The Journal of Finance

Valuation of American Futures Options: Theory and Empirical Tests

Published: 03/01/1986   |   DOI: 10.1111/j.1540-6261.1986.tb04495.x

ROBERT E. WHALEY

This paper reviews the theory of futures option pricing and tests the valuation principles on transaction prices from the S&P 500 equity futures option market. The American futures option valuation equations are shown to generate mispricing errors which are systematically related to the degree the option is in‐the‐money and to the option's time to expiration. The models are also shown to generate abnormal risk‐adjusted rates of return after transaction costs. The joint hypothesis that the American futures option pricing models are correctly specified and that the S&P 500 futures option market is efficient is refuted, at least for the sample period January 28, 1983 through December 30, 1983.

The Value of Wildcard Options

Published: 03/01/1994   |   DOI: 10.1111/j.1540-6261.1994.tb04426.x

JEFF FLEMING, ROBERT E. WHALEY

Wildcard options are embedded in many derivative contracts. They arise when the settlement price of the contract is established before the time at which the wildcard option holder must declare his intention to make or accept delivery and the exercise of the wildcard option closes out the underlying asset position. This paper provides a simple method for valuing wildcard options and illustrates the technique by valuing the sequence of wildcard options embedded in the S&P 100 index (OEX) option contract. The results show that wildcard options can account for an economically significant fraction of OEX option value.

Early Exercise of Put Options on Stocks

Published: 07/19/2012   |   DOI: 10.1111/j.1540-6261.2012.01752.x

KATHRYN BARRACLOUGH, ROBERT E. WHALEY

U.S. exchange‐traded stock options are exercisable before expiration. While put options should frequently be exercised early to earn interest, they are not. In this paper, we derive an early exercise decision rule and then examine actual exercise behavior during the period January 1996 through September 2008. We find that more than 3.96 million puts that should have been exercised early remain unexercised, representing over 3.7% of all outstanding puts. We also find that failure to exercise cost put option holders $1.9 billion in forgone interest income and that this interest is systematically captured by market makers and proprietary firms.

Intraday Price Change and Trading Volume Relations in the Stock and Stock Option Markets

Published: 03/01/1990   |   DOI: 10.1111/j.1540-6261.1990.tb05087.x

JENS A. STEPHAN, ROBERT E. WHALEY

This study investigates intraday relations between price changes and trading volume of options and stocks for a sample of firms whose options traded on the CBOE during the first quarter of 1986. After purging the price change series of the effects of bid/ask spreads, multivariate time‐series analysis is used to estimate the lead/lag relation between the price changes in the option and stock markets. The results indicate that price changes in the stock market lead the option market by as much as fifteen minutes. The analysis of trading volume indicates that the stock market lead may be even longer.

An Anatomy of the “S&P Game”: The Effects of Changing the Rules

Published: 12/01/1996   |   DOI: 10.1111/j.1540-6261.1996.tb05231.x

MESSOD D. BENEISH, ROBERT E. WHALEY

This study analyzes the effects of changes in S&P 500 index composition from January 1986 through June 1994, a period during which Standard and Poor's began its practice of preannouncing changes five days beforehand. The new announcement practice has given rise to the “S&P game” and has altered the way stock prices react. We find that prices increase abnormally from the close on the announcement day to the close on the effective day. The overall increase is greater than under the old announcement policy although part of the increase reverses after the stock is included in the index.

S&P 100 Index Option Volatility

Published: 09/01/1991   |   DOI: 10.1111/j.1540-6261.1991.tb04631.x

CAMPBELL R. HARVEY, ROBERT E. WHALEY

Using transaction data on the S&P 100 index options, we study the effect of valuation simplifications that are commonplace in previous research on the timeseries properties of implied market volatility. Using an American‐style algorithm that accounts for the discrete nature of the dividends on the S&P 100 index, we find that spurious negative serial correlation in implied volatility changes is induced by nonsimultaneously observing the option price and the index level. Negative serial correlation is also induced by a bid/ask price effect if a single option is used to estimate implied volatility. In addition, we find that these same effects induce spurious (and unreasonable) negative cross‐correlations between the changes in call and put implied volatility.

Efficient Analytic Approximation of American Option Values

Published: 06/01/1987   |   DOI: 10.1111/j.1540-6261.1987.tb02569.x

GIOVANNI BARONE‐ADESI, ROBERT E. WHALEY

This paper provides simple, analytic approximations for pricing exchange‐traded American call and put options written on commodities and commodity futures contracts. These approximations are accurate and considerably more computationally efficient than finite‐difference, binomial, or compound‐option pricing methods.

