynegy) increased their 

market share and overall business activity. 
Chapter IX 

Docket No. PA02-2-000 IX-33 Price Manipulation in Western Markets

Although the introduction of an electronic platform facilitated risk 

sharing in the energy markets, many of the specific features of EOL 

were certainly not essential for a successful electronic platform. ICE 

and TradeSpark offer interesting examples of electronic commodity 

trading facilities designed from a different underlying premise. They 

have emerged as major trading platforms, particularly in the aftermath 

of Enron’s collapse and the demise of its EOL platform. ICE and 

TradeSpark provide automated execution facilities (electronic markets) 

in which all traders have identical access and trading opportunities,37

i.e., they serve as electronic brokers. The market systems at ICE and 

TradeSpark are fully transparent limit order market systems. The 

entire order book is displayed to all market participants and 

subscribers rather than just a two-way quote (e.g., the spread). By 

displaying the entire order book continuously, including the depths at 

various prices, the market exhibits ex ante transparency. Traders then 

know the full amount of committed or displayed liquidity that is 

available in the marketplace from various counterparties without 

further market reaction. 

However, the identities of the clients submitting orders are not 

displayed, so that in this sense the market design is “anonymous.” The 

ICE and TradeSpark platforms execute orders sequentially in a system 

in which price and time priority are respected. Price priority ensures 

that orders at better prices are executed prior to orders at inferior 

prices, while time priority ensures that orders at a given price are 

executed in order of submission. Immediately after order execution, 

trade prices and volumes are reported on ICE and TradeSpark. 

The systems are ex post transparent because they provide timely 

transaction reports. Traders then know that other market participants 

entered into a transaction at the stated price, which gives them 

information about other market participants’ assessment of supply and 

demand in this market. However, the privacy of trader identities 

 36Although ICE’s market design is rather different from that of EOL, ICE does 

emulate EOL with respect to the broad idea of an easy-to-use electronic platform and 

such “bells and whistles” as operating out of the browser rather than just in PC 

mode. The transition in which ICE’s activity increased at the expense of EOL 

occurred over several months. 

37These differ in fundamental ways from EOL. The nature of the access to order flow 

information on ICE and TradeSpark also contrasts with some of the well-known U.S. 

trading floors (e.g., the New York Stock Exchange (NYSE), the Chicago Board of 

Trade (CBOT), the Chicago Board Options Exchange (CBOE), and the New York 

Mercantile Exchange (NYMEX)), in which specialists and floor traders have access 

to the flow of information and the right to trade on the floor is restricted to a limited 

number of members. The capitalized value of that access is illustrated by the market 

price of a seat (membership) on various floors. Differential access of market makers 

also arises in other market settings, such as the NASDAQ. 
Chapter IX 

Docket No. PA02-2-000 IX-34 Price Manipulation in Western Markets

continues to be protected subsequent to the trade execution, except that 

the identity is disclosed after trading to one’s counterparty to facilitate 

trading. This prevents other traders (except the counterparty) from 

exploiting information about one trader’s interest in trading. 

Credit Risk and the Organization of ICE and TradeSpark 

A complication that arises in the ICE and TradeSpark platforms is the 

need to handle credit risks because the trading parties do not know the 

identity of their counterparty at the time of trade. This complication 

was not present in EOL because all parties trading with Enron knew 

their credit limits and standing with Enron. The basic contracting 

structure underlying ICE and TradeSpark is not a “clearing 

mechanism” in which the parties trade with a clearing corporation and 

“margin” (collateral value) adjustments are used to ensure the 

fulfillment of the contractual obligations (as in conventional futures 

contracts). Instead, these markets use a set of bilateral contractual 

arrangements to limit credit exposure to the contractual performance 

problems of its clients and maintain the overall credit matrix under 

which the parties define acceptable counterparties.38 Each pair of 

counterparties trading with each other in the ICE platform is required 

to have a master contractual agreement. The actual transactions 

between the parties are bilateral, as the platform’s role is to simply 

facilitate the matching of buyers and sellers and “confirm” the trade 

execution with them. 

