futures trading and cash market volatility: stock index and interest rate futures

Futures Trading and Cash Market Volatility: Stock Index and Interest

Rate Futures Franklin R. Edwards

I. INTRODUCTION

here is a widespread belief today that uncertainty and financial risk are T greater now than at any time since the turbulent 1920’s. Financial risk and uncertainty is commonly associated with more volatile financial asset prices: stock prices, interest rates, and exchange rates. Recently, day-to-day movements in these prices have seemed too large to be realistically attributed to any objective new information. Large moves in stock prices, for example, have occurred only to be reversed in the hours immediately following. These episodes have instilled in investors a growing uncertainty about the future and about the future value of asset prices. There is a clear perception that volatility and the risk of holding financial assets has increased.

Several explanations have been offered to explain the perceived increase in volatility. One is speculation. Financial markets, it is argued, are presently subject to more speculative activity than in the past, and this activity is on net destabilizing. Fluctuations in asset prices are attributed not to changes in economic fundamentals (or to changes in expectations about them) but to large, professionally-managed, speculative trading programs.’ The “Triple Witch- ing Hour” trading phenomenon in the stock market is singled out as a prime example. This belief is reinforced by the knowledge that a larger and larger share of financial asset trading is done by a relatively few professionally-managed institutions and that these institutions often pursue computer-guided trading strategies that have them all selling or buying at the same time.2

Another explanation is the advent of futures markets. It is alleged that these markets have increased speculative activity which, in turn, has destabilized cash markets.

This article is based upon a paper presented at the Conference On The Impact of Stock Index Futures

I want to thank Cindy Ma, a Ph.D student at the Columbia Business School, for her assistance in prepar-

’ “Interest Rate Worries and Program Trading Send Stocks Plunging,” The Wall Street Journal, Septem-

2For an examination of this issue with respect to futures trading, see Lukac, Brorsen, and Irwin (1986).

Trading at The Center For The Study of Futures Markets, Columbia University, June 8, 1987.

ing this paper.

ber 12, 1986.

Franklin R. Edwards is Professor and Director of the Columbia Futures Center, Columbia University.

The Journal of Futures Markets, Vol. 8, No. 4, 421-439 (1988) 0 1988 by John Wiley & Sons, Inc. CCC 0270-73 14/88/04042 1 - 19S04.00

Still another explanation for the increased volatility is the “fashion and fad” view advanced by Shiller ( 1986).3 He argues that capricious changes in inves- tor sentiments and changing “fashions and fads” can strongly influence prices in financial markets.

This paper has two objectives: (1) To determine whether the volatility of asset prices has increased over the period from 1973 to the present; and (2) To examine the allegation that the introduction of financial futures markets, and in particular equity futures, is responsible for an increase in asset price volatility.

The paper focuses on daily data for stock prices and short term debt instruments. The S&P 500 Index, the Value Line Index, 90-day Eurodollars, and 90-day T-Bills are examined.

11. SHOULD VOLATILITY CONCERN US?

It may be useful to discuss briefly why price volatility occurs. Take, for example, stock prices. According to the simple efficient markets model, the real ex- dividend stock price is:

where E, denotes the mathematical expectation conditional on information available at time t.

/3 is the discount factor, 0 < /3 c 1

is the marginal rate of substitution of consumption between period t + j and period t. is the real dividend paid at period t + j .

Bu’(Ct+j) U’(Ct)

d t ,

It is clear that changes in expectations regarding future dividends, in the discount factor, or the marginal rate of substitution of consumption will cause volatility in stock prices. In addition, unanticipated changes in the riskless interest rate or the risk premium will affect the discount factor and, therefore, stock prices. Further, since expectations are conditional upon available information, new information can change expectations about these key variables, and in this way affect share prices and the volatility of prices. Asset price volatility, therefore, occurs because of new information shocks, which arrive in a stochastic manner. If such shocks occur more frequently, and/or cause larger changes in expected values, asset price volatility will increase.

In general, the quicker and more accurately prices reflect new information (assuming that the information is not false), the more efficient will be the allo-

3See Shiller (1986), p. 5. For an alternative view about the usefulness of such anecdotal evidence, see Garber ( 1986).

cation of resources. More asset price volatility need not be bad. It may be a manifestation of a well-functioning market. However, price dat i l i ty greater than that which can be justified by objective new information (or by standard asset-pricing models) is bad. It makes prices inefficient by definition. This has been designated as “excess ~olati l i ty.”~ (Too little volatility is equally bad, although this concept does not seem to have generated enough interest to have been given the label of “deficient volatility.”)

