Investor Behavior in the Option Market

This paper investigates the behavior of investors in the equity option market using a unique and detailed dataset of open interest and volume for all contracts listed on the Chicago Board Options Exchange over the 1990 through 2001 period. We document major stylized facts about the option market activity of three types of non-market maker investors over this time period and also investigate how their trading changed during the stock market bubble of the late 1990s and early 2000. Our key findings are: (1) non-market maker investors have about four times more long call than long put open interest, (2) these investors have more short than long open interest in both calls and puts, (3) each type of investor purchases more calls to open brand new positions when the return on underlying stocks are higher over horizons ranging from one week to two years into the past, (4) the least sophisticated group of investors substantially increased their purchases of calls on growth but not value stocks during the stock market bubble of the late 1990s and early 2000, and (5) none of the investor groups significantly increased their purchases of puts during the bubble period in order to overcome short sales constraints in the stock market.

Measuring Investment Distortions when Risk-Averse Managers Decide Whether to Undertake Risky Projects

This paper examines distortions in corporate investment decisions when a new project changes firm risk. It presents a dynamic model in which a self-interested, risk-averse manager makes investment decisions at a levered firm. The model, calibrated using data from public firms, is used to estimate the magnitude of distortions in investment decisions. Despite potential wealth transfers from debtholders, managers compensated with equity prefer safe projects to risky ones. Important factors in this decision are the expected changes in the values of future tax shields and bankruptcy costs when firm risk changes. We also evaluate the extent to which this effect varies with firm leverage, managerial risk aversion, managerial non-firm wealth, project size, debt duration, and the structure of management compensation packages.

Demand-Based Option Pricing

We model the demand-pressure effect on prices when options cannot be perfectly hedged. The model shows that demand pressure in one option contract increases its price by an amount proportional to the variance of the unhedgeable part of the option. Similarly, the demand pressure increases the price of any other option by an amount proportional to the covariance of their unhedgeable parts. Empirically, we identify aggregate positions of dealers and end users using a unique dataset, and show that demand-pressure effects help explain well-known option-pricing puzzles. First, end users are net long index options, especially out-of-money puts, which helps explain their apparent expensiveness and the smirk. Second, demand patterns help explain the prices of single-stock options.

Demand-Based Option Pricing

We model demand-pressure effects on option prices. The model shows that demand pressure in one option contract increases its price by an amount pro- portional to the variance of the unhedgeable part of the option. Similarly, the demand pressure increases the price of any other option by an amount propor- tional to the covariance of their unhedgeable parts. Empirically, we identify aggregate positions of dealers and end users using a unique dataset, and show that demand-pressure effects contribute to well-known option-pricing puzzles. In- deed, time-series tests show that demand helps explain the overall expensiveness and skew patterns of both index options and single-stock option

Clearly Irrational Financial Market Behavior: Evidence from the Early Exercise of Exchange Traded Stock Options

This paper analyzes the early exercise of Chicago Board Options Exchange listed calls by different classes of investors over the 1996-1999 period. We present two main findings. First, there are a large number of early exercises that can be identified as clearly irrational without invoking any model of market equilibrium, and these exercises are not uniformly distributed across the investor classes. Customers of discount brokers and customers of full service brokers both engage in a significant number of irrational exercises while traders at large investment houses exhibit no irrational early exercise behavior. Second, irrational exercise is triggered both by the underlying stock price attaining its highest level over the past year and by the underlying stock having high past returns. Our findings provide evidence that prospect theory is operative in the options market and that it applies differentially across various classes of investors.published or submitted for publicationnot peer reviewe

Forecasting Future Variance From Option Prices

Although it is widely believed that option prices provide the best possible forecasts of the future variance of the assets which underlie them, a large body of empirical evidence concludes that option prices consistently yield biased forecasts of future variance. The prevailing interpretation of these findings is that option investors may be forming unbiased forecasts of the future variance of underlying assets but that these unbiased forecasts fail to get impounded into option prices because of either (1) the difficulty of carrying out the necessary arbitrage strategies that would force the prices to their proper levels, or (2) the availability to market makers of lucrative alternative strategies in which they simply profit from the large bid-ask spreads in the options markets. This interpretation has significant consequences for nearly the entire range of option pricing research, since it implies that non-continuous trading, bid-ask spreads, and other market imperfections substantially influence option prices. This implication is important, both because incorporating these types of market imperfections into option pricing models is much more difficult than, for example, altering the dynamics of the underlying asset and also because it suggests that researchers cannot learn about option investor expectations by filtering option prices through available option pricing models. The present paper studies the variance forecasting ability of SPX option prices against the backdrop of the prevailing interpretation of the findings in the variance forecasting literature. The paper presents two main empirical findings. First, approximately one third of the usual bias is eliminated when high frequency futures data rather than daily closing data is used to construct measures of realized variance. Second, roughly another third of the bias disappears when forecasts of future variance are extracted from option prices via an option pricing model that ??? unlike the commonly employed model ??? permits a non-zero market price of variance risk and a non-zero correlation between innovations to the level and variance of the SPX index. Furthermore, the remaining bias is no longer significant. In addition to the empirical results, Monte Carlo simulations are performed to study the impact on the results of model misspecification and errors in the futures and options data. The simulations indicate that failure to account for a non-zero market price of variance risk produces a forecasting bias similar to that found in the previous literature when the conventional option pricing model is employed but that errors in the variables do not produce appreciable bias.published or submitted for publicationnot peer reviewe

Facing Up to Conditioned Diffusions

Most data used in finance are generated naturally rather than experimentally. While researchers are typically interested in estimates of model parameters that are not conditional on the particular sample, actual estimates are necessarily conditional on the data. Recent research on survivorship bias in equity returns and the estimation of term structure models from time-series of interest rate data suggests that failing to account for the implicit conditioning can seriously bias the results of empirical research. This paper develops theoretical and numerical tools that make it possible to account for the implicit conditioning when the underlying data are generated by a time-homogeneous univariate diffusion, and carries out a detailed analysis for three specific conditioning events that are of interest in finance. The techniques are illustrated by obtaining estimates of the drift and diffusion coefficients of a term-structure model from a standard time-series of interest rate data both with and without conditioning on these three events. The estimates indicate that the conditioning events have an important impact on the estimated drift coefficient but little effect on the estimated diffusion coefficient. A test statistic fails to reject linearity of the drift coefficient of the short rate process regardless of which of the conditioning events is assumed.published or submitted for publicationnot peer reviewe