The ICE and TradeSpark platforms allow each firm to designate the 

firms with which it is willing to trade particular products.39 The order 

book systems prevent ineligible counterparties from trading with one 

another. The order systems display any orders in the order book that 

the trader cannot access due to credit issues, and the system design 

prevents the execution of ineligible orders. Under these systems 

various clients face different subsets of ineligible (and eligible) orders. 

This design is a clever way to address the fundamental credit problems 

(whose centrality in commodity pricing has become especially 

apparent in the last year) and the diverse views of market participants 

about the creditworthiness of other market participants. Strikingly, this 

design can address the creditworthiness of the particular counterparty 

to a trade (through the prespecified credit matrix) without requiring 

 

38The clients needed to make broad credit determinations outside the trading system. 

The platforms do not provide any information or services with respect to assessing 

credit worthiness, as they simply set up a mechanism for the customers to make their 

own determinations. The participants can then manage the controls provided to them. 

39The systems allow flexibility in defining permissible counterparties. Depending on 

the system, these might vary with the type of product and also are subject to potential 

restrictions on the size of particular exposures (e.g., the customer can impose daily 

limits). 
Chapter IX 

Docket No. PA02-2-000 IX-35 Price Manipulation in Western Markets

disclosure of trader identifications. However, the systems do not allow 

contract pricing to vary by counterparty beyond barring unacceptable 

matches. 

To understand the implementation of this credit system it is important 

to recognize that, as in other electronic limit order markets, there is a 

common ranking of orders in the limit order book as orders are ranked 

by price and then by time of submission. Under price and time priority, 

an investor purchasing in the limit order market purchases the 

commodity from those offering to sell at the lowest price (price 

priority), purchasing the good in sequence by the time of order 

submission (time priority). The role of time priority in such markets is 

to increase the incentive for providing limit orders that enhance 

liquidity provision.40 Orders are executed following price (and then 

time) priority, subject to the credit constraints (two parties can trade 

with each other only if each is an acceptable credit to the other in the 

specific product context). However, unlike conventional electronic 

limit order markets, at a global level departures from price and time 

priority can arise because the system will not execute a trade with a 

prohibited counterparty (e.g., in the ICE and TradeSpark displays an 

order seeking immediate execution skips over the inaccessible orders 

in the limit order book). “Inverted markets” (in which the bid price 

exceeds the ask price) can arise because of differences in who is 

eligible to post or trade quotes. If the same counterparty is eligible to 

trade with both the bid and ask quoters, then, ignoring credit risk, that 

party can earn “arbitrage” profits. For example, suppose one party is 

willing to buy at $4.00 and another is willing to sell at $3.95, but the 

two cannot trade with each other because of credit restrictions. In this 

case, a third trader who is allowed to trade with both parties can buy at 

$3.95 from the credit-inhibited seller and sell the same amount at the 

same time to the credit-inhibited buyer who posted a $4.00 asking 

price. Note that parties who are not able to trade at the best quote 

(because of credit issues) are still not squeezed out of the market 

completely. 

Because of differences in their credit evaluations, different firms will 

trade with different counterparties. Firms with tight credit standards or, 

alternatively, firms with poor credit, will face higher execution costs. 

The markets that these firms face have less depth because of access to 

a more limited set of counterparties. The ICE and TradeSpark systems 

are intended to create a “Chinese wall” between the trader and the 

 

40However, the role of time priority is modest if the pricing grid is tight (the trader 

can jump ahead of the queue for a tiny price concession). This is illustrated by the 

effect of decimalization on time priority on the New York Stock Exchange and 

NASDAQ. The minimum tick sizes on ICE and TradeSpark are very small (between 

$.01 and $.001 for various products). 
Chapter IX 

Docket No. PA02-2-000 IX-36 Price Manipulation in Western Markets

client’s credit manager. The same individual should not make 

decisions concerning both trading and counterparty credit risk. This is 

intended to avoid the conflict of interest in which the trader would 

maximize his trading profit by trading with as many counterparties as 

possible, assuming the trader does not bear consequences for any 

defaults. 

