Another Day, Another Collar: An Evaluation of the Effects

of NYSE Rule 80A on Trading Costs and Intermarket Arbitrage

James Overdahl and Henry McMillan * **

Risk Analysis Division *

Office of the Comptroller of the Currency

Washington, DC 20219

(202) 874-3917

Jim.Overdahl@occ.treas.gov

**Pension Investments

 Pacific Mutual Life Insurance Company

Newport Beach, CA 92660

(714) 640-3320

Economics Working Paper 97-8

May 1997
Another Day, Another Collar: An Evaluation of the Effects 

of NYSE Rule 80A on Trading Costs and Intermarket Arbitrage

Economics Working Paper 97-8

May 1997

ABSTRACT

In 1990, the NYSE amended its Rule 80A to restrict stock index arbitrage on days of large price

movements. We design empirical tests to evaluate the impact of Rule 80A on trading costs and

intermarket arbitrage. We find that Rule 80A significantly curtails--or “collars”-- index arbitrage

activity. Despite the significant curtailment of index arbitrage activity, the cash and futures markets

remain linked. Pricing discrepancies between the markets are simply eliminated less quickly. Our

results are consistent with the hypothesis that information is conveyed from one market to the other

by means other than formal arbitrage. We also find that trading costs in the stock market, as

measured by the average bid-ask spread for S&P 500 stocks, do not change following the triggering

of Rule 80A, in spite of the binding constraint on index arbitrage volume. Overall, Rule 80A

appears to have had little impact on trading costs and intermarket arbitrage despite significant

curtailment of index arbitrage volume.

We have benefitted from the comments of Peter Locke, Lisa Meulbroek, Merton Miller, James Shapiro, Charles Trzcinka,

William Wilhelm, and the workshop participants at the SEC’s Office of Economic Analysis. We gratefully acknowledge

the computational assistance of Tom Dowling, Ian Lang, and Cory Anger. The views expressed herein are those of the

authors only and do not necessarily reflect the views of the Office of the Comptroller of the Currency or of Pacific Mutual.

Please address any comments to Jim Overdahl, Risk Analysis Division, Office of the Comptroller of the Currency,

Washington, DC 20219. Phone: (202) 874-3917. E-mail: jim.overdahl@occ.treas.gov.

Additional copies of this paper, or other Economics Working Papers, can be obtained from the Communications Division,

Office of the Comptroller of the Currency, 250 E Street, SW, Washington, DC, 20219. Telephone: 202-874-5043.

E-mail: kevin.satterfield@occ.treas.gov.
See The Report of the Presidential Task Force on Market Mechanisms, January, 1988; and Trading Analysis of October 1/

13 and 16, 1989, Division of Market Regulation, U.S. Securities and Exchange Commission, May 1990.

“Sell-plus” means that the order can be executed on a plus or zero-plus tick. A plus tick is a price above the price of 2/

the preceding sale. A zero-plus tick is a price equal to the preceding sale if the last transaction at a different price was at

a lower price. “Buy-minus” means that the order can be executed on a minus or zero-minus tick. A minus tick is a price

below the price of the preceding sale. A zero-minus tick is a price equal to the preceding sale if the last transaction at a

(continued...)

1

Another Day, Another Collar: An Evaluation of the Effects 

of NYSE Rule 80A on Trading Costs and Intermarket Arbitrage

Section 1. Introduction.

Since the advent of stock index futures in 1982, stock index arbitrage has been a

controversial trading practice because of its alleged role in contributing to stock market volatility.

Episodes of extreme market volatility in 1987 and 1989 heightened the controversy, leading many

policymakers and market professionals to request that the New York Stock Exchange (NYSE) take

steps to restrict the practice. In response to these requests, the NYSE amended its Rule 80A in 1/

July 1990 to restrict--or "collar"-- stock index arbitrage on days of large price movements. These

restrictions were implemented for a one-year trial period and became permanent in 1991 after

formal approval by the United States Securities and Exchange Commission.

Since the rule’s adoption, its restrictions have been triggered, on average, more than twice

per month. Here is how it works: On days when the Dow Jones Industrial Average ("Dow")

declines by 50 points or more from the previous day's closing value, Rule 80A requires all index

arbitrage sell orders for stocks from the Standard and Poor's 500 Index ("S&P 500") to be entered

with the instruction "sell plus." Conversely, on days when the Dow advances by 50 points or more 2/
 (...continued) 2/

different price was at a higher price.

Exempt from Rule 80A are index arbitrage program trades for market-on-close orders for index options or index futures 3/

expirations.

2

from the previous day's closing value, the rule requires all index arbitrage buy orders for stocks from

the S&P 500 to be entered with the instruction "buy minus." The tick restrictions apply to all index

arbitrage orders in component S&P 500 stocks traded at the NYSE, regardless of how the orders are

routed to the specialist's post. The tick restrictions are removed at the end of the trading day, or 3/

sooner if the market rebounds to a level within 25 Dow points of the previous day's close.

