When firms adjust their capital structures, they tend to move toward a target debt ratio that is consistent with theories based on tradeoffs between the costs and benefits of debt. In contrast to previous empirical work, out tests explicitly account for the fact that firms may face impediments to movements toward their target ratio, and that the target ratio may change over time as the firm's profitability and stock price change. A separate analysis of the size of the issue and repurchase transactions suggests that the deviation between the actual and the target ratios plays a more important role in the repurchase decision than in the issuance decision.

Extending an empirical technique developed in Easley, Kiefer, and O'Hara (1996), (1997a), we examine different hypotheses about stock splits. In line with the trading range hypothesis, we find that stock splits attract uninformed traders. However, we also find that informed trading increases, resulting in no appreciable change in the information content of trades. Therefore, we do not find evidence consistent with the hypothesis that stock splits reduce information asymmetries. The optimal tick size hypothesis predicts that stock splits attract limit order trading and this enhances the execution quality of trades. While we find an increase in the number of executed limit orders, their effect is overshadowed by the increase in the costs of executing market orders due to the larger percentage spreads. On balance, the uninformed investors' overall trading costs rise after stock splits.

Daily retutns are used to examine how mutual funds actively alter the risk of their portfolios in response to past performance. Compared to monthly data, daily returns produce much more efficient estimates of fund volatility, which give vastly different inferences about the behavior of fund managers. In particular, monthly results consistent with under-performers increasing their risk relative to better performing funds disappear with daily data. The differences in the monthly and daily results arise from biases in the monthly volatility estimates attributable to daily return autocorrelation.

This paper shows how to decompose the dollar profit earned from an option into two basic components: i) mispricing of the option relative to the asset at the time of purchase; and ii) profit from subsequent fortuitous changes or mispricing of the underlying asset. This separation hinges on measuring the “true relative value” of the option from its realized payoff. The payoff from any one option has a huge standard error about this value that can be reduced by averaging the payoff from several independent option positions. Simulations indicate that 95% reductions in standard errors can be further achieved by using the payoff of a dynamic replicating porfolio as a Monte Carlo control variate. In addition, the paper shows that these low standard errors are robust to discrete rather than continuous dynamic replication and to the likely degree of misspecification of the benchmark formula used to implement the replication.

Option mispricing profit can be futher decomposed into profit due to superior estimation of the volatility (volatility profit) and profit from using a superior option valuation formula (formula profit). To make this decomposition reiably, the benchmark formula used for the attribution needs to be similar to the formula implicitly used by the market to price options. If so, then simulation indicates that this further decomposition can be achieved with low standard errors. Basic component ii) can be further decomposed into profit from a forward contract of the underlying asset (asset profit) and what I term pure option profit. The asset profit indicates whether the investor was skillful by buying or selling options on mispriced underlying assets. However, asset profit could also simply be just compensation for bearing risk—a distinction beyond the scope of this paper. Although simulation indicates that the attrivution procedure gives an unbiased allocation of the option profit to this source, its standard error is large—a feature common with others' attempts to measure performance of asssets.

Public discussion about corporate use of derivatives focuses on whether firms use derivatives to reduce or increase firm risk. In contrast, empirical academic studies of corporate dervatives use take it for granted that firms hedge with derivatives. Using data from financial statements of 425 large U.S. corporations, we investigate whether firms systematically reduce or increase their riskiness with derivatives. We find that many firms manage their exposures with large derivatives positions. Nonetheless, compared to firms that do not use financial derivatives, firms that use derivatives display few, if any, measurable differences in risk that are associated with the use of derivatives.

Negative abnormal stock returns of about 1% occur near record dates of stock splits. Further, the lower the returns, the more positive are ex-date returns and when-issued premiums. A possible explanation of these related phenomena is that trading hindrances associated with record dates create trading inconvenience that is reflected in lower prices near record dates. In turn, anomalous positive ex-date returns arise in part from the abnormally low prices of unsplit shares caused by the negative record date returns.