This rather academic view of asset volatility is probably not central to investors when they complain about increased volatility. Their concern is no doubt about the stability of their wealth and the certainty of their future wealth. In this context any increase in volatility may be bad. It increases the prospects of their suffering unforseen future losses. Further, when asset prices continually exhibit sharp volatility during very short periods of time (such as a day), investors may lose confidence that the explanation is changes in information about economic fundamentals. They may come to see financial markets as subject to speculative excesses and irrational investment whims. Thus, it is possible that greater volatility might bring with it a general loss of confidence in financial markets with a concomitant loss of market liquidity. This may have negative welfare effects by increasing transaction costs and, indirectly, by raising the required average real return on financial assets.

Increased price volatility is commonly linked to real economic activity in several ways. Bodie, Kane, and McDonald (1983) argue that the increased volatility of nominal interest rates has had the effect of raising the required average real rate of return by increasing the risk premium on bonds. Until 1977, they estimate, the premium of long-term bonds over short-term bonds was near zero. But recent volatility, they contend, has increased the risk premium to about four percentage points (in 1980-82). Thus, real rates on bonds have risen ~ h a r p l y . ~

This argument is not entirely convincing. During the same time period ex ante real interest rates were also unusually high on short-term securities, such as Treasury Bills. It is difficult to believe that short-term securities would re- quire such a high risk premium. Thus, it is unclear whether increased volatility, or some other factor, is responsible for the unusually high real interest rates that existed in the 1980-82 period.6

In a related argument Mascaro and Meltzer (1983) contend that increased money growth uncertainty (which should contribute to interest rate volatility) caused the rise in ex ante real interest rates after October 1979.’ They relate a measure of money growth uncertainty to ex ante real interest rates and find a significant positive relationship, indicating that increased monetary uncertainty caused higher ex ante real interest rates.8

4There is an extensive literature on “excess volatility.” See, for example, Shiller (1981) and Flavin (1983).

’See also Barro (1986). bBodie, Kane, and McDonald (1983) also fail to find evidence that the riskiness of nominal bonds can

’See also Fama (1976), Hartman, and Makin (1986). “he measure of money growth uncertainty is constructed as follows: a univariate time series model is fit

to an M1 money growth series to extract a series of forecast errors. The measure of money growth uncertainty equals the square root of the average sum of squared forecast errors over the previous twelve months.

The overall conclusion of these studies is ambiguous.

explain the recent rise in ex ante real rates on short maturity assets.

FINANCIAL FUTURES & VOLATILITY /423

Both of the above theories relating monetary uncertainty and nominal interest rate volatility to real interest rates have recently been rigorously tested by Huizinga and Mishkin (1985). They examine the relationship between ex ante real interest rates and uncertainty about money growth, inflation, and nominal interest rates.9 Huizinga and Mishkin conclude that “uncertainty variables do not have much explanatory power for ex ante real interest rates.”1°

Thus, while there may be a link between increased asset price volatility and real economic activity via the real interest rate, such a link is at present uncon- firmed and not widely accepted.

A similar argument has been made about the stock market and the cost of capital. Malkiel(l979) and Pindyck (1984, 1986) argue that the higher volatility of stock prices has resulted in an increase in the required risk premia on stocks, causing lower stock prices and, in general, poorer stock market performance. This can in turn result in a higher cost of capital and an adverse effect on real economic activity. Poterba and Summers (1984), in contrast, conclude that changes in volatility cannot account for much of the observed variation in stock prices. Thus, the controversy over the effect of stock price volatility on stock prices, or on capital formation, is just as heated as is the argument over the impact of interest rate volatility on real interest rates, and is just as incon- clusive.

In summary, there is very little firm evidence to support the claim that increased asset price volatility has adverse effects on economic activity. While there is a clear popular perception that greater volatility is bad, it is difficult to establish concrete links between volatility and either economic activity or economic welfare.

111. HAS VOLATILITY INCREASED?

A. Data and Period of Study

Is the perception correct that asset price volatility is increasing? To answer this question data on four financial variables: the S&P 500 Index, the Value Line Index, T-Bills, and Eurodollar 90-day Time Deposits, during the time period 1973 to 1987 are examined. The data are daily spot and futures closing prices as well as intra-day high and low prices for the stock indices.” Previous studies of volatility have often focused on month-to-month changes in prices.12 Daily price data seem more relevant to the current concerns about increasing price

91t may be useful to point out that the controversy is being fought in the context of a rational expectations world. Measures of monetary uncertainty are “rational forecast errors,” and not simply the observed volatility of asset prices. The latter is what is observed and reported in the press, not the former. For a description of the Huizinga-Mishkin uncertainty variable, see their paper, p. 26, note 34.

‘OIbid., p. 27. “The data sources are: the spot S&P Index comes from the CRSP data base; the spot Value Line Index

from Commodity Systems, Inc.; the spot T-Bill and spot Eurodollar rates are 3-month constant-maturity interest rates and are from the Federal Reserve data base. All prices are daily closing trade prices. Futures prices are closing prices and come from the Columbia Futures Center Data Base, supplied by Commodity Systems, lnc.

I2See, for example, Shiller, Op. Cit.