Like the practice it was designed to curtail, Rule 80A has generated considerable

controversy. This controversy has featured many ad hoc assertions about the rule's alleged effects--

assertions that do not necessarily follow from any simple model of market microstructure. Rather

than addressing every claim that has been made in the public policy debate concerning the rule, we

focus our attention on claims that can be translated into testable propositions readily delivered by

models found in the literature on market microstructure. We empirically test propositions

concerning the effect of Rule 80A on: 1) the linkage of the stock market and the futures market; and

2) trading costs in the stock market. Focusing our attention on testable propositions means that we

choose not to consider other assertions, such as the one frequently made in the financial press that

Rule 80A has prevented market crashes, since such assertions cannot be restated as refutable

hypotheses derived from any recognized microstructure model. We consider market volatility, a

variable of particular interest in the public policy debate, to be one component of the

aforementioned trading costs.

In constructing our tests, we compare market behavior before and after the triggering of the
3

rule's tick restrictions. To isolate changes attributable to Rule 80A, we compare market behavior

on days when the rule was triggered to its behavior on days before the rule's adoption when Rule

80A would have been triggered had it been in place.

Our findings can be summarized as follows. When Rule 80A is triggered:

1. Index arbitrage volume falls significantly. There is a significant decrease in the dollar

volume of index arbitrage associated with the S&P 500 futures contract on the Chicago

Mercantile Exchange (CME). Sell-side and buy-side arbitrage is less than a third of what

would be expected relative to the control period. Agency arbitrage is more severely

constrained than principal index arbitrage. Sell-side and buy-side agency index arbitrage

associated with the S&P 500 futures contract is less than 7 percent of what would be

expected relative to the control period.

2. The cash and futures markets remain linked. Despite the sizable reduction in index

arbitrage activity when Rule 80A is in force, the markets remain linked. Pricing

discrepancies between the markets are simply eliminated less quickly than when index

arbitrage is not constrained.

3. Trading costs are not materially affected. Trading costs in the stock market, as

measured by bid-ask spreads, do not fall in spite of the binding constraint on index arbitrage

volume. Relative to the control group, both total trading volume (inversely related to the

spread) and short-term volatility (directly related to the spread) decline after Rule 80A is

triggered. The overall impact of these opposing forces on bid-ask spreads is ambiguous. 

These findings complement the evidence in three other studies of Rule 80A. The NYSE

Report (1991), completed at the request of the SEC, evaluates the performance of Rule 80A in the

nine months following its adoption. The NYSE's main conclusion, that the rule produced little

overall effect on the stock market, is consistent with our own findings despite differences in control

periods, sample periods, and statistical measures. Kuserk, Locke, and Sayers (1992) evaluate the

impact of Rule 80A on the S&P 500 futures market in the three months following the rule's

adoption. These authors conclude that "80A does not appear to be unduly constraining index

arbitrage" and that "no harm to the (futures) market making sector is found." To obtain their
For discussion of time of day effects see Amihud and Mendelson (1987), Ekman (1992), Gerety and Mulherin (1992), 4/

Harris (1986), Jain and Joh (1988), and Stoll and Whaley (1990).

4

conclusions, they compared the S&P 500 cash-futures basis on days when the tick restrictions were

with that basis during a control period when the tick restrictions were not in effect. Our conclusions

differ from the conclusions of these authors in that we find Rule 80A to significantly constrain index

arbitrage activity. We attribute the different findings to the different measures of index arbitrage

volume. We are able to observe index arbitrage volume directly whereas Kuserk et al. infer

arbitrage volume by observing basis behavior.

Like the NYSE report and Kuserk et al., Santoni and Liu (1993) look at the impact of the

rule in the months immediately following the rule's adoption. They find that intraday stock market

volatility (measured as unconditional variance of percentage price changes over one-minute

intervals) falls after the rule is triggered, whereas volatility increases around similar market moves

in their control sample. Our findings with respect to market volatility, which are included as part

of our analysis of trading costs, are consistent with this result.

In this paper we construct more powerful tests than those used in the three previous studies.

We examine a larger set of observations over a three-and-a-half year period. We also employ a

broader control group than in the previous studies. Finally, we segment our test and control samples

to account for known time-of-day effects in the prices of stocks and futures. Our tests are based 4/

on a detailed minute-by-minute (and in some cases trade-by-trade) analysis of 39 midday events

where Rule 80A was triggered. We find that our conclusions are not sensitive to variations in our

control group--even when we include observations from the days surrounding the 1987 market

crash.
5

Section 2. Theory and Testable Propositions.

2.1 Index Arbitrage and Market Linkage

We use the term "market linkage" to describe the degree to which prices in one financial

market reflect information contained in prices from related financial markets. Markets are linked

in part by the order flow generated by arbitrage trading. Miller (1992) has referred to this order

flow which serves to inform market makers about intermarket price discrepancies as "formal"

arbitrage to distinguish it from other market-linking mechanisms, such as good shopping by

knowledgeable investors, that do not involve arbitrage-generated order flow.

One issue appearing in the recent microstructure literature is the role that formal arbitrage

plays in linking markets. In one set of models, the market-linking role of formal index arbitrage is

critically important. For example, in Kumar and Seppi (1994), who extend the model of Kyle

(1984,1985) to include the specifics of index arbitrage, market-makers observe the net order flow

only in their own market and set prices conditional on that information. A testable proposition from

this type of model is that the arbitrage-curtailing effects of Rule 80A will impair the linkage of the

futures and the cash market.

