Exploring price impact liquidity for December 2016 NYMEX energy contracts 

by 

Stephen Kane1
 

Research Economist
 

Office of the Chief Economist
 

Commodity Futures Trading Commission
 

1 The author would like to thank his CFTC colleagues: Anu Aggarwal, David Aron, Gloria Clement, Jeff 

Crilley, Nancy Doyle, Nick Fett, Mathew Flagge, Harold Hild, Carrie Kennedy, Richard Haynes, Mathew 

Hunter, Owen Kopon, John Lawton, Lihong McPhail, Scott Mixon, Shallom Moses, Esen Onur, David 

Reiffen, Lynn Riggs, Michel Robe, John Roberts, Hannah Ropp, Paul Schlichting, Julie Schoening, 

Amitabha Shakya, Rajiv Sharma, Stephen Sherrod, and Rahul Varma for comments that improved this 

manuscript. This research was produced under the official capacity of the author. The Office of the Chief 

Economist and CFTC economists produce original research on a broad range of topics relevant to the 

CFTC’s mandate to regulate commodity futures markets, commodity options markets, and the expanded 

mandate to regulate the swaps markets pursuant to the Dodd-Frank Wall Street Reform and Consumer 

Protection Act. These papers are often presented at conferences and many of these papers are later 

published by peer-review and other scholarly outlets. The analyses and conclusions expressed in this 

paper are those of the author and do not necessarily reflect the views of other members of the Office of 

Chief Economist, other Commission staff, or the Commission itself. 

1
 
 

 

 

 

 

 

This paper proposes a new daily price impact assessment for futures contracts, LLLLdd, 

while investigating four December 2016 energy contracts listed on NYMEX: CL (crude oil); NG 

(natural gas); HO (diesel); and RB (gasoline). The paper uses transaction prices in nearby 

futures contract prices to update stale prices. By making this adjustment, the author improves 

the liquidity assessments. Farther out the curve, trading in spread transactions is more 

predominant than in outright transactions. The computations suggest that a market participant 

could have achieved, in general, a smaller price impact than trading in an outright December 

transaction by first entering into a December-to-December spread transaction in CL and then 

exiting out of the new December position with one year shorter time to expiration with a 

corresponding outright trade. The lower price impact may be due to substantial liquidity that 

may result from market participants using the spread transactions to increase the time to 

expiration of their CL positions. This result, however, fails to hold for the other three energy 

contracts. 

2
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1. INTRODUCTION 

The author proposes a new daily liquidity assessment, LLd.

2 The paper examines the 

liquidity of the December 2016 contracts on NYMEX for light sweet crude oil3 (CL), Henry Hub 

natural gas4 (NG), New York Harbor ULSD5 (HO), and RBOB gasoline6 (RB). Over the 

lifetime of the contracts, generally, the price impacts are less than 1.0% of the contract price. 

2. LIQUIDITY ASSESSMENT 

LLLLdd is the volume-weighted average price impact of trades involving a futures contract 

over a trading day.7 It focuses on trades that may affect changes to open interest at the end of the 

trading day and not just the immediate ability to trade with a counterparty which has been the 

traditional focus of liquidity assessments that are designed for market making.8 LLLLdd does not use 

limit order book quotes, because quotes do not represent consummated trades. Further, some of 

the liquidity in the limit order book is fleeting and cannot be traded against. In addition, the limit 

2 See Leon (2012) for a discussion on the importance of liquidity risk management for financial 

institutions and their supervisory regulators. 

3 The underlying is West Texas Intermediate crude oil that may be delivered in Cushing, OK. See 

http://www.cmegroup.com/trading/energy/crude-oil/light-sweet-crude_contract_specifications.html. 

4 Henry Hub is located in Erath, LA. See http://www.cmegroup.com/trading/energy/naturalgas/natural-gas_contract_specifications.html. 

5 ULSD stands for ultra-low-sulfur diesel. This contract used to be called heating oil. The contract 

specification was changed slightly by NYMEX, but the contract still retained its HO symbol. See 

http://www.cmegroup.com/trading/energy/refined-products/heating-oil_contract_specifications.html. 

6 RBOB stands for Reformulated Blendstock for Oxygenate Blending. This is gasoline before it is 

blended with denatured fuel ethanol. The delivery location is New York harbor. See 

http://www.cmegroup.com/trading/energy/refined-products/rbob-gasoline_contract_specifications.html. 

7 The paper defines a trading day to include all traded contracts that are cleared on the same date. 

8 See Fett et al (2016) and Marshall et al (2012) for literature reviews of liquidity assessments in futures 

markets. See Kervel et al (2016) for a liquidity discussion concerning large institutional orders in a low 

latency environment. 

3
 
 

 

 

 

 

 

 

 

 

 

 

 

 

order book may not replenish quickly. Finally, the act of offloading a position may induce 

market makers to increase their ask price or reduce their bid price or both (i.e., widen their bidask spread) to protect themselves against the adverse selection risk that is inherent in market 

making, causing the market price to move against a trader (Kyle (1985)). 

The author anticipated that LLLLdd for a contract would tend to be slightly higher, i.e., less 

liquid, near the inception of the contract and improve, but far from monotonically, as the time to 

expiration decreases. When a contract enters the spot month,9 the author anticipated that the 

contract would become slightly less liquid, too. This is because the author thought that LLLLdd

would be similar to other more traditional assessments of liquidity, namely, open interest and 

trading volume. As such, the liquidity assessments far out the curve (longer time to expiration of 

the futures contract) came as a surprise. 

LLLLdd gives equal weight to the price impact involved for each futures contract traded. 

This volume-weighting is more appropriate with futures data, because open interest10 is not 

fixed.