424/ EDWARDS

volatility, where the emphasis is on large changes in day-to-day or even intra- day prices. l3

The period of analysis, June 1973 through May 1987, was chosen because fixed-dollar exchange rates were abandoned in March 1973 (the end of the Bretton Woods system), and because this period saw the beginning of financial futures markets: 1972 for foreign currencies, 1976 for T-Bills, 1977 for T-Bonds, 1981 for Eurodollar Time Deposits, and 1982 for the S&P 500 Index and the Value Line Index. The ending date of the analysis was dictated solely by the data available to me.

In analyzing volatility during this time period it is necessary to treat the period from October 1979 through September 1982 separately. Before Octo- ber 1979 the Federal Reserve used the Federal Funds rate, or money market conditions, as its operating target.14 Its strategy was to smooth interest rate fluctuations by allowing short-term interest rates to fluctuate only in a narrow range. In October 1979, however, the Federal Reserve adopted a nonborrowed reserves (or reserve aggregate) operating target. It abandoned interest rate tar- gets in favor of controlling monetary aggregates more closely in an effort to curb inflation. This was a dramatic shift of policy.

In October 1982, the Federal Reserve again changed its policy, replacing the nonborrowed reserves procedure with a borrowed reserves procedure. The latter led to a monetary policy after October 1982 that was quite similar to that in force prior to October, 1979, but quite unlike that in force from October 1979 through September 1982.

An examination of the different monetary policy operating procedures has led analysts to conclude that the volatility of interest rates: Should be greater during the October 1979 through September 1982 period than either before or after this period; and that in the period after October 1982, volatility should still be somewhat greater than before October 1979.15

While it is not entirely clear what effect this change in monetary policy should have had on stock prices, it is plausible to expect that stock price volatility should also have been greater in the 1979-82 period, since higher interest rate volatility should affect stock prices as we11.16

The validity of treating the October 1979 through September 1982 period as a distinct monetary regime has received strong empirical support from Huizinga and Mishkin (1985). They conclude that “. . . changes in monetary policy regimes are an important factor in explaining the recent unusual behavior of ex ante real interest rates. We find that not only are there significant shifts in the stochastic process of real interest rates in October 1979 and Octo- ber 1982 when the Federal Reserve altered its behavior, but these rates are also found to be the most likely breakpoints in the real rate process.”17

%ee for example, “Stock Prices Fall by Record Amount in Busiest Session,” The New Yo& Times,

I4See, for example, Gilbert (1985). I5See Roley (1986), Walsh (1984), and Hawkins (1984). IbSome economists contend that monetary policy after October 1982 was in fact almost identical to that in

effect before October 1979, a policy of smoothing short-term interest rates. See, for example, Mishkin (1986).

September 12, 1986.

”lbid. , pp. 33-34.


Thus, in the empirical analyses which follow, the period from October 1979 through September 1982 is treated as a separate sub-period in order not to confuse (or mix together) quite distinct monetary policy regimes. An attractive by-product of this procedure is that it allows us to examine the effects of the October 1979 and September 1982 shifts in monetary policy on asset price volatility.

B. Measumes of Volatility

Several measures of volatility were estimated and compared to determine the sensitivity of our conclusions to the measure of volatility used.18 We report only three: The standard close-to-close variance estimator of the percentage changes in daily spot prices, measured as ln(Pt/Pt-l), where P, and are closing prices on successive days; a more efficient high-low variance estimator using intra-day high (H) and low (L) prices, measured as [In(H,) - ln(L,)I2/4 ln2; and an intra-day price range estimator, represented by the mean and standard deviation of the daily percentage differences between the intra-day high and low prices, measured as ln(H,/L,).

The first two measures are standard volatility estimators and are widely dis- cussed in the 1iterat~re.I~ The third measure is closely related to the second estimator, but may be useful to present separately because of its ready intu- itive interpretation.

C. Close-to-Close Volatility

Estimates for the first measure of volatility, the variance of close-to-close prices, are shown in Tables I and I1 for three sub-periods 1973-79, 1979-82, and 1982-86. Table I contains the estimates for the S&P 500 and Value Line Stock Indices, and Table I1 shows those for T-Bills and Eurodollars.

Two conclusions emerge from these tables. First, there has not been a general increase in volatility. The volatility of stock prices has either remained the same or declined. Table I shows that volatility was significantly lower for the S&P 500 Index in 1982-86 than in 1973-79. The volatility of short-term debt instruments also has declined significantly in the 1982-1986 period from what

18For example, the mean of the absolute daily percentage close-to-close price changes was estimated and compared to the standard deviation of close-to-close percentage daily price changes. Monthly volatility estimates had a correlation of .975. Other comparisons of different volatility measures indicate that our conclusions are quite robust with respect to different measures. In addition, because of the significant changes in the level of prices that took place over the 1973-86 period, we based our volatility measures on percentage rather than absolute price movements. From an investment perspective, it is obvious that comparing rates of return is more meaningful than comparing absolute (or dollar) movements.