In another set of models, the order flow generated by index arbitrage is not critical to the

linking of markets. An example of this type of model is that of Chowdry and Nanda (1991), who

extend the Kyle model to allow market makers to observe price information from markets other than

their own. In this type of model, a market-maker observing a sudden jump in the futures price does

not wait around for arbitrage order flow to arrive. The mere threat of arbitrage (e.g., after Rule

80A expires) causes the market maker to revise his quotes, thus keeping markets linked without any
6

formal arbitrage taking place. A testable proposition from this type of model is that Rule 80A will

not impair the linkage between the futures market and the stock market.

The same testable proposition emerges from Miller (1992) and Miller, Muthuswamy, and

Whaley (1994), who have suggested another reason why formal arbitrage may not be necessary to

keep markets linked. According to this argument, investors use one of two methods to adjust the

exposure of their portfolios--either effecting a single transaction in the futures markets or replicating

the index through multiple transactions in the cash market. Investors will choose the cheaper of the

two routes, taking into account not just the direct transaction costs but also any mispricing of the

futures market relative to its theoretically correct value as implied by the cost-of-carry relationship

between futures and cash prices. In short, according to this argument, good shopping by

knowledgeable investors keeps the markets linked without any formal arbitrage. 

2.2 Index Arbitrage and Trading Costs

One of the most controversial aspects of index arbitrage is its effect on the cost of marketmaking. In the microstructure literature, index arbitrage can affect the cost of market-making in two

ways. The first is purely institutional, resulting from differences between CME and NYSE rules

concerning price continuity. Specialists lose to index arbitragers by providing price continuity

whenever market moves are discontinuous. The arbitrager gains at the specialist’s expense by

selling stock to the specialist that both know is overvalued or buying stock from the specialist that

both know is undervalued.

Second, index arbitragers may have an informational advantage that creates an adverse

selection cost for the relatively less-informed market-makers. This cost can be seen most clearly
7

in the case of those who enter limit orders on the specialist's book. These market-makers commit

themselves to trade a stipulated number of shares at prices announced in advance. Arbitragers can

pick off obsolete resting limit orders before they are adjusted to reflect new information being

signaled by the futures market. If the volume of index arbitrage increases, the losses to writers of

limit orders will also increase. Miller (1992) has compared the costs that index arbitrage imposes

on market-makers to an excise tax on market liquidity that is collected by the arbitrager instead of

the government.

Kumar and Seppi (1994) explicitly model the effects of this type of informational advantage.

In their model, arbitragers observe the imperfectly correlated evolution of the various marketmakers' beliefs across different markets. Since market-makers in this model observe only

information contained in the order flow of their own market, their information lags behind that of

the arbitrager who sees information contained in the prices of other markets. A testable proposition

resulting from this model of market microstructure is that the trading costs of market-makers should

be lower when index arbitrage is curtailed, such as under Rule 80A, than they would be when index

arbitrage is not restricted. 

2.2.1 Index Arbitrage and Market Volatility

The market microstructure literature identifies short-term price volatility as an important

component of the bid-ask spread (see, for example, Stoll, 1989). Short-term volatility--to the extent

it is affected by index arbitrage order flow--serves as a potential transmission mechanism between

index arbitrage and trading costs as measured by the bid-ask spread. The effect of index arbitrage

on price volatility has been studied by Cuny and Stoughton (1992), who demonstrate that even when
Rule 80A was triggered an additional 39 times during the market open or close or on days in which the CME trading 5/

limits, or “circuit breakers,” were in effect. We define the first half hour of trading as the open, the last half hour as the

close, and the intervening period as the midday.

8

arbitragers have superior information about intermarket price discrepancies, the volatility of price

changes over time should be unaffected by index arbitrage. Empirical work consistent with this

view can be found in Harris et al. (1990). The results of these studies yield an additional testable

proposition concerning Rule 80A and trading costs: the volatility component of the bid-ask spread

should be unaffected by the triggering of Rule 80A.

Section 3. Data and Summary Statistics.

3.1 Days in the Sample.

Although Rule 80A is triggered by changes in the Dow, our analysis focuses on changes in

the S&P 500 because it is this index’s component stocks that are affected by the rule’s tick

restrictions. The S&P 500 index is not calibrated with the Dow, so 50 Dow points correspond to

a range, rather than a specific number, of S&P 500 index points. In our sample the S&P 500 cash

index had moved anywhere from 3.43 to 8.62 points from its previous close before Rule 80A was

triggered.

Panel A of table 1 lists our test sample of 39 midday events when Rule 80A was triggered

from August 1990 through December 1993. Table 1 also indicates the time that the trigger was 5/

hit and the total price change (from the previous day's close) in the S&P 500 futures contract and

cash index at that time. Panel B of table 1 identifies the 27 control days used in our tests. The

controls occurred on a set of days from October 1986 through July 1990 when the Dow moved 50

points from its previous close. These days would have triggered Rule 80A had it been in place at
Since the Dow was lower during the control period, 50 Dow points would be a larger percentage swing in the control 6/

period than in the test period. However, the rule has stayed with 50 points since its initial implementation and we believe

that specifying point changes rather than percentage changes is consistent with how the rule would have been administered

had it been in place during our control period.