The need for a Chinese wall emphasizes the vulnerability of the credit 

restriction system to collusion between the trader and the credit 

manager, as well as across firms. In particular, different firms that 

wish to undertake “wash sale” trades with one another can do so by 

identifying the remaining trading firms that can intervene and execute 

on the quote as unacceptable credit risks, thereby disabling the other 

firms from participating in the wash transactions.41 The wash sales 

provide a mechanism to increase one’s trading volume and potentially 

to manipulate the reported price.42 As a by-product of the remainder of 

the trader’s holdings, there may be natural incentives to provide false 

prices to alter the perceived value of the asset. Of course, in a 

conventional electronic market the ability to artificially move the price 

is limited because of the constraints of competing orders. For example, 

if a trader posts a price that is above fair market value, that trader faces 

the risk that another trader who is not involved in the wash trade 

scheme will execute on that posting. 

The ICE platform provides notice to parties when their credit status 

changes. The ability to change the credit setting on ICE and identify 

rivals as not credit worthy greatly facilitates the ability to manipulate 

reported prices by wash sales. 

Evidence indicates that certain members of the consortium that 

initially formed ICE did execute wash transactions by altering credit 

acceptance ratings so that they could only trade with a planned partner. 

The consortium incorporated a variable equity interest that provided 

incentive for the consortium members to trade on ICE. Ownership 

interests could rise with increasing transactional volumes by those 

owners. It appears that some consortium members attempted to 

increase that ownership interest through wash trades. They placed 

credit restrictions to prevent others from trading and then executed 

large trades. 

These wash trades emphasize the importance of the ownership 

structure of the trading platform in general and specifically raise 

 

41This occurred on ICE but could not occur on TradeSpark due to TradeSpark’s 

requirement of allowing transactions only when there are a minimum number of 

potential counterparties. 

42See Chapter VII, p. VII-14 for more detailed discussion on wash transactions. 
Chapter IX 

Docket No. PA02-2-000 IX-37 Price Manipulation in Western Markets

questions about the suitability of the incentives provided to increase 

volume and whether the credit restriction mechanism can facilitate 

collusion among firms to create wash sales. 

Contrasting ICE and TradeSpark With EOL 

The contrast between the structure of EOL and these platforms is 

striking. EOL was initially organized as a dealer market (one-to-many 

trading platform), while ICE and TradeSpark were multilateral trading 

platforms (many-to-many trading platforms). Initially, it was intended 

that EOL would earn the dealer spread and support the trading 

activities of the parent firm, Enron, which was a major player in most 

of the underlying energy markets. Enron was the counterparty for all 

the trades on EOL. EOL lacked transparency as the order book was not 

displayed (except for its two-way quote) and trades were not reported. 

As a result of this lack of trade reporting, when prices quoted on EOL 

changed, investors would not be able to tell if those changes resulted 

from transactions or for any other reason. For example, the EOL 

market maker might have changed the price because market 

fundamentals changed or possibly to mislead the market. 

In contrast, ICE and TradeSpark are pure brokerage systems based on 

a multilateral trading platform (these systems do not participate in 

individual trades), earning brokerage, confirmation, and data fees. 

They provide equal access and information to all eligible participants. 

The order book is always displayed and trade executions are reported 

in a timely manner. 

Despite its informational structure and other features of the EOL 

platform by which Enron enjoyed major advantages, the EOL system 

itself was apparently quite popular. Nevertheless, many participants 

(who were also competitors with Enron) became frustrated with the 

EOL platform. For example, the formation of ICE and TradeSpark 

each reflected a consortium model whose partners (financial 

institutions and trading firms) were concerned about the monopoly 

power that had accrued to Enron in establishing EOL as the 

“marketplace.” In the case of ICE, to help the market get started, the 

founders agreed to make initial order flow commitments (for relatively 

small amounts). However, due to the concerns Staff described earlier, 

and for other reasons, ICE is now evolving to an independent board 

structure and is trying to provide financial liquidity to its owners.43 

 