19The high-low variance estimator was developed by Parkinson (1980), who showed theoretically that under certain restrictive assumptions, it is a more efficient estimator than the traditional close-to-close variance. The difficulty of estimating true volatility occurs because of the lack of continuous price observations: the closing price is only one observation each day. Beckers (1983) empirically compared the two estimators and found that, in general, Parkinson’s estimator contained new information and was a more accurate estimator of true volatility. Garman and Klass (1980) propose still another measure which is a weighted average of the Parkinson high-low estimator and the traditional standard deviation close-to-close estimator. The efficiency of the latter is not much greater than that of Parkinson’s estimator.

4261 EDWARDS

Table I VOLATILITY OF CASH STOCK INDICES

Variances-Rates of Retorn

S&P 500 (Value Line)

73(75)-79 0.8311 0.5187

79-82 0.9492 0.7218 F-statistic 1.142* 1.3916" (nl, n2) (1599,760) (1193,760)

73(75)-79 0.8311 0.5187

82-86 0.7417 0.5095 F-statistic 1.1205+ 1 . O m + + (nl, 122) ( 1599,1076) (1193,1076)

79-82 0.9492 0.7218

82-86 0.7417 0.5095 F-statistic 1.2798+ 1.4167+ (nl, n2) (760,1076) (760,1076) Data for the S&P 500 Index begin on June 1, 1973, and for the Value Line Index on January 1, 1975. The respective time periods are 6/1/73 or 1/1/75 to 9130179, 10/1/79 to 9/30/82, and 10/1/82 to 12/31/86. The F-statistic is the ratio of the variances, and n l and n2 are the respective number of observations. *Indicates that the later time period is significantly greater than the earlier time period at least at 5% level. +Indicates that the earlier time period is significantly greater than the later time period at least at 5% level. ++The difference between the two time periods is not statistically significant.

vs .

vs .

vs .

it was in the earlier 1973-79 period. Finally, for both stocks and debt instruments volatility has declined since the period of peak volatility, 1979-82.

Second, for both stocks and debt instruments volatility increased significantly during the 1979-82 period, and then experienced a significant decline during the 1982-86 period. It is clear, therefore, that the shifts in monetary policy that occurred in both October 1979 and October 1982 had a significant effect on financial asset volatility. After September 1982, volatility returned to a level either equal to or lower than that which prevailed before 1979.

D. High-Low Volatility Estimators Compared to Close-to-Close Estimators

An alternative way to measure price volatility is to make use of daily high and low prices in addition to closing prices. This provides three daily price observations, rather than only one. As indicated earlier, under certain restrictive assumptions (that the logarithm of stock prices follows a Brownian motion with zero drift), it can be shown that a variance estimator using high and low prices

FINANCIAL FUTURES & VOLATILITY 1427

Table II VOLATILITY OF DEBT INSTRUMENTS

Variances-Rates of Return

T-Bill Euro (3 Mo.) (3 Mo.)

73-79

79-82 vs.

F-statistic ( n l , nA

73-79

82-86 vs.

F-statistic (n1, n2)

79-82 vs . 82-86 F-statistic ( n l , n2)

0.0009 0.0023

0.0056 6.2222*

(1576,748)

0.0009

0.0004 2.2500+

(1576,1059)

0.0056

0.0004 14.0000 +

(748,1059)

0.0098 4.2609*

(1605,772)

0.0023

0.0007 3.2860+

(1605,1089)

0.0098

0.0007 14 .OOOO+

(742,1089)

The respective time periods are 1/1/73 to 9/30/79, 10/1/79 to 9/30/82, and 10/1/80 to 12/31/86. *Indicates that the later time period is significantly greater than the earlier time period at least at 5% level. +Indicates that the earlier time period is significantly greater than the later time period at least at 5% level.

in addition to closing prices is substantially more efficient, 7.4 times greater than an estimator based only on the close-to-close variance.20 The Parkinson high-low estimator used in this study is a simplified high-low variance estimator which also displays superior efficiency characteristics.21

Unfortunately, intra-day high and low prices are not available for spot interest rates, and are only available on a consistent basis for stock indices since early 1984. On January 2, 1984, Standard and Poor changed its methodology for calculating high and low prices for its 500 Index. Consequently, high-low volatility estimates are presented only for recent years. (see Table IV).

N. HAS THE INTRODUCTION OF FUTURES TRADING INCREASED VOLATILITY?

A. The Argument

It is often alleged that the introduction of futures trading destabilizes cash markets, making cash prices more volatile. What is the evidence? While a

*OBeckers (1983) and Garman and Klass (1980). 21 Beckers (1983).

428/ EDWARDS

number of empirical studies have examined the effect of futures trading on cash volatility,22 few have studied the impact of financial futures. This section examines the volatility before and after the advent of futures trading of stock indices, T-Bills, and 90-day Eurodollar Time Deposits.