In using midday observations we conform to the suggestion of Miller (1990) who argues that the real test of Rule 80A 7/

is when it is triggered in the middle of the day. We confine our attention to midday observations because including

opening or closing events would yield insufficient observations to perform meaningful “before” versus “after”

comparisons, that is, the event window would be significantly truncated on one side or the other. In addition, observations

from the market open are potentially corrupted by delayed openings for stocks.

Table 1 indicates that the futures contract could be close to its CME trading limit, or “circuit breaker,” before the cash 8/

market triggered Rule 80A. The CME circuit breaker is triggered by a 12-point movement in the nearby S&P 500 futures

contract. Indeed, the CME circuit breaker was triggered before Rule 80A on August 6, 1990. A ninety minute window

around the time when Rule 80A was triggered includes almost all of these circuit breaker events. Changes in the behavior

of cash or futures markets may be due to the circuit breaker or the anticipation of those circuit breakers.

Rule 80A was triggered twice on August 21, 1990. 9/

9

the time.6/

_______________________________________________

Table 1 Here.

_______________________________________________

To obtain a clean test of Rule 80A, the samples shown in table 1 have been culled from a

larger set of initial observations using the following selection criteria. First, events during 1988

were excluded from the control sample because the collar on the NYSE’s Designated Order

Turnaround system (DOT) was in effect at that time. Second, we exclude events within 30 minutes

of the open or the close. Third, we exclude days when "circuit breakers" on the S&P 500 futures 7/

contract of the CME were triggered. The CME has had circuit breakers in place for its S&P 500

futures contract since October 1988.8/

During our test period, Rule 80A was triggered on 68 occasions on 67 days. From our

9/

initial sample of 68 events, we use as the basis of our tests 39 instances in which Rule 80A was
The event window is truncated for events that occur within 90 minutes of the open or the close. For example, an event 10/

occurring at 10:30 a.m. would have only 60 one-minute intervals in the “before” sample. All sample windows have at

least 30 one-minute intervals observed on each side of the event trigger.

10

triggered in the midday, that is, after the first half hour of trading and before the last half hour.

3.2 Prices, Volume, and Bid-Ask Spreads.

Price and volume data come from several sources. Tick Data, Inc., provides tick-by-tick

price data for the S&P 500 futures contract using the official time and sales record of the CME.

They also provide data on the S&P 500 cash index and the Dow sampled at frequent, but irregular,

intervals of less than one minute. We calculate bid-ask spreads and trading volume for the S&P 500

cash index from the Securities Industry Automation Corporation records. We identify index

arbitrage transactions from NYSE records.

For the purposes of this study, we measure index arbitrage as the dollar value of all NYSE

stock transactions directly corresponding with the establishment or liquidation of S&P 500 futures

positions as recorded in the NYSE's program trading reports. These records distinguish between

trades that are for principal accounts (trades for the member firm's own account) and trades for

agency accounts (trades for a member firm's customer accounts). We record index arbitrage volume

in one-minute intervals for 90 minutes before and after the triggering of Rule 80A. We measure 10/

aggregate trading volume as the aggregate dollar value of all transactions in S&P 500 stocks listed

on the NYSE. These data are recorded in one-minute intervals for 90 minutes before and after the

triggering of Rule 80A. Daily dividends on the S&P 500 index are recorded from various issues of

the S&P 500 Information Bulletin.
The autocorrelation may be due to stale prices. The last reported trade for some securities in the index may have

11/

occurred several minutes earlier. Such prices would not be currently available for arbitragers. In contrast, the futures price

has no stale elements. As a result, the futures price will tend to lead the cash price when market prices trend in one

direction or another. See Harris (1986) and Miller, Muthuswamy, and Whaley (1994).

11

3.3 Event Time Plots.

Charts 1 and 2 display S&P 500 cash and futures price indexes respectively, recorded in

event time, for the 180 minutes surrounding the triggering of Rule 80A. We use these series in our

statistical tests. The index for each day is standardized to equal 100.0 when Rule 80A is triggered

in the test group or would have been triggered in the control group (that is, t=0). Both the test and

control samples are separated into up and down samples (which consist of days for which Rule 80A

restricted arbitrage buy and sell orders respectively). The daily index values are then aggregated

into an equally weighted index for the sample.

___________________________________________

Charts 1 and 2 Here

___________________________________________

Both charts show a close correspondence between the test and control samples. There appear

to be no significant differences in the pattern of cash returns between the control and test samples

within 30 minutes of the event. Over the 90- minute interval, the increases or decreases are about

.83 percent for all groups. The indexes continue down or up briefly after the 50 point move,

possibly because of the normal autocorrelation present in the index. The indexes are basically flat 11/

afterwards, however, as one would expect in efficient markets without a trend. Furthermore, these

returns are insignificantly different from zero over this 90-minute window.
12

Section 4. Tests.