43To mitigate conflicts of interest, information about rivals is not shared with the 

board and decisions as to which contracts to trade are viewed as business 

development rather than board issues. 
Chapter IX 

Docket No. PA02-2-000 IX-38 Price Manipulation in Western Markets

Although EOL did not engage in trade reporting or order display to 

retain maximum advantage relative to its counterparties in the trading 

process, ICE is finding it valuable to publish more of the data because 

an important portion of its business model is to sell data. Since ICE 

itself is not a dealer, its sources of revenue are very different than 

those of EOL. Of course, broad sales of transactional data are a 

significant part of the revenue of major equity markets (such as the 

New York Stock Exchange and NASDAQ). 

The Role of Voice Brokers 

The major competition faced by electronic trading platforms is from 

voice brokers,44 who perform a central role in searching for and 

matching potential counterparties to a trade. They are dominant across 

products (even for month-ahead products), except for the next-day 

instruments.45 Voice brokers have recently become more important as 

credit issues are now extremely significant in the marketplace; when 

one trades through a voice broker, one’s decision can be contingent 

upon the specific identity of the counterparty (even in the ICE and 

TradeSpark platforms one can only condition upon the counterparty 

being an “acceptable” credit). Customers also feel that they obtain 

valuable information for trading with the use of a voice broker.46

Many of the competing brokers are actually hybrids (a voice broker 

plus an electronic platform that serves as a “matching engine”). Voice 

brokers recently formed the Energy Brokers Association to develop a 

code of ethics for brokers.47 It is important to note that Bloomberg, 

like ICE, does not have a voice broker; however, it has introduced an 

electronic platform called “Powermatch.” 

 

44Voice brokers were the dominant portion of the trading system prior to EOL and 

continue to be widely used at present. 

45Because of the industry commission structure, which is proportional to the 

underlying physical quantities, the single-day contract is not attractive to voice 

brokers. There are natural economic efficiencies in processing small trades in a 

relatively automated manner. This is somewhat parallel to traders preferring more 

customized handling of larger trades (to facilitate strategic handling of the order to 

minimize its potential price impact), but not smaller trades, for a given instrument. 

The mechanics of electronic market design are efficient in addressing a high volume 

of transactions. In short-term instruments there is a lot of trading and a concentration 

of activity within a few hours. 

46However, at some level the information provided by voice brokers must form a 

“zero-sum” game (i.e., any information received is at the expense of someone else 

trading through that broker), although voice brokerage still can be an efficient 

trading system. 

47The founding members are Amerex Group, APB Financial LLC, GFI Group Inc., 

Natsource LLC, Prebon Energy Inc., Starsupply Petroleum LLC, and TFS Energy 

LLC. 
Chapter IX 

Docket No. PA02-2-000 IX-39 Price Manipulation in Western Markets

While there is considerable bilateral (OTC) trade in the sense that 

trades in many instruments do not go through a “clearing” exchange 

(such as the NYMEX), there is very little “direct” trade that does not 

go through an intermediary in the marketplace. Firms value the 

anonymity of using a broker and want the maximum amount of 

competition on the other side of their trade.48

Conclusion: Forward 

Looking Recommendations 

As mentioned earlier in this chapter, Staff provided evidence of the 

manipulation of the physical natural gas market at the Henry Hub in 

Louisiana in order to profit in the financial markets. The structure of 

the EOL platform enhanced Enron’s ability to perpetrate the 

manipulation. Informational advantages arising out of the EOL 

platform allowed Enron to directly apply the manipulation as market 

maker. EOL provided Enron the ability to better time the manipulation 

through the use of real-time data about individual market participants 

and by monitoring their responses. The ability to mislead market 

participants through complete control of the quote-setting process 

further enhanced Enron’s ability to manipulate the market. Finally, the 

lack of transparency of the EOL system (in failing to provide 

information regarding limit orders and the stack, and in failing to 

provide information on past trades) enhanced Enron’s ability to keep 

competitors in the dark. 