11 Moreover, volume-weighting is better suited to account for market participants electing 

9 For the four energy contracts considered in this paper, the spot “month” is the last three trading days of 

the physical-delivery contract (This is the convention we have of calling a period a month even when 

we’re only talking about a few days). Long and short positions held to the close of trading on the last 

trading day, and not offset by an exchange-for-related-position (EFRP) transaction, are matched by the 

clearinghouse and delivery occurs after the last trading day. This feature (delivery only after the last 

trading day) is different from agricultural futures contracts, where delivery generally takes place during 

the spot month. See termination of trading provisions in NYMEX Rulebook chapters 151, 191, 200, and 

220, available at http://www.cmegroup.com/rulebook/NYMEX/1a/150.pdf, 

http://www.cmegroup.com/rulebook/NYMEX/1a/191.pdf, 

http://www.cmegroup.com/rulebook/NYMEX/2/200.pdf, and 

http://www.cmegroup.com/rulebook/NYMEX/2/220.pdf. 

10 Open interest is the number of futures contracts outstanding on the long side of a futures contract. 

11 The number of securities outstanding is generally fixed but may change with an initial public offering 

or a secondary offering. In addition, short sellers are restricted by their ability to borrow a security. 

Nevertheless, there is no legal restriction on the number of times a security may trade during a day. 

4
 
 

 

 

 

 

 

 

 

 

 

to shred their orders, i.e., to break up their orders into smaller trades, because volume-weighting 

accounts for the total amount of a large transaction that is shredded.12 Otherwise, shredded 

orders might be given too much influence in a liquidity assessment, because without volumeweighting each shredded trade in the overall transaction would be treated separately. LLLLdd

assesses the price impact of larger quantity trades with commensurately larger weight. Since 

volume-weighting applies the proportion of contracts traded relative to total volume, it is more 

suitable for clearing applications that seek to estimate the liquidation costs to offload positons in 

a contract month than liquidity assessments that treat each trade equally. In this manner, LLLLdd is 

distinguished from immediacy liquidity that is more relevant in the context of market making. 

LLLLdd uses the first trade of the day to initialize the assessment, so the summation for LLLLdd

begins at 2 and not at 1. LLLLdd is defined as follows: 

Let PPii= the price of trade i. 

Let PPii

∗ = the proxy for the current market price. This might be PPii−1 or something else. 

Let QQii = quantity traded, the number of futures contracts traded) in trade i. 

Let NNdd = the number of trades on day d. 

NNdd Let TTTTdd = Total notional volume during a trading day d except for the first trade, that is ∑ii=2 QQii. 

NNdd QQii ∗ LLLLdd = ∑ | ii=2 |PPii − PPii TTTTdd

12 For a discussion on how to assess the cost of rebalancing a portfolio, see Perold (1988). Specifically, 

an implementation shortfall calculation might use LLLLdd in imputing benchmark prices for a portfolio 

rebalancing. 

5
 
 

 

 

 

 

 

 

 

 

 

 

 

 

|PPii − PPii

∗

| is measured in U.S. dollars. TTTTdd is measured in quantity traded. The 

coefficient QQii is without units because it is quantity traded/ quantity traded. Thus the units of TTTTdd

LLLLdd are $s. 

The paper’s data set includes block trades that have timestamps,

13 because the 

investigation seeks liquidity that might be needed to liquidate a large position, as may be the case 

if a DCO14 instructs a clearing member to offload some or all of a market position.15 Such 

liquidity demand may ultimately induce market participants, not necessarily the other side of the 

trade, to maintain open interest at the end of the trading day. 

Determining when a block trade occurred is difficult. NYMEX does not require 

reporting of the time when a block trade occurred. NYMEX reports a block trade only after it is 

reported to them. After engaging in a block transaction, NYMEX grants participants a five 

minute period to report their trades to them. This allows time for the parties to transact without 

the immediate worry of other market participants learning about the large trade and deciding to 

trade in front of their anticipated trades, leading to worse price executions. In the calculations 

that follow, the paper presumes that block trade participants will take the full five minutes to 

13 Block trades are trades that are negotiated away from the exchange, usually bilaterally, and then are to 

be reported to the exchange within the allowed time delay. Unfortunately, many block trades do not have 

timestamps. The author removed all trades without timestamps from the analysis because the author does 

not know where to place such trades in the time series. 

14 A DCO has authority to take action with respect to a clearing member. See CFTC regulation 

39.13(h)(6). It would be the clearing member that takes action with respect to a FCM when the clearing 

member is not the FCM. The FCM is the party that takes action with respect to an FCM’s customer’s 

position. 

15 For some applications, an investigator might be interested in only the liquidity emanating from the 

matching engine and elect to exclude block transactions from the computation. Block trades that have 

timestamps are included in this paper because they represent liquidity that a market participant might 

exploit to exit out of a position. 

6
 
 

 

 

 

 

 

 

 

 

 

 

 

 

report their trades to NYMEX. So the computations move block trades back five minutes in the 

time series. LLLLdd is sensitive to where block trades are placed in the time series as this affects the 

choice of the proxy for the market price. Further, LLLLdd is weighted by the relative volume of the 

trade to the total trading volume that happens over a trading day so block trades are given more 

weight in LLLLdd. As a sensitivity test, the author computed LLLLdd assuming no time delay, and 

results were qualitatively similar. 

LLLLdd includes all outright-to-outright transactions.16 Since the exchange matching engine 

has functionality that allows outrights to trade against spreads, LLLLdd also includes outright-versusspread transactions.17 LLLLdd is sensitive to including outrights-versus-spread trades because these 

transactions generally improve liquidity, i.e., lower LLLLdd, especially far out the curve. 