4.1 Index Arbitrage Volume.

If Rule 80A’s tick restrictions increase the cost of completing the cash leg of an index

arbitrage trade, index arbitrage trading volume should decline. Table 2 displays summary statistics

for “restricted” index arbitrage volume, that is, index arbitrage programs subject to the tick

restrictions of Rule 80A, and t-statistics for testing the equality of mean values between the test and

control groups. The statistics are calculated separately for 50-point decreases (panel A) and

increases (panel B) in the Dow. The first row of each panel of the table reports index arbitrage

trading volume subject to Rule 80A’s restrictions (i.e., S&P 500 stock purchases when zero-downtick restrictions are imposed and S&P 500 stock sales when zero-up-tick restrictions are imposed),

aggregated separately for the 90 minutes before and the 90 minutes after the triggering of Rule 80A.

Positive values reflect purchases of S&P 500 component stocks and negative values reflect sales.

These figures are reported as averages over the number of Rule 80A events in each category.

__________________________________________

Table 2 Here.

__________________________________________

Total restricted arbitrage, reported in the first row of each panel, is partitioned by account

type in rows two and three. The second row of each panel displays restricted principal index

arbitrage volume, that is, index arbitrage conducted by an NYSE member firm for its own account.

The third row of each panel displays restricted agency index arbitrage, that is, index arbitrage
13

conducted for a member firm’s customer account. 

The observations displayed in table 2 are consistent with the hypothesis that Rule 80A is a

binding constraint on index arbitrage volume. Restricted index arbitrage volume (i.e., volume for

the test group) in the 90 minutes after a 50-point move in the Dow is lower than in the 90 minutes

before both in absolute terms and relative to index arbitrage volume in the control group. Panel A

shows that in the control group S&P 500 index arbitrage sell volume increased from about $100

million in the 90 minutes before a 50-point move in the Dow to $130 million in the 90 minutes

following. In the test group, restricted index arbitrage sell volume decreased from $124 million

before to $45 million after. This means that on down days, restricted index arbitrage volume after

the trigger was only 28 percent of what would be expected given the control period. 

Panel B of table 2 shows that on up days, restricted index arbitrage fell from $162 million

to $44 million in the test period but only fell from $133 million to $127 million in the control

period. This means that on up days, restricted index arbitrage volume after the trigger was only 28

percent of what we would have expected given the control period.

Both panels in table 2 tell the same story about the impact of Rule 80A index arbitrage

volume. Before 50 point Dow moves there is no statistically significant difference between mean

index arbitrage volume in the test and control groups. After 50 point Dow moves, mean volume in

the test group drops significantly relative to the control group. This observation is consistent with

the hypothesis that Rule 80A is a binding constraint on index arbitrage activity.

These observations are not consistent with the findings of Kuserk et al. (1992), who

conclude that “80A does not appear to be unduly constraining index arbitrage.” We attribute the

different findings to the different measures of index arbitrage volume. We are able to observe index
14

arbitrage volume directly whereas Kuserk et al. infer arbitrage volume by observing basis behavior.

Both principal and agency index arbitrage volume decline after Rule 80A is triggered,

although the biggest impact is on agency volume. In the 90 minutes after the triggering of Rule

80A, principal index arbitrage volume declines relative to the volume observed in the 90 minutes

before the triggering of the rule, both on down days and up days. These observations are reported

in the second row of panels A and B of table 2. On down days, principal index arbitrage volume

declines to 44 percent of what was observed before the trigger, a decline from $98 million to $43

million. On up days, principal index arbitrage volume declines to 33 percent of what was observed

before the trigger, a decline from $127 million to $42 million. In the control period, principal index

arbitrage was virtually unchanged surrounding 50-point moves.

Agency index arbitrage volume is almost entirely eliminated when Rule 80A is triggered,

both on up days and down days, and the decrease in volume is statistically significant (see the third

row of panels A and B of table 2). On down days, agency index arbitrage volume falls from an

average of $25 million to $2 million around the triggering of Rule 80A--a 93 percent decline in

dollar volume. This decline is striking when compared with the increase (from $34 million to $63

million) in agency index arbitrage during the control period around 50-point decreases in the Dow.

On up days, agency index arbitrage volume falls from $35 million to $600,000 around the

triggering of Rule 80A’s restrictions, a 98 percent decline in dollar volume. This decline in volume

is striking when compared with the control period’s modest decline (from $81 million to $77

million) around 50-point increases in the Dow.

The differing effects of Rule 80A on agency and principal index arbitrage volume may be

due to NYSE regulations that pre-dated Rule 80A. For example, the NYSE’s short-sale tick
)casht

' g(bet&1& c) % a(L))futuret% b(L))casht% gt

15

(1)

restriction (which pre-dates Rule 80A) is more likely to affect a large NYSE member firm than its

customer-- independent of any Rule 80A tick restrictions, because an NYSE member firm is more

likely than its customer to be a far-flung operation with many trading desks. Given that it is costly

to monitor compliance with the NYSE’s short-sale restrictions across all trading desks at all times,

these firms may have voluntarily submitted tick-sensitive orders to avoid violating short-sale

restrictions even before the adoption of Rule 80A. Sofianos (1993) presents evidence of such

behavior by some traders.