As traders lose money in markets where they suffer significant 

informational disadvantages and manipulations, they may withdraw or 

reduce trading in those markets, thereby reducing liquidity. As 

liquidity falls, market makers will tend to demand higher fees because 

of the additional risks they bear as the difficulties in offsetting 

purchases and sales rise. These additional costs are borne by all 

companies that buy, sell, or hedge energy products. 

Market manipulation also causes the misallocation of resources due to 

incorrect price signals. The inability to correctly value a particular 

energy product can lead to inefficient investment choices in energy 

plants and technology. The potential for future manipulation causes 

energy product traders to substitute away from instruments likely to be 

manipulated. As a result, there may be inadequate use of spot markets 

and excess precautionary use of storage and long-term contracts. 

Manipulation does not simply transfer wealth among market 

 

48The one exception would be for a very few specialized products in which there are 

only a few potential suppliers. 
Chapter IX 

Docket No. PA02-2-000 IX-40 Price Manipulation in Western Markets

participants; it causes deadweight losses to society as a whole by 

distorting consumption and investment decisions. The overall 

combination of costs and distortions applies not only to manipulation 

through market trades, but also to the false reporting of index prices to 

influence settlement prices for derivative instruments and direct 

bilateral contracts. These latter concerns are described in Chapter III. 

Low-burden methods of gathering useful information exist and can be 

implemented at a very low cost. Additional information would allow 

Staff to more efficiently identify these manipulations. Voluntary 

disclosures by a gas trader in an informal interview led to Staff’s 

discovery of the July 19, 2001 Henry Hub manipulation. Without these 

disclosures, it is unlikely that FERC Staff would have discovered the 

manipulation. Looking forward, Staff will need to be equipped with 

additional information to identify similar manipulations. 

Staff needs the ability to quickly identify evidence of churning. In the 

investigation of Reliant’s trading in southern California and Enron’s 

trading at the Henry Hub, Staff identified evidence of churning (in 

which investors turn over their positions quickly rather than 

establishing stable positions based on long-term needs). Information 

about the identity of market participants and associated transactions is 

available to many of the markets (such as ICE and TradeSpark). This 

information would be useful to FERC on a historical basis and through 

a real-time data feed. It would enhance FERC’s understanding of the 

markets’ operation on an ongoing basis and could significantly 

enhance its monitoring and enforcement capacity and role. The 

selection of particular data filters and tests to monitor data would 

facilitate the automation of this review process. 

A particularly important approach would be to monitor the markets 

directly for churning. For example, a “churn alarm,” which would 

monitor for a large amount of net buying (or selling) in a short period 

of time, would be helpful in identifying aggressive trading behavior. 

While this would likely generate a high proportion of false positives 

due to the nature of liquidity provision, it could also identify more 

suspect trading behavior. 

As Staff discussed earlier in this chapter, evidence exists that 

companies successfully executed wash trades over ICE by restricting 

the credit of companies not participating in the wash trading scheme. 

This ensured that competitors could not execute trades on offers placed 

on ICE that were intended for a specific company. A filter that 

monitors credit changes for corrupt reasons could be used to help 

evaluate unusual patterns in credit changes. 
Chapter IX 

Docket No. PA02-2-000 IX-41 Price Manipulation in Western Markets

Staff believes that electronic data that directly provide trading 

information and efficiently report instances of concern to FERC would 

provide an effective oversight capability with minimal cost to the 

industry. FERC would be able to learn from exposure to the 

information, distinguish false positives, and follow up where concerns 

remain. The cost of implementing this type of sophisticated system is 

decreasing and would likely increase Staff’s productivity dramatically. 

Staff believes that self-monitoring and reporting requirements could be 

created that would mandate companies to disclose behaviors that fall 

within certain definitions or risk losing their certificate to trade gas. 