LLLLdd does not include spread-versus-spread transactions because a market participant 

cannot use a spread transaction directly to liquidate an outright position that is one side of the 

market.

18 A trader can liquidate a spread position, however, if the position is the legs of the 

spread. 

LLLLdd is a proxy for liquidity that is computed using price changes. There are price 

changes that are not due to the liquidity needs of traders, however. Prices may move when there 

16 An outright-versus-outright transaction means that both sides of the transaction assume positions only 

in same calendar month contract. 

17 A spread transaction is a transaction in which a trader takes positions in at least two different calendar 

month contracts. For example, a trader might take a short position in a December 2016 contract and 

simultaneously take a long position in a December 2015 contract. 

18 The paper does consider the ability of market participants to use spread transaction indirectly. 

Specifically, a market participant first engages in a December 2016/December 2015 spread transaction 

and then exists out of the December 2015 position with an outright transaction where there is better 

liquidity. The author acknowledges that this is an area warranting future research because the provision 

of spread versus spread trading may play an important role in trading deferred contract months. 

7
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

are new pre- and post-trade disclosures or other information disclosures or subsequent analyses 

involving these disclosures arriving to the market. Further, prices may move if market 

participants actively disagree about the price formation implications of market fundamentals. 

Consequently, a contract market may be more liquid than LLLLdd assesses it to be on a given day. 

If there is substantial trading volume, the overestimate of the price impact of trading may be 

reduced substantially, but not eliminated entirely. 

3. AMIHUD-LIKE ASSESSMENT 

As a sensitivity test, this paper considers another liquidity assessment that employs 

consummated trades: 

1 ∑NNdd AAdd = |PPii − PPii

∗ ii=2 | / QQii (NNdd−1) 

AAdd is an Amihud-like price impact ($/quantity traded). The two assessments are 

different, but they have the same sum (except for units), if QQii is equal to 1 for all i, namely, 

1 ∑NNdd |PPii − PPii

∗

| . The author compares LLLLdd and AAddto by assuming one contract is (NN ii=2 dd−1) 

traded in AAdd. 

Weighting larger quantity trades more heavily is appropriate in determining the cost to 

liquidate a position in a calendar month because we are interested in the average cost to trade a 

contract and not the average cost of individual trades. AAdd gives less weight to large quantity 

trades whereas LLLLdd gives more weight to larger quantities traded. Absent different price 

executions for different order sizes, AAdd is still affected by how an order is shredded, but LLLLdd is 

invariant to how an order was broken up because LLLLdd gives the overall trading the same 

weighting in the assessment. 

8
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

For contrast purposes and because there is no “correct” assessment per se, the graphs of 

LLLLdd and AAdd are presented for all the energy commodities considered. Even though there are 

theoretical reasons to select LLLLdd over AAdd for an initial margin surcharge application, there are not 

strong empirical reasons for the contracts examined. When performing two-sample t-tests with 

unequal variances for the energy contracts considered in this paper, the distributions of LLLLdd and 

AAdd are not statistically significantly different from each other at the alpha=0.05 level. Most 

trades consummated by the matching engine are for only one contract. Further, many large 

volume block trades failed to have timestamps. These facts combined with the similarity in the 

price impact between larger volume trades and smaller volume trades help to explain the lack of 

statistical significance between the different liquidity assessments. 

4. STALE PRICES 

The computation of LLLLdd or any assessment based on consummated trades is less reliable 

as a proxy very far out the curve, because of infrequent trading. First, LLLLdd cannot be computed 

when there are less than two trades. Second, PPii−1 , as a proxy for the current market price, PPii

∗

, is 

suspect when there are just a few trades, because tick-by-tick price changes are more likely to be 

due to other reasons than liquidity demands. This makes LLLLdd a weaker proxy for liquidation 

liquidity near the inception of trading of a futures contract when there is a longer time until the 

expiration of the contract, i.e., far out the curve. 

In an attempt to address the second concern, the paper constructs a more sophisticated 

proxy for the current market price, PPii

∗

, than PPii−1 . The proxy exploits the frequent trading in 

contract months in the same commodity near expiration. The paper uses PPii

^, the price of the last 

non-block outright-to-outright traded contract in a close-to-expiration contract month, while 

9
 
 

 

 

 

 

 

 

 

 

 

 

 

 

assuming that the implied spread of between the calendar month and a close-to-expiration 

contract month is constant (i.e., using PPii−1

^~ , the most recent trade price in the near-to-expiration 

contract before trade i in the far-to-expiration contract , and PPii−1, the most current trade in the 

far-to-expiration before the recent trade i in the far-to expiration contract, and computes the 

implied spread, (PPii−1 - PPii−1

^~ ) which is assumed to be constant while there is no trading in the farto-expiration contract.

19 

Specifically, the paper uses the most current difference in the price between the last 

traded contract in (1) the calendar month in the far-to-expiration contract and (2) the close to 

expiration contract month, that has a timestamp less than or equal to the timestamp of the last 

trade in the far-to-expiration contract for the implied spread. If there are equal timestamps, then 

the method sorts on the exchange match-id to determine which trade occurred first. The paper 

then adds the price of the close-to-expiration contract with the implied spread, which is assumed 

to be constant. However, if there are no trades in the near-to-expiration contract directly after the 

last trade in the far to expiration contract month, then the computation uses the previous price in 

the far-to-expiration contract, PPii−1 , for the current market price. That is: 

∗ ^~ PP ) ii = ൛ PPii

^ + (PPii−1 - PPii−1 if the last trade in time is in near-to-expiration contract, or 

PPii−1 otherwise. } 

Since CL terminates trading three business days before the 25th of the month, the author 

chose to use the contract for the calendar month of the cleared date plus 1 month at or before the 

19 The implied spread between far away contracts months might have less volatility than the price of a 

contract in a far-away contract month, because the spread might not be so sensitive to information 

disclosures or analyses that concern the spread and not the entire term structure of crude oil. 