4.2 Testable Propositions Concerning the Effects of Rule 80A on Market Linkage.

Since the testable propositions concerning market linkage and index arbitrage discussed in

the previous section need to be made operational, we model the stochastic process linking cash and

futures prices as an error-correction mechanism. The intuition behind this specification is that the

persistence of basis error is a sign that markets are not closely linked. Our error-correction

specification for the S&P 500 is 

where the variable "cash" is the logarithm of the cash price index, "future" is the logarithm of the

futures price, and "be" is the logarithm of the basis error that itself is defined here as the futures

price divided by the fair value futures price. The constant term, “c,” shows whether the basis error

differs from zero. The coefficient “g” produces an estimate of the adjustment speed of the cash

index to lagged basis error. It is this coefficient that we are most concerned about in generating an

operational hypothesis to be tested. If the adjustment speed coefficient falls significantly after Rule
16

80A is triggered, then it can be argued that market linkage is impaired, i.e., that basis error persists

for a longer time. The lagged futures and cash price changes, measured here by the polynomials

a(L) and b(L), capture other dynamic factors in pricing. The operational null and alternative

hypotheses can be restated as:

H : g = g o before after

H : g Ö g A before after

To test whether Rule 80A affects market linkage, the sample for each event is split into pre50-point samples (t=-90,...,-1) and post-50-point samples (t=0,...,+90) for both the test and control

groups. Five lags are used on the cash and futures prices. Equation (1) is estimated for each day

containing sufficient observations in each sample to identify all coefficients.

We summarize the evidence on market linkage and the persistence of basis error in table 3.

The table lists the average estimated adjustment-speed coefficient (g), its average t-statistic, and the

number of events with significant adjustment-speed coefficients for the pre-event and post-event

samples. Finally, the table includes the F-statistic to test for structural stability in the entire equation

surrounding 50-point Dow moves. For conciseness, the coefficients for a(L) and b(L) are omitted

from the table.

______________________________________

Table 3 Here.

_______________________________________

Comparison of the estimated g coefficients reveals that the average estimated adjustment-speed

coefficient changes quantitatively in the test sample, but not in the control sample. For the sample

of all test events, the average ‘g’ coefficient drops from .131 to .073, indicating that price
An otherwise identical specification substitutes )future as the dependent variable. Then generalized least squares or 12/

t

an augmented vector auto regression can be used to estimate the two equations simultaneously to account for

contemporaneous correlation of the error components in the two equations. We present only the cash equation estimates

here. There is essentially no change in the estimates for the futures equation, either pre or post, control or test sample.

Also, we conducted Granger causality tests for the futures and cash markets. Using five-minute lags on this sample, the

estimates of causality were unchanged.

The critical value for the F-statistic at the five percent level of confidence is approximately 1.60 for these samples. 13/

17

discrepancies between the two markets are corrected less quickly after Rule 80A is triggered. In

contrast, for the sample of all control events, the average ‘g’ coefficient changes insignificantly from

.109 to .104. Similar results are reported for up moves and down moves when tested separately.

This evidence suggests that Rule 80A weakens the linkage between the markets, in that adjustment

toward equilibrium is slowed (i.e., basis error persists longer), but that the linkage is not broken.12/

 Our result--that market linkage is not broken but that the speed of adjustment is slower and that

basis error persists longer than when formal index arbitrage is not constrained--is consistent with

the “smart shopping” hypothesis of Miller (1992) and Miller, Muthuswamy, and Whaley (1994).

The F-statistics lead us to reject stability (at the 5 percent level) in 19 of 39 test events but

in only 6 of 27 control events. Thus, structural stability is rejected more frequently in the test

sample than in the control sample. The average F-statistic, while 2.04 for the test sample, is only

1.36 for the control sample and is consistent with the hypothesis that Rule 80A affects the stochastic

process linking basis error to cash prices. 

13/

4.3. Tests of the Effect of Rule 80A on Trading Costs.

4.3.1. Bid-Ask Spreads.

To run an operational test of the effect of Rule 80A on trading costs, we use the bid-ask
10,000 (

(P

ask & Pbid)

[(P

ask % Pbid)/2]

Minute-by-minute bid-ask spread data were incomplete or could not be recovered for 19 of the 39 test events.

14/

Although the missing observations reduce the number of observations, the omissions are random and should not

systematically affect our results.

18

spreads quoted by marke-makers as our summary measure. As Stoll (1989) has shown, changes in

the quoted bid-ask spread should reflect changes in trading costs. The operational null and

alternative hypotheses can be restated as:

Ho: B/A Spread before = B/A Spread after

H : B/A Spread Ö B/A Spread A before after

We compare bid-ask spreads in our test and control samples before and after 50 point Dow

moves. We calculate minute-by-minute spreads for each firm as: 14/

 We then form a “spread index” of S&P 500 firms by averaging the percentage bid-ask spreads

across these firms, giving equal weight to each NYSE-listed firm in the S&P 500 index.