Under parts 284.284 and 284.402 of its regulations, the Commission 

issued blanket certificates for unbundled gas sales services and 

marketing services, respectively. Staff recommends a proceeding to 

decide if and to what extent regulations should be implemented that 

require reporting to avoid losing or affecting the rights granted under 

the blanket certificates. 

An important fundamental principle about market design and marketbased rates is that commodity pricing should reflect competitive 

market conditions and the minimization of trading costs. The market 

design should be “workably competitive.” For example, it is difficult 

to see how a market trading structure in which a single firm (such as 

Enron) is a dominant player and operates the leading platform (EOL) 

would meet these competitive standards in light of the potential for 

rent extraction and information production to advantage the dominant 

firm. While this report should not be construed as requiring one 

specific and definitive microstructure design of the trading structure, it 

does point to some of the types of dimensions in which the efficiencies 

of the microstructure of trading can be enhanced. Our report 

emphasizes the importance of effective competition across platforms 

and market designs. 

One of the ways in which markets would be less prone to manipulation 

is by an open architecture and transparent trading system.49 It is 

striking that EOL participants lacked access to information about the 

book of limit orders, except for the quotes, including knowledge of the 

location of the competition. One of the problems in the EOL design is 

that public investors cannot identify the available pockets of liquidity 

from Enron and public investors, but yet Enron can. A fundamental 

aspect of this point concerns the asymmetric observability of 

information, such as the limit order book, rather than the lack of public 

information per se. Outsiders would have been especially reluctant to

show their hand in light of this asymmetry in the structure of 

 

49This would discourage manipulations through the trading process and by providing 

false trade information to producers of market indices. 
Chapter IX 

Docket No. PA02-2-000 IX-42 Price Manipulation in Western Markets

information and the potential ability of counterparties (such as Enron) 

to exploit any informational advantage. 

Regarding the informational advantage EOL provided to Enron, the 

markets have adjusted. Currently there are no successful one-to-many 

platforms. UBS, which took control of the EOL platform, recently 

announced that it would no longer provide a one-to-many service. 

Dynegy did the same with regard to its one-to-many platform, 

DynegyDirect. ICE and TradeSpark are currently operating the leading 

electronic exchanges and are relatively transparent many-to-many 

exchanges. Nevertheless, Staff has recommended in Chapter VII of 

this Report that the Commission condition blanket gas certificates and 

market-based rates to require that sellers who use these platforms 

ensure that the platforms have certain information and monitoring 

features. 
Chapter X 

Docket No. PA02-2-000 X-1 Price Manipulation in Western Markets 

X. Analysis of Allegation That Williams Energy Marketing & 

Trading Company Attempted To Corner the Market in California 

for January 2001 Gas 

The Commission Staff investigated an allegation that appeared in The 

New York Times on June 2, 2002 that Williams Energy Marketing & 

Trading Company (Williams) attempted to corner the market for 

natural gas in California and increase prices for gas delivered in 

January 2001. Staff examined trade records and other information and 

documents that Williams provided. Staff concludes that the claims are 

unsubstantiated. 

Williams Energy Marketing & 

Trading Company 

Williams is an energy marketing and trading unit of The Williams 

Companies, a publicly traded, Tulsa-based firm that owns and operates 

natural gas pipelines, among other activities. Williams is engaged in 

the purchase, sale, and arranging of transportation of natural gas. The 

company also provides risk management services through a variety of 

financial instruments and structured transactions, including over-thecounter forwards and other energy-related derivatives.1

 

A major share of Williams’ gas needs relates to tolling agreements that 

Williams has executed under which it provides gas to three electric 

generation facilities in southern California.2

 During the fall and winter 

of 2000–2001, in order to provide gas to these facilities Williams’ 

power desk notified its gas cash desk of the gas volumes required for 

the next business day. The gas cash desk reviewed prior-day actual gas 

consumption to determine daily and month-to-date imbalance 

positions. On a day-ahead basis, the gas cash desk determined whether 

to physically buy or sell gas to meet its requirements based on (1) the 

amount of baseload gas already purchased, (2) the amount of expected 

gas flow on El Paso Natural Gas Company’s pipeline serving southern 

California, and (3) daily pricing versus forward pricing (balance-ofthe-month or next-month pricing), among other factors. The gas cash 

desk then made trades by telephone or online exchanges. On a sameday basis, the gas cash desk monitored intraday changes in gas demand 

 

1

See www.williams.com/productservices/index.jsp and 

yahoo.marketguide.com/MGI/busidesc.asp?target=/stocks/companyinformation/busi

desc&Ticker=WMB. 