Nevertheless, implied spreads may be sensitive to supply interruptions, demand shocks, and storage 

activity that involve the relevant time interval, among other things. 

10
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

15th of the month and the cleared date plus 2 months after the 15th of the month for the near-toexpiration contract. This was done to approximately obtain the contract month with the highest 

trading frequency, avoid the spot month, and to be computationally straightforward. 

The definition of the near-to-expiration contract was modified for HO and RB because 

the highest trading volume occurs in contract months other than those closest to expiration. 

Instead, the computations use one month later for the near-to-expiration contract for both HO 

and RB. 

5. SPREADS 

Many traders used spread transactions to extend the time until expiration of their futures 

contracts. In offloading an outright position far out the curve, a market participant might have 

preferred spread transactions involving the December 2016 contract, because it may have been 

cheaper to use spreads and a closer to expiration outright contract than using an outright 

transaction in the December 2016 contract. The author considered a December 2015-December 

2016 spread transaction because it is had the highest trading volume of all spreads with the 

December 2016 contract in crude oil over the lifetime of the December 2016 contract by a 

substantial margin. In particular this spread transaction had highest trading volume far out the 

curve. There was substantial trading volume in CL for the June 2016 spread to December 2016 

that a DCO might utilize, too. The remaining energy contracts December-to-December spreads 

are less liquid.20 This made it impractical to engage in a spread trade to the contract that is one 

20 The largest trading volume calendar spread transaction in NG is the April/May spread in the same year. 

The price of the spread which is long April and short May will be larger if there is a cold winter in the 

United States, all else being equal. This is because the amount of natural gas in storage will be drawn 

down to heat building and for other uses, but by May the demand for natural gas will have subsided and 

the replenishing of storage of natural gas will be underway. Thus, the price of the spread which is long 

11
 
 

 

 

 

 

 

 

 

 

 

 

 

year closer to expiration because it appears that it would have been cheaper to trade out of a 

position directly with an outright contract. 

6. APPLICATION: INITIAL MARGIN SURCHARGE 

Derivative clearing organizations (DCOs)21 require clearing members22 and futures 

commission merchants (FCMs)23 to post margin to limit exposure to potential losses from 

defaults. In calculating initial margin,24 DCOs consider historical price movements of the 

futures price, but this is not their only consideration. DCOs and FCMs may require an additional 

surcharge of initial margin for illiquid futures contracts because a trader who wishes to unwind a 

position may induce an impact on the market price;25 That is, the market price of the futures 

April and short May during a cold winter will be high because natural gas is under higher demand than 

during a mild winter. 

21 DCOs clear financial contracts by becoming the counterparty to a trade through a process called 

novation. They mitigate their credit loss exposure by having their counterparties (clearing members) post 

collateral to them called margin. 

22 A clearing member may carry positions on behalf of itself or others. A position for “itself” generally 

means a position in a “house account.” And “others” includes clearing member’s customers –that is, each 

customer origin, who may be (1) customers of the clearing member’s FCM, or (2) customers of another 

FCM who is not a clearing member. See the definition of clearing member in CFTC regulation 1.3(c) and 

more generally, CFTC regulation 39.13 for more details. DCOs require clearing members to post margin 

for open positions to limit exposure to potential losses from defaults its clearing members. See CFTC 

regulation 39.13(f). 

23 Generally, a customer has no direct relationship with a DCO. An FCM intermediates contracts between 

the DCO and its customers and thereby guarantee the performance of its customers. 

24 Many FCMs are clearing members. Initial margin serves as the first source of collateral in absorbing a 

trader’s losses. Initial margin is posted by the clearing member to the DCO to protect against adverse 

price movements in a customer’s portfolio. In addition, FCMs may collect extra initial margin from its 

customers which it not required to post to the DCO. 

25 See CFTC Regulation 39.13(g)(13). “A derivatives clearing organization shall apply appropriate 

limitations or charges on the concentration of assets posted as initial margin, as necessary, in order to 

ensure its ability to liquidate such assets quickly with minimal adverse price effects, and shall evaluate the 

appropriateness of any such concentration limits or charges, on at least a monthly basis.” 

At a minimum, FCMs charge the amount of initial margin required by the relevant DCO. An FCM may 

impose an initial margin surcharge for reasons other than an illiquid contract. 

12
 
 

 

 

 

 

 

 

 

 

 

 

 

 

contracts moves against the trader due to a lack of liquidity. This illiquidity makes it more costly 

to offload a positon. 

DCOs and FCMs may use a bid-ask spread at the close of trading for a contract as a 

transaction cost assessment of offloading a position, that is, a liquidity surcharge.26 For a 

particular contract month, a liquidity surcharge might be estimated by:

27 

(bid-ask spread) * (Quantity to offload). 

This paper offers an alternative to the bid-ask spread; namely:

28 

LLLLdd * (Quantity to offload). 

These estimates of the cost of liquidation are independent of the correlation in the positions in 

the underlying portfolio.29 

26 See https://www.theice.com/publicdocs/clear_credit/ICE_CDS_Margin_Calculator_Presentation.pdf. 

27 A DCO might seek to port healthy customers with sufficient initial margin to protect the DCO to a 

healthy FCM without hedging their positions. Nevertheless, a DCO would likely approximately hedge, 

use liquid contracts but allow some residual basis risk, a defaulted “house account” or a defaulted FCM’s 

customer’s position. By doing so, the DCO would have more time to offload positons, since there is less 

price risk in the approximately hedged positions. Engaging in additional hedging will increase the 

transaction costs for a DCO beyond pure price impact costs, however. 