Why should the introduction of futures trading increase the volatility of cash markets? Conventional wisdom suggests that futures trading will add more informed traders to the cash market, making the cash market more liq- uid and, therefore, less volatile. The view that futures trading will increase volatility appears to stem from a belief that futures markets result in uninformed (or irrational) speculators trading in both futures and cash markets.. Such speculators, it is argued, drive prices up or down hoping for short-run “bandwagon” profits. Those who hold this view point to the expiration-day effects caused by large institutional stock-index arbitrageurs and to institutions like commodity pools which employ “technical” trading strategies (rather than “fundamental” informat i~n) .~~

It is not possible, of course, to know to what extent futures speculators trade irrationally. However, economists who have analyzed the “irrational speculation” argument theoretically conclude that it would take a considerable amount of such speculation to destabilize cash markets. Stein (1986), for example, demonstrates that under a variety of realistic conditions the introduction of a substantial amount of uninformed speculation will still not increase cash market volatility. Despite this theoretical work, there is still disagree- ment about whether futures trading increases or decreases the volatility of spot prices. The issue, therefore, remains an empirical one.

With little or no theory to suggest that futures markets increase cash market volatility, and with little evidence to indicate that increased volatility (should it occur) is necessarily bad, it is surprising how contentious the volatility issue has been throughout the history of futures markets. Financial instruments, stocks and debt instruments, are but a new battlefield upon which an old bat- tle is being waged.24

B. The Evidence €or Financial Futures

During the last ten years a number of both equity and interest rate based futures contracts have begun trading. To assess the impact of these contracts, we examine the Volatility of the underlying cash instruments both before and after the start of futures trading. The start of futures trading occurred on tliese dates for the following instruments:

S&P 500 April 21, 1982 Value Line February 24, 1982 90-Day Eurodollars December 9, 1981 90-Day T-Bills January 6, 1976

22See, for example, Cox (1976) and Weaver and Banerjee (1982). 2’See Brorsen and Irwin (1985). 24The volatility debate may be a smoke-screen for cash market participants who dislike futures markets

because they undercut the power of cash market participants to set prices.


Determining the impact of these contracts on cash market volatility is com- plicated by the monetary regime shifts that took place in 1979 and 1982. We have seen that, because of this monetary policy shift, volatility was significantly greater in 1979-82 than either before or after this period. It would be inappropriate, therefore, to attribute these effects to the presence of futures trading.

Cash market volatility for each of the above instruments for both the period before and after the introduction of futures trading is computed and tested to see if there is a statistically significant change in the level of volatility. The calculations are made in two ways: including the 1979-82 monetary-regime- shift period, and excluding it. Excluding this period provides a clearer view of the impact of futures markets.

It is obvious that this statistical procedure is quite crude in that it does not account for factors other than the monetary regime shift that might influence daily price volatility. Unfortunately, there is no satisfactory way to do this. Daily price movements are subject to daily changes in investors’ expectations, which cannot be measured. For example, expectations about future price inflation can change quickly and significantly during the course of a day, as new economic news unfolds. Thus, the results, based on the volatility before and after the introduction of futures, are only valid if there also has not been a shift in either the information generation process or the expectations-formation process that coincides with the advent of futures trading.25

Table 111 shows the price volatilities for the periods for which daily data were available before and after futures trading for the two stock indices and for the two interest rate instruments. Once the 1979-82 period is excluded from the analysis, it becomes clear that volatility has generally diminished since the start of futures trading. Only the Value Line Index does not show a decline in volatility; it shows no significant change. There is never an increase in volatility. Further, these conclusions hold for T-Bills for each of the “after- futures” periods taken separately: the period prior to 1979 and the period after 1982.

Table IV shows volatility estimates for both the S&P 500 and Value Line Indices for individual years from 1982 to May 18, 1987. In addition, it reports alternative volatility estimates based on intra-day highs and lows as well as close-to-close daily prices. It is clear that until 1986 volatility has been lower in every full year since the advent of futures. Beginning in 1986, however, volatility began to rise, and in 1987 increased even more. This pattern is evident for all measures of volatility, which show similar movements.26

It is doubtful that the rise in stock market volatility is due to anything associated with futures trading. The most likely causes are the exceptional rise in stock prices during recent months and the sharp fall of the dollar against lead- ing c~rrencies.~’ Higher volatility also has occurred in the bond market and in

25A few earlier studies attempt to control for “other” factors, but, in my view, fail to do so. I discuss later in the paper why the procedures used in these studies are flawed.

zblf monthly volatilities are calculated using the close-to-close (column 1 of Table IV) and intra-day (column 3 of Table IV) measures for the period 1982-86, the two measures show a correlation of .91 for the S&P 500 Index and .95 for the Value Line Index.

27Regression analyses relating monthly measures of volatility to absolute percentage price (or index) changes during a month clearly show a positive and significant relationship between volatility and price movements. The greater the general price change is during the month, the higher is market volatility.