Does Net Buying Pressure Affect the Shape of Implied Volatility Functions?

Published: 03/25/2004   |   DOI: 10.1111/j.1540-6261.2004.00647.x

Nicolas P. B. Bollen, Robert E. Whaley

This paper examines the relation between net buying pressure and the shape of the implied volatility function (IVF) for index and individual stock options. We find that changes in implied volatility are directly related to net buying pressure from public order flow. We also find that changes in implied volatility of S&P 500 options are most strongly affected by buying pressure for index puts, while changes in implied volatility of stock options are dominated by call option demand. Simulated delta‐neutral option‐writing trading strategies generate abnormal returns that match the deviations of the IVFs above realized historical return volatilities.

One Market? Stocks, Futures, and Options During October 1987

Published: 07/01/1992   |   DOI: 10.1111/j.1540-6261.1992.tb03997.x

ALLAN W. KLEIDON, ROBERT E. WHALEY

We provide new evidence regarding the degree of integration among markets for stocks, futures and options prior to and during the October 1987 market crash. Where previous analyses have resulted in recommendations for the implementation of circuit breakers, the coordination of margin requirements across markets, and changes in regulatory jurisdiction, our analysis indicates that delinkage between markets during the crash was primarily caused by an antiquated mechanism for processing stock market orders. The results suggest that market integration may be better served by efficient order execution than by further restricting markets.

Hedge Fund Risk Dynamics: Implications for Performance Appraisal

Published: 03/13/2009   |   DOI: 10.1111/j.1540-6261.2009.01455.x

NICOLAS P.B. BOLLEN, ROBERT E. WHALEY

Accurate appraisal of hedge fund performance must recognize the freedom with which managers shift asset classes, strategies, and leverage in response to changing market conditions and arbitrage opportunities. The standard measure of performance is the abnormal return defined by a hedge fund's exposure to risk factors. If exposures are assumed constant when, in fact, they vary through time, estimated abnormal returns may be incorrect. We employ an optimal changepoint regression that allows risk exposures to shift, and illustrate the impact on performance appraisal using a sample of live and dead funds during the period January 1994 through December 2005.

Implied Volatility Functions: Empirical Tests

Published: 12/17/2002   |   DOI: 10.1111/0022-1082.00083

Bernard Dumas, Jeff Fleming, Robert E. Whaley

Derman and Kani (1994), Dupire (1994), and Rubinstein (1994) hypothesize that asset return volatility is a deterministic function of asset price and time, and develop a deterministic volatility function (DVF) option valuation model that has the potential of fitting the observed cross section of option prices exactly. Using S&P 500 options from June 1988 through December 1993, we examine the predictive and hedging performance of the DVF option valuation model and find it is no better than an ad hoc procedure that merely smooths Black–Scholes (1973) implied volatilities across exercise prices and times to expiration.

Mean Reversion of Standard & Poor's 500 Index Basis Changes: Arbitrage‐induced or Statistical Illusion?

Published: 06/01/1994   |   DOI: 10.1111/j.1540-6261.1994.tb05149.x

MERTON H. MILLER, JAYARAM MUTHUSWAMY, ROBERT E. WHALEY

Mean reversion in stock index basis changes has been presumed to be driven by the trading activity of stock index arbitragers. We propose here instead that the observed negative autocorrelation in basis changes is mainly a statistical illusion, arising because many stocks in the index portfolio trade infrequently. Even without formal arbitrage, reported basis changes would appear negatively autocorrelated as lagging stocks eventually trade and get updated. The implications of this study go beyond index arbitrage, however. Our analysis suggests that spurious elements may creep in whenever the price‐change or return series of two securities or portfolios of securities are differenced.

Assessing Goodness‐of‐Fit of Asset Pricing Models: The Distribution of the Maximal R2

Published: 04/18/2012   |   DOI: 10.1111/j.1540-6261.1997.tb04814.x

F. DOUGLAS FOSTER, TOM SMITH, ROBERT E. WHALEY

The development of asset pricing models that rely on instrumental variables together with the increased availability of easily‐accessible economic time‐series have renewed interest in predicting security returns. Evaluating the significance of these new research findings, however, is no easy task. Because these asset pricing theory tests are not independent, classical methods of assessing goodness‐of‐fit are inappropriate. This study investigates the distribution of the maximal R2 when k of m regressors are used to predict security returns. We provide a simple procedure that adjusts critical R2 values to account for selecting variables by searching among potential regressors.