A dynamic model of strategic trading with two asymmetrically informed traders is analyzed where one informed trader knows the information seen by both informed traders, and the other informed trader only knows his private information. While the first informed trader is better informed, the second informed trader can make inferences about this extra information; in fact, the second informed trader can make sharper inferences from the order flow than the market maker about the extra information. In this setting, competition among the informed traders has a very interesting form. The informed trader with the additional information trades less intensely on that information early on, and both informed traders trade very intensely on their common information. This makes it more difficult for the trader with less information to learn about the information he does not have. When there are only a few remaining trading periods and the information known to both traders has largely been revealed through their trading, then the trader with the additional information trades more intensely on the basis of his private information.

This paper addresses the problem of testing financial models in the presence of market micro structure effects. The moment restrictions implied by the financial and market microstructure models are jointly tested using Hansen's (1982) GMM approach. To illustrate the methodology, I consider the random walk model in combination with the bid-ask price effect model of Blume and Stambaugh (1983). Within this sufficiently simple framework, I obtain closed-form expressions for the estimators, standard errors of the estimators, and the test statistic, which affords an opportunity to examine the precision of the estimators and the power of the test as the return interval increases. I show that apparent rejections of the random walk model cannot be sustained when tests of the model are adjusted for market micro structure effects, and I discuss other applications of the methodology.

We examine 38 takeovers of distressed firms and find that these takeovers are more likely to involve firms in the same industry and less likely to be hostile takeovers than are acquisitions in general. We use five different measures to evaluate post-merger performance of the combined bidder and target firms. All performance measures suggest that bidders are unable to successfully restructure targets. The market demonstrates an ability to forecast the success of restructuring. Restructuring success is negatively related to the size of premium paid by the bidder for the target and positively related to the financial distress of the target.

We examine the cash flow signaling, overinvestment, and dividend clientele explanations for the information content of dividend change announcements. After simultaneously controlling for the standardized dividend change, dividend yield, and Tobin's Q, we find that announcement period excess returns are positively related to the magnitude of the standardized dividend change and to the dividend yield, but unrelated to Tobin's Q. We provide further evidence on the cash flow signaling and overinvestment hypotheses by examining revisions in analysts' earnings forecasts and changes in capital expenditures following dividend change announcements. We find that analysts significantly revise their earnings forecasts following dividend changes and that Q < 1 firms actually increase their capital expenditures following dividend increases and decrease them following dividend decreases. Overall, our findings support the cash flow signaling and dividend clientele hypotheses for stock price reactions to dividend change announcements, but provide little support for the overinvestment hypothesis.

This paper examines alternative methods for pricing options when the underlying security volatility is stochastic. We show that when there is no correlation between innovations in security price and volatility, the characteristic function of the average variance of the price process plays a pivotal role. It may be used to simplify Fourier option pricing techniques and to implement simple power series methods. We compare these methods for the alternative mean-reverting stochastic volatility models introduced by Stein and Stein (1991) and Heston (1993). We also examine the biases in the Black-Scholes model that are eliminated by allowing for stochastic volatility, and we correct some errors in the Stein and Stein (1991) analysis of this issue.

This paper studies the diversifiability of jumps in stock returns. It presents a multivariate time-series model of the stochastic process for an index and its component stocks that explicitly admits discrete common jumps. Maximum likelihood estimation for such a model is developed and applied to the daily Major Market Index and its component stocks for the period 1985 through 1990. The paper finds that Poisson-distributed jumps observed from both the index and its component stocks constitute nondiversifiable risk, implying that the standard assumption in option pricing that these jumps are not priced may be invalid.

Using intraday data, we find that bank announcements of changes in the prime rate have significant effects on Dow Jones stock price indexes and yields in the Treasury bill futures market. We find comparable effects using daily data for indexes of share prices of banks and financial firms as well as interest rates on various maturities of government securities. Our evidence is consistent with the view that banks have a comparative advantage in processing private information gained through bank-borrower relations and the regulatory supervision process.