28 LLLLdd may be modified in various ways. For instance, a DCO might use the 90th percentile of LLLLdd over a 

relevant historical time interval to compute a liquidity surcharge for a related contract month. 

29 A trader might be able to offload a more balanced portfolio more slowly, and with potentially a lower 

price impact, because a balanced portfolio may have less price risk associated with it. Moreover, it’s 

likely to be more costly to offload a larger position, all else being equal, but the liquidity assessments 

discussed in this paper make no adjustments for the size of the underlying portfolio. If the quantity to be 

offloaded is a large percentage of average daily trading volume, then the price impact may be super-linear 

in quantity to offload and greater than these estimates. For instance, Robert Taylor of CME states 

"Typical value-at-risk (“VaR”) models scale linearly with portfolio size, however, it is well-known that 

the cost of liquidation increases super-linearly with size. CCP’s models, therefore, are required to apply a 

form of additional margins on large portfolios of even the most liquid products, and also during times of 

market crisis which would require significantly higher collateral." on page 5 of his comment letter dated 

December 2, 2014 with respect to the margin for uncleared swaps proposed rulemaking. 

13
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

There are two basic types of margin: variation and initial. Variation margin resets a 

customer’s trading losses or gains on their portfolio to zero. Variation margin is posted to settle 

up using the current prices, often closing prices, for positions. This settling up occurs after the 

close of the trading on the exchange. There can also be calls for variation margin by a DCO 

during the trading day if there are extreme price movements, but these events are infrequent. 

Initial margin is the amount of margin required by a DCO and any additional collateral required 

to be held at an FCM30 that is posted by the customer to insure against most adverse future price 

movements affecting a participant’s positions. A DCO must use at least a 99% confidence 

interval31 to cover adverse price movements in the underlying futures contracts over the margin 

period of risk.32 For a futures contract, the margin period of risk is often one trading day. If a 

contract is more illiquid, however, the appropriate minimum liquidation time for the margin 

period of risk may be longer than one day, because it may take longer to offload a participant’s 

The author leaves the super-linear modeling to future research. Such estimates are complicated by the use 

of spread transactions to transform positions into potentially more liquid outright positions and the 

subsequently exit out of the more liquid outright contracts. 

30 A FCM might demand additional initial margin, because the FCM wants to protect itself from default 

by its customers, because an FCM guarantees the performance of its customers to the DCO. Further, a 

customer may desire to have extra margin at an FCM. Extra margin allows a customer to respond more 

easily to calls for additional margin as conditions change over time – especially if it is relatively costly or 

inconvenient to transfer collateral to the FCM through wire transfer or automated clearing house 

transaction. 

31 The actual coverage of the initial margin must meet an established confidence level of at least 99 

percent, based on data from an appropriate historic time period, that is, an ex post time period. See, 

CFTC Regulation 39.13(g)(2). See CFTC Regulation 39.13(g)(2). For instance, on page 2 of a 

commenter letter dated December 2, 2014, Robert Taylor of CME states “CME calibrates its initial 

margin requirements for its over-the-counter (“OTC”) interest rate swaps using a 99.7% confidence level 

sampling to meet a 99% coverage standard.” 

32 Regarding spread and portfolio margins, a DCO may allow reductions in initial margin requirements 

for related positions if the price risks are significantly and reliably correlated. See CFTC Regulation 

39.13(g)(4). This paper discusses cross-margining benefits with holding offsetting contracts in different 

calendar months for the same commodity. 

14
 
 

 

 

 

 

 

 

position, especially to avoid a significant price impact if a large amount of open interest needs to 

be liquidated.33 

The types of assets posted as initial margin need not be cash, but may be other high 

quality instruments such as U.S. Treasury and high-grade corporate debt that a DCO or FCM has 

deemed acceptable. See CFTC Regulation 39.13(g)(10). A DCO may apply a haircut to highgrade corporate debt (for instance, a 5% hair cut would only count 95% of the current market 

value of a debt instrument towards initial margin), because it is less likely to retain its value and 

ability to be converted into cash in times of market stress, in comparison to a U.S. Treasury 

security. See CFTC Regulation 39.13(g)(12). 

Initial margin can be a misnomer in practice. That is because many practitioners and this 

paper use the term not just for the amount of margin that is initially required to be placed at the 

DCO and FCM, but also for the amount of margin that is required to be maintained at the DCO 

and FCM, sometimes called maintenance margin. The amount of initial margin required may 

also increase or decrease if the volatility of the underlying contracts increases or decreases, 

respectively, as this will likely affect the confidence interval over the look back period used to 

compute the confidence interval. 

Cross-margining benefits should substantially reduce the initial margin required of a 

customer’s portfolio that takes offsetting positions in different calendar months in the same 

33 Assessing the liquidity in a contract may also be helpful to an exchange in setting and in determining 

whether to grant an exemption to one of its position limits. An exchange would likely want to deter a 

market participant from trading in a manner that causes sudden or unreasonable price impacts on a 

contract market; such price impacts may cause financial harm to market participants, or even reputational 

risk or economic disadvantage to the exchange. In such circumstances, an exchange would likely elect 

not to grant an exemption or to instruct a market participant to establish or liquidate his or her desired 

position gradually, in an orderly manner. 