Table 4 displays the average bid-ask spreads surrounding 50-point Dow moves. For down

days, the bid-ask spread increases both on days in the control sample and on days in the test sample.

In the control sample, the percentage bid-ask spread goes from 82.36 basis points to 87.65 when the

50-point mark is breached. In the test group, the percentage bid-ask spread rises from 96.33 basis

points to 100.27 after Rule 80A is triggered. In dollars, the average spread for the test group widens

4 cents per share on a stock worth $100 per share and that of the control group increases by 5 cents

per share. In terms of tick size, in order for the average change in the bid-ask spread to be worth

a sixteenth of a dollar, each share of stock would need to be worth approximately $160 at a time
19

when the average price of a NYSE share was approximately $34. Overall, on down days, the

evidence from average bid-ask spreads shows that on days Rule 80A was triggered there was little

change in spreads either in absolute terms or relative to the control group. 

___________________________________________________

Table 4 Here.

___________________________________________________

 For up days, table 4 shows that spreads increase from 73.95 basis points to 75.71 in the

control group around 50-point Dow moves. In the test group, the average percentage bid-ask spread

falls from 94.13 basis points to 93.27 as Rule 80A is triggered. In dollars, the average spread for

the test group falls less than a penny per share on a $100 per share stock. In terms of tick size, in

order for the average change in the bid-ask spread to be worth a sixteenth of a dollar, each share of

stock would need to be worth approximately $700. Overall, on up days, the evidence shows that

Rule 80A has had little effect on bid-ask spreads either in absolute terms or relative to the control

group. 

Summary statistics may not tell the entire story of specialist behavior when confronted with

large moves in the Dow. Specialists adjust spreads to account for volatility and volume, and the

percentage spread may reflect the index level if the minimum tick is binding on the absolute spread.

To account for these factors, a multivariate regression analysis is employed. We use the average

spread as the dependent variable in a cross-sectional regression. We define LEVEL to be the

average cash index value in the 30 minutes before or after a 50-point event. We define VOLUME

to be the average dollar volume of the S&P 500 stocks during the 30 minutes before or after the
20

event. The standard deviation of minute-by-minute index returns for the 30 minutes before and after

the event is defined as SIGMA. To distinguish between observations generated by the test sample

and those generated by the control sample, we define the dummy variable TEST to equal one if the

observed spread is from the test sample and zero if it is from the control sample. To distinguish

between observations before and after a 50-point Dow move, we define the dummy variable POST

to be one if the spread is generated from the portion of the sample observed after the 50-point move,

and zero if the spread is generated from the pre-50 point portion of the sample. Finally, we define

the dummy variable POSTTEST to be one if the observation follows a 50-point Dow move and is

in the test sample.

A semi-logarithmic specification is estimated. The point estimates for this equation (tstatistics in parentheses) are: 

ln(SPREAD)= 11.25 - 1.21ln(LEVEL) +.20ln(VOLUME) + .028(SIGMA)

(21.0) (-12.7) (0.6) (2.8)

+ .297(TEST) + .019(POST) - .008(POSTTEST) R =.844 2

(9.8) (0.6) (-0.2)

The dummy variable TEST is highly significant, indicating that bid-ask spreads are about 30 percent

larger during the test period for reasons not explained in the regression. However, neither POST

nor POSTTEST is significant. This insignificance indicates that spreads are no larger after the 50-

point Dow move in both the control and test samples after controlling for the effects of volume,

volatility, and index level. The coefficient for VOLUME is positive but insignificant indicating no

independent effect on spreads. High volume is generally associated with small bid-ask spreads.
We do not attempt to discriminate between inventory management and asymmetric information components of the bid- 15/

ask spread (Glosten and Harris 1988, and Stoll 1989). Nor do we consider the issue of quote revision (Hasbrouck 1988).

21

However, if this volume is largely unanticipated one-sided volume, the capacity of marketmakers

can be strained and they may respond by widening their spreads. Overall, this evidence suggests 15/

that rule 80A has had little effect on how specialists set spreads. 

4.3.2 Market Volatility.

Table 5 presents summary and test statistics used to compare volatility in periods before and

after the triggering of Rule 80A. This comparison is done for both the test group and the control

group. The table presents, for down days and up days respectively, the unconditional standard

deviation of minute-by-minute returns (expressed in percentage basis points) from the S&P 500 cash

index and the nearby S&P 500 futures contract. We use minute-by-minute observations to construct

this test. 

______________________________________

Table 5 Here.

______________________________________

The operational hypothesis and its alternative can be restated as:

Fbefore = Fafter

Fbefore Ö Fafter

The test results displayed in Table 5 show that before to the rule's adoption, that is, for the

control group, cash index volatility increased after a 50-point Dow move. On down days volatility
22

rose from 3.05 percentage basis points to 3.90, and on up days, volatility rose from 2.71 percentage

basis points to 2.81. However after the rule's adoption, that is, for the test group, cash index

volatility declined after a triggering move in the Dow. On down days, volatility decreased from

3.55 percentage basis points to 2.34. On up days, volatility decreased from 2.14 percentage basis

points to 1.84. For the sample of down days, the observed differences in volatility before and after

a triggering event is significant for both the control group and for the test group. These results are

consistent with the intraday results reported by Santoni and Liu (1993).

