This paper investigates options market reaction to changes in the instantaneous variance of the underlying asset. There are three main findings. First, options market investors underreact to individual daily changes in instantaneous variance. Second, these same investors overreact to periods of mostly increasing or mostly decreasing daily changes in instantaneous variance. Third, they tend to underreact (overreact) to current daily changes in instantaneous variance that are preceded mostly by daily changes of the opposite (same) sign. The third finding can reconcile the first two and is also consistent with well‐established cognitive biases.

We present strong evidence that option trading volume contains information about future stock prices. Taking advantage of a unique data set, we construct put-call ratios from option volume initiated by buyers to open new positions. Stocks with low put-call ratios outperform stocks with high put-call ratios by more than 40 basis points on the next day and more than 1% over the next week. Partitioning our option ignals into components that are publicly and nonpublicly observable, we find that the economic source of this predictability is nonpublic information possessed by option traders rather than market inefficiency. We also find greater predictability for stocks with higher concentrations of informed traders and from option contracts with greater leverage.

This paper analyzes the early exercise of exchange‐traded options by different classes of investors over the 1996 to 1999 period. A large number of exercises are identified as clearly irrational without invoking any model of market equilibrium. Customers of discount brokers and customers of fullservice brokers both engage in a significant number of irrational exercises while traders at large investment houses exhibit no irrational early exercise behavior. Rational and irrational exercise is triggered for discount and full‐service customers by the underlying stock price attaining its highest level over the past year and by high returns on the underlying stock.

[We model demand-pressure effects on option prices. 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 the unhedgeable parts of the two options. Empirically, we identify aggregate positions of dealers and end-users using a unique dataset, and show that demand-pressure effects make a contribution to wellknown option-pricing puzzles. Indeed, time-series tests show that demand helps explain the overall expensiveness and skew patterns of index options, and cross-sectional tests show that demand impacts the expensiveness of single-stock options as well.]

We present strong evidence that option trading volume contains information about future stock prices. Taking advantage of a unique data set, we construct put-call ratios from option volume initiated by buyers to open new positions. Stocks with low put-call ratios outperform stocks with high put-call ratios by more than 40 basis points on the next day and more than 1% over the next week. Partitioning our option signals into components that are publicly and nonpublicly observable, we find that the economic source of this predictability is nonpublic information possessed by option traders rather than market inefficiency. We also find greater predictability for stocks with higher concentrations of informed traders and from option contracts with greater leverage.

[This article uses a unique option data set to provide detailed descriptive statistics on the purchased and written open interest and open buy and sell volume of several classes of investors. We also show that volatility trading through straddles and strangles accounts for a small fraction of option trading volume and presents evidence that a large percentage of call writing is part of covered call positions. Finally, we find that during the stock market bubble of the late 1990s and early 2000 the least sophisticated investors in the data set substantially increased their purchases of calls on growth but not value stocks.]

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.

There are a number of circumstances in finance in which it is useful to estimate diffusion processes conditional on some event. In this paper, we develop the theoretical and numerical tools necessary to perform conditional estimation of diffusion processes within a generalized method of moments framework. We illustrate our method by estimating a univariate diffusion process for a standard time-series of interest rate data conditioned to remain between lower and upper boundaries. A test statistic fails to reject by a wide margin the linearity of the conditionally estimated drift coefficient.

Abstract This paper examines optimal capital structure choice using a dynamic capital structure model that is calibrated to reflect actual firm characteristics. The model uses contingent claim methods to value interest tax shields, allows for reorganization in bankruptcy, and maintains a long-run target debt to total capital ratio by refinancing maturing debt. Using this model, we calculate optimal capital structures in a realistic representation of the traditional trade-off model. In contrast to previous research, the calculated optimal capital structures do not imply that firms tend to use too little leverage in practice. We also estimate the costs borne by a firm whose capital structure deviates from its optimal target debt to total capital ratio. The costs of moderate deviations are relatively small, suggesting that a policy of adjusting leverage infrequently is likely to be reasonable for many firms.

This article uses a unique option data set to provide detailed descriptive statistics on the purchased and written open interest and open buy and sell volume of several classes of investors. We also show that volatility trading through straddles and strangles accounts for a small fraction of option trading volume and presents evidence that a large percentage of call writing is part of covered call positions. Finally, we find that during the stock market bubble of the late 1990s and early 2000 the least sophisticated investors in the data set substantially increased their purchases of calls on growth but not value stocks. (JEL: G0, G1, G12, G13, G14)