We investigate the role of information in affecting a firm's cost of capital. We show that differences in the composition of information between public and private information affect the cost of capital, with investors demanding a higher return to hold stocks with greater private information. This higher return arises because informed investors are better able to shift their portfolio to incorporate new information, and uninformed investors are thus disadvantaged. In equilibrium, the quantity and quality of information affect asset prices. We show firms can influence their cost of capital by choosing features like accounting treatments, analyst coverage, and market microstructure.

A simple valuation model with time‐varying investment opportunities is developed and estimated. The model assumes that the investment opportunity set is completely described by the real interest rate and the maximum Sharpe ratio, which follow correlated Ornstein–Uhlenbeck processes. The model parameters and time series of the state variables are estimated using U.S. Treasury bond yields and expected inflation from January 1952 to December 2000, and as predicted, the estimated maximum Sharpe ratio is related to the equity premium. In cross‐sectional asset‐pricing tests, both state variables have significant risk premia, which is consistent with Merton's ICAPM.

We examine whether the market interprets changes in dividends as a signal about the persistence of past earnings changes. Prior to observing this signal, investors may believe that past earnings changes are not necessarily indicative of future earnings levels. We empirically investigate whether a change in dividends alters investors' assessments about the valuation implications of past earnings. Results confirm the hypothesis that changes in dividends cause investors to revise their expectations about the persistence of past earnings changes. This effect varies predictably with the magnitude of the dividend change and the sign of the past earnings change.

This paper documents that hedge funds did not exert a correcting force on stock prices during the technology bubble. Instead, they were heavily invested in technology stocks. This does not seem to be the result of unawareness of the bubble: Hedge funds captured the upturn, but, by reducing their positions in stocks that were about to decline, avoided much of the downturn. Our findings question the efficient markets notion that rational speculators always stabilize prices. They are consistent with models in which rational investors may prefer to ride bubbles because of predictable investor sentiment and limits to arbitrage.

We develop an arbitrage‐free and complete framework to price options on the stocks of firms involved in a merger or acquisition deal allowing for the possibility that the deal might be called off at an intermediate time, creating discontinuous impacts on the stock prices. Our model can be a normative tool for market makers to quote prices for options on stocks involved in such deals and also for traders to control risks associated with such deals using traded options. The results of tests indicate that the model performs significantly better than the Black–Scholes model in explaining observed option prices.

This paper develops a structural model that determines default spreads in a setting where the debt's collateral is endogenously determined by the borrower's investment choice, and a demand variable with permanent and temporary components. We also consider the possibility that the borrower cannot commit to taking the value‐maximizing investment choice, and may, in addition, be constrained in its ability to raise external capital. Based on a model calibrated to data on office buildings and commercial mortgages, we present numerical simulations that quantify the extent to which investment flexibility, incentive problems, and credit constraints affect default spreads.

Does the “smart money” effect documented by Gruber (1996) and Zheng (1999) reflect fund selection ability of mutual fund investors? We examine the finding that investors are able to predict mutual fund performance and invest accordingly. We show that the smart money effect is explained by the stock return momentum phenomenon documented by Jegadeesh and Titman (1993) . Further evidence suggests investors do not select funds based on a momentum investing style, but rather simply chase funds that were recent winners. Our finding that a common factor in stock returns explains the smart money effect offers no affirmation of investor fund selection ability.