430/ EDWARDS

Table III VOLATILITY BEFORE AND AFTER FUTURES TRADING

(VARIANCES OF RATES OF RETURN USING CLOSE-TO-CLOSE DAILY PRICES)

Stock Indices Debt Instmments

S&P 500 Value Line T-blll Ew0T.D.

PN?-FUtaree i) Entire Period” 0.8559 0.5979 0.0016 0.0046 ii) Exclude 79-82b 0.8311 0.5187 0.0016 0.0023

POst-FUttWeS

i) Entire Period‘ 0.7783 0.5212 0.0018+ 0.0014* ii) Exclude 79-82b 0.7417* 0.5095 0.0004* 0.0007*

iii) Pre 10/79 only” - - 0.0004* - iv) Post 9/82 onlf 0.7417* 0.5095 0.0004* 0.0007*

*Variance for the pre-futures period (excluding the time period 10/1/79 to 9/30/82) is greater than the variance for the post-futures period at the 5 percent level of significance. +Variance for the pre-futures period is significantly less than for the post-futures period at the 5 percent level of significance. ‘The exact time periods are 6/1/73 to 4/20/82 for the S&P 500, 1/1/75 to 2/23/82 for the Value Line, 6/1/73 to 1/5/76 for T-Bills, and 6/1/73 to 12/8/81 for Euro Time Deposits. ”The period 10/1/79 to 9/30/82 is excluded. ’The period 4/21/82 to 12/31/86 for the S&P 500, 2/24/82 to 12/31/86 for the Value Line, 1/6/76 to 12/31/86 for T-Bills, and 12/9/81 to 12/31/86 for Euro Time Deposits. dThe period 1/6/76 to 9/30/79 for T-Bills. The period 10/1/82 to 12/31/86 for all instruments.

markets not associated with stock index futures trading. The upswing in stock price volatility, therefore, should be interpreted in the context of the nearly five years of stock index futures trading that we have experienced. During most of that time volatility was lower than it was prior to futures trading.28

Finally, Table V shows a similar pattern for short-term debt instruments: cash market volatility has been lower in every year since the start of futures trading in these instruments (excluding the 1979-82 period). Further, the volatility of T-Bill prices increased somewhat in early 1987, although both T-Bill and 90-Day Eurodollar volatility remained below their prefutures levels.

Thus, with the possible exception of the “expiration-day” stock index effects, there is no evidence that futures trading in financial instruments has destabilized cash markets. If anything, price volatility has been lower since the introduction of futures.

C. Previous Empirical Studies of Financial Futures and Cash Market Volatility

While there has been extensive investigation of the impact of futures trading in nonfinancial contracts on cash market volatility, there have been few studies

ZSA recent SEC study of trading on September 11 and 12, 1986, also concludes that futures-related trading was not responsible for the volatility that occurred on those days. “The Role of Index-Related Trading in the Market Decline on September 11 and 12, 1986,” a report by the Division of Market Regulation, U.S. Securities and Exchange Commission, March 1987.


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Table V INDIVIDUAL YEAR VOLATILITIES: DEBT INSTRUMENTS

JUNE 1, 1973 TO MAY 18, 1987

Euro Time Line T-Bill (A)* Deposits (B)*

Pre-Futures

1/5/76 (A) 0.0398 12/8/81(B) 0.0681

1 6/1/73 to

Post-Futums 2 1 /6/76 to

9/30/79 0.0198 -

3 10/1/79 to 9/30/82 (A) 0.0747 12/9/81 to 9/30/82 (B) 0.0749

4 1983 0.0195 0.0264 5 1984 0.0228 0.0279 6 1985 0.0189 0.0239 7 1986 0.0144 0.0151 8 1/1/87 to

5/18/87 0.0241 0.0166 *The standard deviation of close-to-close daily price changes.

of financial futures.29 The empirical studies of financial futures that have been done, however, suggest that the introduction of futures trading has not increased the volatility of cash prices.30 In most of these studies the authors attempt to control for economic factors that might affect underlying cash market volatility by including yields (or prices) on cash market securities for which futures trading does not exist. For example, Froewiss (1979) and Figlewski (1981) use 10-year Treasury Bonds to control for “market factors’’ that might affect GNMA cash prices (a 10-year T-bond futures contract did not exist at the time); Simpson and Ireland (1982) use FNMA securities as well as 10-year T-Bonds for the same purpose; and Simpson and Ireland (1985) use 90-day Bankers’ Acceptance yields to control for factors affecting the 91 -day T-Bill rate.