15
 
 

 

 

 

 

 

 

 

 

 

 

 

commodity relative to a stand-alone portfolio containing positions on the same side of the market 

in each contract month. In the offsetting case, the portfolio is exposed to the basis risk between 

the two calendar contracts but not the price risk of the commodity overall. For instance, the 

price movements of a relevant spread position tend to be substantially less than the daily price 

movements of a particular contract month. Consequently, an offsetting spread position would 

likely require holding substantially less initial margin than stand-alone portfolios.34 

A DCO may face a trade-off when imposing a liquidity surcharge. This is because a 

futures exchange tends to be vertically integrated with its DCO. Since requiring more margin 

increases the cost of trading, a DCO would prefer not to reduce the revenue of its exchange; 

however, a DCO would also prefer to have more initial margin posted to protect its clearing 

members, the default fund, and ultimately itself from defaulted positions. 

A position defaulted to a DCO35 might be liquidated by an auction where the clearing 

members of the DCO have an affirmative obligation to bid to assume the defaulted positions. 

The ability to auction defaulted position mitigates to some extent liquidity issues for DCOs, but 

the ability to auction does not completely eliminate price concession losses to a DCO. 

As the first bearer of losses, a customer needs to be aware of potential liquidity cost 

losses from having his or her positions offloaded at a substantial discount and might elect to 

maintain extra margin, prophylactically. FCMs, who guarantee customer positions and bear 

34 This may be one reason why market makers may be willing to make markets in spreads farther out the 

curve than in outright contracts. Market maker might not have to post as much margin when its 

proprietary portfolio does not net out to zero, because the portfolio is substantially hedged by each leg of 

a spread being offset by one of the other legs in a spread transaction. 

35 For a position to be defaulted to a DCO, a customer or house account, a customer’s or house account’s 

FCM, and the corresponding clearing member (if the clearing member is different than the FCM) would 

all have had to default. 

16
 
 

 

 

 

 

 

 

 

 

 

 

losses after a customer defaults and who may execute trades in order to reduce a customer’s 

position, may also seek extra initial margin from customers. This extra margin protects their 

customers and the FCM itself from price concession trading losses as well as other loss 

exposures from the customer to the FCM. 

6. CONCLUSIONS 

The liquidity costs were generally less than 1.0% of the contract price for NYMEX’s 

December 2016 CL, NG, HO, and RB. The low liquidity cost was anticipated close to expiration 

because these contracts are some of the oldest and most established futures contracts, but 

liquidity costs remained low far out the curve, too. 

The computation for CL suggests that a trader could have accessed even better liquidity 

very far out the curve by first engaging in a December 2015-to-December 2016 spread 

transaction and then trading out of the new position with an outright December 2015 transaction. 

This result, however, failed to hold true for the other three energy contracts, because either the 

December-to-December spread transactions were illiquid or because there was not a substantial 

liquidity advantage in executing an outright transaction in the December 2015 versus the 

December 2016 contract. 

17
 
 

 

 

 

 

7. GRAPHS 

Open Interest versus Days to Expiration December 2016 CL 

When first listed by NYMEX, the December crude oil contract had nine years to 

expiration. As is typical for a futures contract, open interest builds slowly. Open interest 

increased drastically in the months close to expiration before declining sharply just before the 

spot month when exchange position limits in the physical-delivery contract restrict speculative 

positions. This suggests that there were many market participants that wanted financial exposure 

to crude oil, but did not want to make or take actual delivery of the underlying commodity. 

NYMEX provided the open interest data to the CFTC. 

18
 
 

 

Trading Volume without the First Trade against Days to Expiration for December 2016 CL 

Note: The CFTC has only stored transaction data back until 2011. 

The shape of the trading volume graph is similar to the open interest graph but is more 

jagged. It is more peaked near the expiration of the contract, too. 

19
 
 

 

 

 

 

 

 

Liquidation Liquidity versus Days to Expiration for CL December 2016 

Note: The CFTC has stored the transaction data only back to 2011. 

The liquidity for December 2016 CL varies from day to day. The tick size is $0.01 per 

barrel with one contract unit being 1,000 barrels. The block size is 50 contracts for the outright 

and 5 for the year-to-year spread. LLLLdd equal to 0.2 suggests a $200 price impact to trade one 

contract. At $50 per barrel, one long futures contract would sell for $50,000. $200/$50,000 is 

0.4%. It appears that liquidity is not appreciably worse -- even appreciably better -- far out the 

curve even though open interest and trading volumes are substantially less there. 

20
 
 

 

 

 

LL with LLR (using the last trade) against Days to Expiration for CL December 2016 

This graph displays LL with the more sophisticated proxy for the current market price 

with LLR which employs the last price as a proxy for the current market The more sophisticated 

proxy reduces some of the overestimate of the liquidity costs that is due to stale prices. This is 

especially true far out the curve, where the contract is assessed to be substantially more liquid. 

The p-value for the two-sample t-test with unequal variances is 3.42E-05. This p-value gives 

strong evidence to the alternative hypothesis that the distribution of LL is different than LLR. 

21
 
 

 

 

 

 

 

AAdd with LLLLdd against Days to Expiration CL December 2016 

As discussed above, the author prefers LLLLdd over AAdd for theoretical reasons. Even 

though AAdd and LLLLdd assess differently, they are appear to be qualitatively similar. The p-value 

for the two-sample t-test with unequal variance is 0.077227. Given the large sample sizes of the 

non-missing observations, 1249, the p-value gives weak evidence for the alternative hypothesis 

that the two samples are different. For instance, at an alpha =0.05 level, we fail to reject the null 

hypothesis that the two samples are the same. 