2

See the Capacity Sale and Tolling Agreement filed in Docket Nos. ER98-2184-004, 

ER98-2185-004, and ER98-2186-004. The Commission summarized the tolling 

agreement briefly in AES Huntington Beach, L.L.C., 87 FERC ¶ 61,221 at p. 61,877 

(1999). Williams also has additional gas customers in southern California. 
Chapter X 

Docket No. PA02-2-000 X-2 Price Manipulation in Western Markets 

and purchased or sold gas to stay within pipeline imbalance tolerances. 

Based on its view of market fundamentals and changes in gas 

requirements at the electric generation facilities subject to the tolling 

agreements, the gas cash desk might also have held an incremental 

position of long or short going into the following month. 

The Allegation That Williams 

Tried To Corner the Market 

and Drive Up Prices in 

California 

On June 2, 2002, The New York Times printed an article in which it 

quoted Jones Murphy, a former Williams employee. According to the 

article, Williams hired Mr. Murphy as the director of emerging 

products at Williams’ headquarters in Tulsa, Oklahoma, to help 

manage the company’s trading risks. The article states that Mr. 

Murphy was on Williams’ trading floor in December 2000 when he 

heard a commotion at the desk of Blake Herndon, director of risk 

management. The article quotes Mr. Murphy as stating that he “went 

over to ask what was going on,” and that “Blake laughed and said they 

were going to corner the market for natural gas and run it up for 

December closing, which means delivery in January.”3

 The article 

further states that Mr. Murphy “thinks that an examination of trading 

records would show that the company succeeded in driving up natural 

gas prices in California.”4

 

In the article, Mr. Herndon denies Mr. Murphy’s allegation. Mr. 

Herndon is quoted as stating that “[i]t is comical to think that anyone 

could corner the gas market in California. I think this shows the lack of 

understanding of how these markets work.”5

 William Hobbs, president 

of Williams, is also quoted as denying Mr. Murphy’s statement. Mr. 

Hobbs stated that “there has been any number of investigations, and 

Williams has fully cooperated.” He also stated in the article that “[w]e 

have provided piles and piles of documents, and no one has come back 

and said that Williams has done anything wrong.”6

 

3

Banerjee, Neela, “A Collision on Risks of Energy Trading,” The New York Times

(June 2, 2002) at Business section, p. 1. 

4

Id. 

5

Id. 6

Id.
Chapter X 

Docket No. PA02-2-000 X-3 Price Manipulation in Western Markets 

The Commission Staff’s 

Investigation of the 

Allegation

On June 5, 2002, counsel for Williams stated in a letter to the 

Commission Staff that it welcomed an independent review of its gas 

trading data to permit an evaluation of the allegation. Staff requested 

from Williams, and Williams voluntarily provided, a substantial 

volume of data and documents, including records of physical and 

financial transactions executed in the fall and winter of 2000–2001, 

cash book summary reports for gas, daily position reports, and markto-market values. 

As discussed above, the allegation is that Williams drove up prices in 

an effort to corner the market for monthly gas in California with 

delivery in January 2001. Monthly gas is traded over a span of time 

that can begin several months in advance of the month of delivery. 

Peak trading typically occurs in the weeks preceding the month of 

delivery and ends when the month of delivery begins. Positions taken 

by traders are measured in terms of gas quantities, such as MMBtu or 

NYMEX contracts. Position reports typically include relevant 

information such as the geographic location of the gas to be traded and 

the month of delivery. Position statements provide information about a 

trading desk’s position by time and location, and profit and loss 

statements identify profits and losses associated with those positions. 