This methodology assumes that financial markets are completely segre- gated. In particular, if it is assumed that the introduction of futures trading in T-Bills injects irrational speculators into the T-Bill market it would have to be true that T-Bill yields would not affect Bankers’ Acceptance yields. If this is not true and changes in the behavior of T-Bill yields are transmitted to Bank-

29See, for example, Powers (1970). 30See Corgel and Gay (1984), Charles and Workman (1981), Figlewski (1981), Froewiss (1978), Moriarty

and Tosini (1985), Seider (1981), Simpson and Ireland (1982). Simpson and Ireland (1985).


ers’ Acceptance yields; then using Bankers’ Acceptance yields to represent economic factors independent of futures trading is obviously inappropriate. Use of such interdependent control variables does not permit a correct statistical inference about the impact of futures trading.

Both finance theory and what is known about the operation of financial markets suggest that financial markets are highly integrated. Arbitrage pricing theory, in particular, envisages a two-way street between securities such as T-Bills and Bankers’ Acceptances, or GNMA’s and either FNMA’s or 10-year T-Bonds. In purposely choosing a “control” security which has had a long and close relationship to the cash security that they wish to examine, researchers have implicitly built in a close arbitrage relationship which should be expected to continue after the introduction of futures trading on either one of the securities. Thus, the control variables they use are not independent of the effects of futures trading. It is clear that a better statistical methodology is needed to control for the cash market volatility that would occur in the absence of futures trading.

There also have been a number of “causality” studies related to the issue of the impact of financial (as well as nonfinancial) futures trading on cash markets. These do not, however, shed any light on the issue of whether futures trading is a stabilizing or destabilizing influence. The objective of these studies is to determine the causal impact of futures price volatility on the volatility of cash markets. In brief, they estimate the causality relationship between either the weekly or monthly average (daily) price volatility in futures and cash markets, using a “Granger” definition and statistical meth~dology.~~ Some results have suggested that futures price volatility causes (or leads) cash price volatility. (This finding is common in studies of nonfinancial futures markets.)32

Causality studies, however, cannot infer either a stabilizing or destabilizing effect of futures trading. Even if futures price volatility “leads” cash price volatility, it may simply be because futures markets process more quickly the same information available to cash markets. Since trading costs are lower in futures markets, this is likely. Futures markets need not introduce any new information (true or false) for us to find that futures price volatility leads cash price volatility. Further, to the extent that futures markets contain new information, there is no way of knowing whether such information is or is not re- flective of fundamental economic factors. Causality analysis, therefore, tells us nothing about the volatility effects of futures trading.

V. STOCK INDEX EXPIRATION-DAY EFFECTS

Stock index futures trading has received close public scrutiny because of the associated expiration-day effects. The four days each year that have been noto- riously labelled the “Triple Witching Days” are those on which the S&P 500 futures and options index contracts expire, as well various individual stock options contracts. Because of the “cash settlement” feature of stock index futures and options contracts, many participants in this market, who do a cash trade related to a futures position they hold, prefer to “unwind” their posi-

31See Bhattacharya, Ramjee, and Ramjee (1986). 32See, for example, Oellerman and Farris (1985).

tions at the termination of trading in the futures or option contract. When those doing such cash trades “at the close” happen to be predominantly on one side of the market, there may be substantial order imbalances in the cash market. If the specialists handling the underlying stock cannot provide suffi- cient liquidity, these order imbalances can lead to sharp price movements, either up or down. The result may be significant price volatility on expiration days.

Stock price volatility is in fact greater on those days when index options and futures expire together than when either only options expire or when neither futures nor options expire. However, much of this increase in volatility appears to occur during the last hour of trading. Table VI shows the standard deviation of percentage changes in various stock indices (close-to-close) for all Fridays versus Fridays on which certain futures or option index contracts expire. Volatility is significantly greater for those days on which both futures and index options expire. Thus, higher volatility appears to be associated only with the expiration of futures contracts.

Table VII provides information on intra-day volatility, hour-at-hour. While volatility is somewhat higher after 2:OO p.m. on those Fridays on which both futures and options expire, most of the increase takes place during the last hour of trading (after 3:OO p.m.). During the last hour volatility is significantly higher on expiration days than on normal days. Further, Table VIII shows that on 9 of the 13 expiration days studied there were price reversals on the

Table VI VOLATILITY OF FRIDAY INDEX CHANGES

Index Type of Friday* Volatility ~~ ~~ ~

S&P 500 Normal 0.723 Options/Futures 1.026+ Options-only 0.541

S&P 100 Normal 0.786 OptiodFutures 1.178+ Options-only 0.635

NYSE COMP Normal 0.705 Options/Futures 0.846 Options-only 0.522

*Volatility is the standard deviation of percent changes in the index from Thursday close to Friday close. For futures expira- tions through March 1984, close to close data are for Wednes- day to Thursday because futures terminated on Thursday during this period. Data span 7/1/83-10/24/86. +Significantly greater than normal days at the 5 percent level of significance, using an F-test with 11 and 114 degrees of freedom. Source: T. Kilcollin, “Program Trading, Stock Index Futures and Stock Market Volatility,” unpublished paper, prepared for the Conference on Monetary Uncertainty, Financial Futures and Economic Activity, November 6-7, 1986.