22
 
 

 

 

 

 

 

 

 

 

 

 

 

Outright Liquidity for December 2016 with December 2015-2016 December Spread plus 2015 

Outright Liquidity for CL 

The LL of CL December 2016, LLO, tends to be below LLA, the LL of the previous 

calendar year outright plus the LLR of the December 2015 / December2016 calendar spread, 

except for, generally, far out the curve ( > 1600 days to expiration) and when the December 2015 

contract was near expiration ( 365 < days to expiration < 430 for the December 2016 contract). 

The graphs suggests that a market participant might have been able to offload a portion of a 

trader’s position more cheaply with a December 2016-2015 spread and outright for December 

2015 instead of a straightforward December 2016 outright far out the curve. In the energy 

contracts examined in this paper, crude oil is the only contract that exhibits this behavior. There 

were a substantial number of traders who got exposure farther out the curve by using spread 

transactions to roll their position. 

23
 
 

 

 

Open Interest versus Days to Expiration for December 2016 NG 

The natural gas contract had a nine year time to expiration when it was first listed by 

NYMEX. Open interest grew more slowly for natural gas, but it also follows the same typical 

pattern common to all the energy contracts in this paper. 

24
 
Trading Volume without the first trade against Days to Expiration for NG 2016 

Note: The CFTC has stored the transaction data only back to 2011. 

The shape of the trading volume graph is similar to the open interest graph, but slightly 

more peaked near the expiration of the contract. The lack of trading volume in the early years of 

the contract makes it more difficult to compute a reliable liquidity assessment based on 

transacted prices. 

25
 
 

 

Liquidation Liquidity versus Days to Expiration for December 2016 NG 

Note: The CFTC has stored the transaction data only back to 2011. 

Although natural gas had less open interest as compared to crude oil, the contract had 

similar liquidity in outright trading. One contract is 10,000 million British Thermal Units 

(mmBtu). The tick size is $0.001 per mmBtu. The block size is 50 contracts for the outright and 

15 contracts for the year-to-year spread. With LLLLdd equal to 0.01 the price impact is suggested be 

$100. At a price of $3.00 per mmBtu, one contract would sell for $30,000. $100/30,000 is 

approximately 0.333%. 

26
 
 

 

 

 

LL with LLR (using the last trade) against Days to Expiration for 2016 NG 

This graph displays LL with the more sophisticated proxy for the current market price 

with LLR which employs the last price as a proxy for the current market. The more 

sophisticated proxy reduces some of the overestimate of the liquidity costs that is due to stale 

prices. This is especially true far out the curve, where the contract is assessed to be substantially 

more liquid. The p-value for the two-sample t-test with unequal variances is 0.00116. With 

sample sizes of 595 for non-missing values, this p-value gives strong evidence to the alternative 

hypothesis that the distribution of LL is different than LLR. 

27
 
 

 

 

 

AAdd and LLLLdd against Days to Expiration for December 2016 NG 

As discussed above, the author prefers LLLLdd over AAdd for theoretical reasons. Even 

though AAdd and LLLLdd assess differently, they appear to be qualitatively similar. The p-value for 

the two-sample t-test with unequal variance is 0.080472. Given the large sample sizes of the 

non-missing observations, 595, remember that we need two transactions in the contract to 

compute the liquidity assessments, the p-value gives weak evidence for the alternative 

hypothesis that the two samples are different. For instance, at an alpha =0.05 level, we fail to 

reject the null hypothesis that the two samples are the same. 

28
 
 

Outright Liquidity for December 2016 with December 2015-2016 December Spread plus 2015 

Outright Liquidity for NG 

Generally, the LL of NG December 2016, LLO, tends to be below LLA, the LL of the 

previous calendar year outright plus the LLR of the December 2015 / December 2016 calendar 

spread. The graphs suggests that a market participant would not have been able to offload a 

portion of a trader’s position more cheaply with a December 2016 / 2015 spread and outright for 

December 2015 instead of a straightforward December 2016 outright. 

29
 
 

 

 

Open Interest versus Days to Expiration for December 2016 HO 

The diesel contract had less open interest compared to CL and NG, but it was still 

substantial. The open interest of this contract peeked earlier than just before the spot month. 

NYMEX lists the diesel contract for trading forward four years and one month until expiration. 

30
 
 

 

Trading Volume without the first trade against Days to Expiration for HO 2016 

The shape of the trading volume graph is similar to the open interest graph. As with the 

open interest graph, the trading volume peaks earlier than just before the spot month. 

Consequently, the near-to-expiration contract month was chosen to be one month later in an 

attempt to capture, approximately, the highest volume. 

31
 
 

 

Liquidation Liquidity versus Days to Expiration for December 2016 HO 

The diesel contract was liquid in the outright contract. The tick size is $0.0001. One 

contract is 42,000 gallons or 1,000 US barrels. The block size is 25 contracts for the outright and 

10 for the December-to-December spread. With LLLLddequal to 0.001 the price impact is suggested 

to be $420. At a price of $1.65 per gallon, one contract would sell for $69,300. $420/69,300 is 

approximately 0.606%. 

32
 
 

 

 

 

 

LL with LLR (using the last trade) against Days to Expiration for 2016 HO 

This graph displays LL with the more sophisticated proxy for the current market 

price with LLR which employs the last price as a proxy for the current market. The p-value for 

the two-sample t-test with unequal variances is 0.334751. With sample size of 519 for nonmissing values, this p-value gives little evidence for the alternative hypothesis that the 

distribution of LL is different than LLR. For this contract, updating prices with the more 

sophisticated proxy had less influence than with the other contracts. 