In contrast, futures volatility increases slightly after triggering events following the adoption

of the rule. On down days, volatility rose from 6.48 percentage basis points to 7.64. On up days,

volatility rose from 4.30 percentage basis points to 4.63. These before and after changes are not

statistically significant, however. Before and after changes in the futures control group are also

statistically insignificant. Overall, the evidence presented in Table 5 is consistent with the

hypothesis that while Rule 80A is associated with a reduction in cash market volatility, it does not

affect futures market volatility. 

The impact of Rule 80A on short-term cash market volatility can be summarized by

normalizing the results of the test group with the results of the control group. Relative to the control

group, the triggering of Rule 80A is associated with a significant decline in minute-by-minute cash

market volatility. On down days, relative to the control group, minute-by-minute volatility declines

by approximately 50 percent after the triggering of Rule 80A. On up days, the decline in volatility

is nearly 20 percent relative to the control group.

This decrease in measured volatility is associated with a change in the autocorrelation

process of the return series. Consistent with our determination that basis error persists longer when
23

Rule 80A is in effect, we find that cash return series displays greater positive autocorrelation after

Rule 80A is triggered. For both test groups, a typical series of returns displays first-order

autocorrelation before the triggering of the rule, but displays first- and second- order autocorrelation

after the rule is triggered. The more positively autocorrelated series translates into a less volatile

return series.

A decrease in market volatility, all else being equal, should result in a reduction in trading

costs as measured by bid-ask spreads. However, all else does not remain equal. Overall S&P 500

trading volume declines significantly following the triggering of Rule 80A. Relative to the control

group (in which trading volume was largely unaffected by the breaching of the 50-point threshold),

trading volume of all types declines by nearly 30 percent on down days and 7 percent on up days.

The result is that, relative to the control group, both total trading volume (inversely related to the

spread) and short-term volatility (directly related to the spread) decline after Rule 80A is triggered.

The overall impact of these opposing forces on bid-ask spreads is inconclusive. 

Our measure of the volatility component of the bid-ask may mask the true level of volatility

as perceived by the specialist. The observed minute-by-minute price adjustment process may indeed

be slower and smoother as the volume of one-sided index arbitrage order flow is reduced. It follows

that the specialist does not lose as much to the arbitrager by providing price continuity. But

arbitrage order flow does not have to arrive to affect the way the specialist sets the bid-ask spread.

The mere threat of one-sided arbitrage order flow can keep spreads from narrowing in spite of the

reduction in observed volatility in the price series immediately after Rule 80A is triggered. Minuteby-minute volatility may not tell the whole story about the price adjustment process because it does

not account for information that both the arbitrager and the specialist possess about where cash
24

prices are heading relative to futures prices.

Section 5. Concluding Remarks.

The 1990 amendment of NYSE Rule 80A, like the practice of stock index arbitrage it was

designed to curtail, has become a controversial feature of U.S. financial markets. We find that Rule

80A significantly curtails--or “collars”-- index arbitrage activity. Sell-side and buy-side arbitrage

subject to the rule’s restrictions is about one third of what would be expected given the control

period. Agency arbitrage is more severely constrained than principal index arbitrage. Sell-side and

buy-side agency index arbitrage associated with the S&P 500 futures contract falls more than 90

percent relative to the control period. These results, consistent with the NYSE report (1991), are

not consistent with the findings of Kuserk et al (1992) who conclude that “80A does not appear

to be unduly constraining index arbitrage.” We attribute the different findings to the different

measures of index arbitrage volume. We are able to directly observe index arbitrage volume

whereas Kuserk et al. infer arbitrage volume by observing basis behavior.

Despite the significant curtailment of index arbitrage activity, the cash and futures markets

remain linked. Our evidence suggests that Rule 80A weakens the linkage between cash and futures

markets in that pricing discrepancies between the markets are eliminated less quickly. Our results

are consistent with the hypothesis that information is conveyed from one market to the other by

means other than formal arbitrage. Specialist quote revision in anticipation of one-sided order flow

and smart shopping by stock traders can explain why the virtual elimination of index arbitrage

volume does not eliminate market linkage.

We also find that trading costs in the stock market, as measured by the average bid-ask
25

spread for S&P 500 stocks, do not change following the triggering of Rule 80A, in spite of the

binding constraint on index arbitrage volume. Relative to the control group, both total trading

volume (inversely related to the spread) and volatility (directly related to the spread) decline after

Rule 80A is triggered. The overall impact of these opposing forces on bid-ask spreads is

ambiguous. In addition, we find no change in futures market volatility attributable to Rule 80A.

In summary, our overall assessment of Rule 80A is that it has had little impact on trading

costs and intermarket arbitrage despite significant curtailment of index arbitrage volume. Although

we find statistically significant changes in market behavior after the triggering of Rule 80A, similar

changes are also observed to occur on days of large price movements before Rule 80A's adoption.

Therefore, we cannot conclude that these changes are attributable to Rule 80A.
26

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