Table VII VOLATILITY OF INTRADAY INDEX CHANGES*

Time Period

from:10:00 11:OO 12:OO 1:00 2:OO 3:OO Index Type of Friday to:ll:00 12:OO 1:00 2:OO 3:OO Close

S&P 500

S&P 100

NYSE COMP

VALUE LINE

Normal Options/Futures Options-on1 y

Normal Options/Futures Options-only



.376

.488

.267

.411

.533

.260

.304

.361

.209

.304

.283

.206

.291 .229 .202

.148 .199 .150

.193 .160 .170

.337 .247 .236

.179 .258 .168

.243 .200 .213

.259 .179 .187

.139 .153 .153 ,168 .141 .165

.174 .131 .144

.139 .082 .lo2

.168 .114 .089

.211

.274

.243

.463

.357

.305

.203

.274

.217

.131

.201

.149

.256

.781 t

.229

.446

.834t

.320

.220

.581 t

.211

.159

.394t

.232 *Volatility is the standard deviation of percent changes over the time shown. Data span 7/83- 10/24/86. tsignificantly greater than normal days at the 5 percent level of significance, using an F-test with 11 and 114 degrees of freedom. Source: T. Kilcollin, “Program Trading, Stock Index Futures and Stock Market Volatility,” unpublished paper, prepared for the Conference on Monetary Uncertainty, Financial Futures and Economic Activity, November 6-7, 1986.

following trading days. Taking only those nine expiration days, the average (absolute) index move during the last hour of trading was .824 percent. The average price reversal for the nine trading days which followed was --.650. Thus, about 75 per cent of the price change was reversed the following day. This clearly suggests a liquidity problem due to order-imbalance.

These data, together with the earlier analysis, demonstrate that, while there has been a price impact of stock index futures trading, the effect is limited largely to expiration days. On these days volatility is clearly greater because of deficient liquidity in the cash market.

The potential economic significance of this effect seems small. The observed expiration-day price effects, which are on average less than one percent, are not unacceptably large. They are also transitory. In 1986 alone, for example, there were 58 days (other than the four S&P expiration days) on which a close- to-close S&P 500 Index move of greater than one percent occurred. During the entire 14-year period from 1973-86, about one in five days experienced an index move of greater than one percent. In addition, studies of “block trading’’ on the New York Stock Exchange have shown that on days on which “blocks” are traded, stock prices change on average by more than one percent.33 Fi- nally, in contrast to block trades, expiration-day price effects are more pre-

”See , for example, Kraus and Stoll(1972).

436/ EDWARDS

Table VIII DAY BY DAY SUMMARY OF LAST HOUR PRICE CHANGES AND SUBSEQUENT REVERSALS FOR

S&P 500 INDEX VALUES

Date

15-Sep-83 15-Dec-83 15-Mar-84 15-Jun-84 21 -Sep-84 21-Dec-84 15-Mar-85 21-Jun-85 20-Sep-85 20-Dec-85 21-Mar-86 20-Jun-86 19-Sep-86

Expiration-Day Last-How Next-Day:

Index Change Amount of (absolute value, Reversal

in percent) (percent)*

.520 - .073

.615 - .192

.266 - 1.709 so1 .148

1.263 - .193 .285 .284 .976 - .283 .996 - .886 .579 - 1.401 .076 .635

1.111 - .514 1.098 - .600 .524 .134

Average: All Days .678 - .358

Average: Nine reversal days .824 - .650 *A negative sign indicates a price reversal. A positive sign indicates a price movement in the same direction. Source: T. Kilcollin, “Program Trading, Stock Index Futures and Stock Market Volatility,” unpublished paper, prepared for the Con- ference on Monetary Uncertainty, Financial Futures and Economic Activity, November 6-7, 1986.

dictable and more transitory. The potential harmful effects on investors, therefore, should be less. Thus, while it would be preferable if there were no expiration-day effects, the importance of these effects has been exaggerated, especially by the financial press.

VI. CONCLUSION

The main conclusion of this study is that the introduction of financial futures trading has not destabilized cash markets. Volatility has not increased because of futures trading. Both the day-to-day and intra-day price volatility of the stock market and of short-term debt instruments over the 18 year period from 1973-87 were examined and it was concluded that the introduction of futures on these assets did not result in an increase in price volatility. No evidence was found which links futures trading to an increase in general market volatility. While there is some evidence of futures-induced short-run volatility,

FINANCIAL FUTURES & VOLATILITY 14.37

such as that which occurs on (futures) contract expiration days, this does not carry over to longer periods of time.

Thus, it seems unlikely that the recent volatility of stock and bond prices is attributable to anything associated with futures trading. The more likely explanation for such volatility is the increasing uncertainty generated by the exis- tence of widely recognized macroeconomic disequilibriums.

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futures trading and cash market volatility: stock index and interest rate futures

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