33
 
 

 

 

 

 

AAdd and LLLLdd against Days to Expiration for December 2016 HO 

As discussed above, the author prefers LLLLdd over AAdd for theoretical reasons. Even 

though AAdd and LLLLdd assess differently, they appear to be qualitatively similar. The p-value for 

the two-sample t-test with unequal variance is 0.34512. Given the large sample size of the nonmissing observations, 519, remember that we need two transactions in the contract to compute 

the liquidity assessments, the p-value gives little evidence for the alternative hypothesis that the 

two samples are different. For instance, at an alpha =0.05 level, we fail to reject the null 

hypothesis that the two samples are the same. 

34
 
 

 

Outright Liquidity for December 2016 with 2015/2016 December Spread plus 2015 Outright 

Liquidity HO 

As the red graph is predominately above the blue graph, this suggests that a trader would 

have done better to exit a position in the December 2016 directly with an outright trade than first 

using a December 2015/2016 spread and exiting out with a December 2015 outright. 

35
 
 

Open Interest versus Days to Expiration for December 2016 RB 

The final contract considered is RBOB gasoline. NYMEX lists the contract for three 

years. Open interest follows the typical pattern for futures contracts except that open interest 

peeked sooner and declined before the prompt month. 

36
 
 

Trading Volume without the first trade against Days to Expiration for RB 2016 

The shape of the trading volume graph is similar to the open interest graph. As with the 

open interest graph, the trading volume peaks earlier than just before the spot month. 

Consequently, the near-to-expiration contract month was chosen to be one month later in an 

attempt to capture, approximately, the highest volume. 

37
 
 

 

Liquidation Liquidity versus Days to Expiration for December 2016 RB 

One contract is 42,000 gallons. The tick size is $0.0001. The block size is 25 contracts 

for the outright and the author presumes it is 10 for the year-to-year spread, but could not find 

that information explicitly on the CME’s web page. With LLLLdd equal to 0.01, a price impact of 

$420 is suggested. At a price of $1.55 per gallon, one contract would sell for $65,100. 

$420/$65,100 is approximately 0.645%. 

38
 
 

 

 

 

LL with LLR (using the last trade) against Days to Expiration for 2016 RB 

This graph displays LL with the more sophisticated proxy for the current market price 

with LLR which employs the last price as a proxy for the current market. The p-value for the 

two-sample t-test with unequal variances is 0.223258. With sample size of 456 for non-missing 

values, this p-value gives weak evidence for the alternative hypothesis that the distribution of LL 

is different than LLR. For this contract, updating prices with the more sophisticated proxy had 

less influence than with the CL and NG contracts. 

39
 
 

 

 

 

AAdd and LLLLdd against Days to Expiration for December 2016 RB 

As discussed above, the author prefers LLLLdd over AAdd for theoretical reasons. Even 

though AAdd and LLLLdd assess differently, they appear to be qualitatively similar. The p-value for 

the two-sample t-test with unequal variance is 0.376875. Given the large sample size of the nonmissing observations, 456, remember that we need two transactions in the contract to compute 

the liquidity assessments, the p-value gives little evidence for the alternative hypothesis that the 

two samples are different. For instance, at an alpha =0.05 level, we fail to reject the null 

hypothesis that the two samples are the same. 

40
 
 

Outright Liquidity for December 2016 with 2015/2016 December Spread plus 2015 Outright 

Liquidity RB 

The red graph is predominately above the blue graph suggesting that trading in the 

December-to-December spread and more prompt outright would have been more expensive than 

simply trading in the outright contract. 

41
 
 

 

 

 

 

8. REFERENCES 

Amihud, Y., (2002), Liquidity and Asset Prices, Journal of Financial Markets, 5, 31-56.
 

Fett, N., and Haynes, R. (2016), Liquidity in Selected Futures Contracts, CFTC White Paper.
 

Taylor, Robert, December 2, 2014, comment letter with respect to margin for uncleared swaps,
 

https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=60051&SearchText=.
 

CME (2016), Customer Gross Margining Technical Information Updated December 27, 2016, 

http://www.cmegroup.com/clearing/risk-management/files/CGMTechnicalInformation.pdf.
 

http://www.cmegroup.com/rulebook/NYMEX/1a/150.pdf.
 

http://www.cmegroup.com/rulebook/NYMEX/1a/191.pdf.
 

http://www.cmegroup.com/rulebook/NYMEX/2/200.pdf.
 

http://www.cmegroup.com/rulebook/NYMEX/2/220.pdfhttp://www.cmegroup.com/trading/ener
 

gy/crude-oil/light-sweet-crude_contract_specifications.html
 

http://www.cmegroup.com/trading/energy/natural-gas/natural-gas_contract_specifications.html
 

http://www.cmegroup.com/trading/energy/refined-products/heatingoil_contract_specifications.html
 

http://www.cmegroup.com/trading/energy/refined-products/rbobgasoline_contract_specifications.html
 

https://www.theice.com/publicdocs/clear_credit/ICE_CDS_Margin_Calculator_Presentation.pdf
 

Kervel, V., and Menkveld, A. (2016), High-Frequency Trading around Large Institutional 

Orders, Working paper. 

Kyle, A., Continuous Auctions and Insider Trading, Econometrica, 53(6), 1315-1335. 

Leon, C. (2012), Estimating the intraday liquidity risk of financial institutions: a Monte Carlo 

approach, Journal of Financial Market Infrastructures, 1(1), Fall, 75-107. 

Marshall, B., Nguyen, N., and Visaltanachoti, N. (2012), Commodity Liquidity Measurement 

and Transaction Costs, Review of Financial Studies, 25(2), 599-638. 

Perold, A. (1988), The Implementation Shortfall: Paper vs. Reality, Journal of Portfolio 

Management, 14(3), 4–9. 

42