 

As a general matter, a market participant attempts to corner a market 

by accumulating a long position, which in the context of this 

investigation would mean entering contracts to purchase physical gas. 

To successfully corner a market, the market participant’s long position 

must represent a substantial portion of available supply. When prices 

have peaked, the market participant liquidates its position at profits 

that reflect an exercise of market power. By accumulating a substantial 

position, the market participant can exert market power by raising the 

price it can secure for its supply. 

Conclusion of the 

Commission Staff’s 

Investigation 

For Williams to corner the market for physical gas, it would have 

needed to purchase gas in volumes that greatly exceeded the 

requirements of Williams’ gas customers. We do not see evidence of 

this purchasing activity on a day-to-day or even an intraday basis. In 

November 2000, Williams’ customers’ physical needs pursuant to its 

tolling agreements were 10,274,209 Bcf, and Williams purchased 
Chapter X 

Docket No. PA02-2-000 X-4 Price Manipulation in Western Markets 

10,701,353 Bcf. In December 2000, Williams’ customers’ physical 

needs pursuant to its tolling agreements were 10,905,316 Bcf, and 

Williams purchased 11,143,809 Bcf. Finally, in January 2001, 

Williams’ customers’ physical needs pursuant to its tolling agreements 

were 14,247,195 Bcf, and Williams purchased 12,681,667 Bcf. These 

data show that Williams did not purchase substantially more gas than 

it needed to meet its customers’ physical needs. In fact, the amounts 

that Williams purchased above its needs represent less than 1 percent 

of the gas market in southern California. 

In November and December 2000 and January 2001, Williams’ natural 

gas purchases represented approximately 4, 5, and 6 percent, 

respectively, of the total demand for Southern California Gas 

Company and Pacific Gas and Electric Company. During November 

and December 2000, Williams’ natural gas purchases represented 

approximately 10 percent of the total Southern California Gas 

Company demand. These data place into perspective the dimension of 

Williams’ physical activity in the relevant time period. While not 

insubstantial, it appears to be too small to constitute a corner-themarket strategy. 

Williams’ cash desk began the month of November for southern 

California short approximately 43,000 MMBtu/d at approximately 

$5.20. Gas prices increased throughout the month, from $5.20 to 

$17.99. Overall, the gas cash desk incurred a loss for November 2000 

on physical gas transactions. In December 2000, the gas cash desk 

began the month long for southern California approximately 67,000 

MMBtu/d at approximately $14. Gas Daily index prices averaged 

approximately $25 throughout the month. Overall, the cash desk 

incurred a gain for December 2000 of less than $35 million on 

physical gas transactions. Williams’ profit and loss activity in the 2 

months preceding January indicates a level of profits that is not large 

relative to the size of the gas market in southern California. 

 

In addition to profiting by cornering physical gas, we might also 

expect to see large positions taken in the financial markets in 

anticipation of increasing gas prices. However, we do not see evidence 

of this activity. Williams’ largest long financial position in January 

2001 SoCal gas was 80,000 MMBtu/d. This position was active during 

November 2000. It was small relative to the volume of gas that 

Williams needed to purchase to meet its customers’ needs. The fact 

that Williams’ financial position was far smaller than its physical 

position indicates that Williams did not have a strong belief that prices 

would rise. 
Chapter X 

Docket No. PA02-2-000 X-5 Price Manipulation in Western Markets 

Williams’ gross mark-to-market margin for the forward southern 

California basis January 2001 contract also does not reflect a strategy 

to corner the market. Williams recorded a gain of approximately $3.5 

million in November 2000 and less than $1 million in December 2000. 

Williams’ cumulative gross cash margin for the gas cash desk for 

southern California for January 2001 was a gain of less than $12 

million. 

Based on our review of data, information, and documents that 

Williams provided, the Commission Staff concludes that the 

allegations that Williams cornered the market in southern California 

for January 2001 natural gas and drove up natural gas prices in 

southern California during the fall and winter of 2000–2001 are 

unsubstantiated.