Knowledge that Transforms

This paper examines the effects of uncertainty about the stock return predictability on optimal dynamic portfolio choice in a continuous time setting for a longhorizon investor. Uncertainty about the predictive relation affects the optimal portfolio choice through dynamic learning, and leads to a state‐dependent relation between the optimal portfolio choice and the investment horizon. There is substantial market timing in the optimal hedge demands, which is caused by stochastic covariance between stock return and dynamic learning. The opportunity cost of ignoring predictability or learning is found to be quite substantial.

A long return history is useftil in estimating the current equity premium even if the historical distribution has experienced structural breaks. The long series helps not only if the timing of breaks is uncertain but also if one believes that large shifts in the premium are unlikely or that the premium is associated, in part, with volatility. Our framework incorporates these features along with a belief that prices are likely to move opposite to contemporaneous shifts in the premium. The estimated premium since 1834 fluctuates between four and six percent and exhibits its sharpest drop in the last decade.

Diversified firms have different values from comparable portfolios of single‐segment firms. These value differences must be due to differences in either future cash flows or future returns. Expected security returns on diversified firms vary systematically with relative value. Discount firms have significantly higher subsequent returns than premium firms. Slightly more than half of the cross‐sectional variation in excess values is due to variation in expected future cash flows, with the remainder due to variation in expected future returns and to covariation between cash flows and returns.

This paper studies a dynamic model of a financial market with a strategic trader. In each period the strategic trader receives a privately observed endowment in the stock. He trades with competitive market makers to share risk. Noise traders are present in the market. After receiving a stock endowment, the strategic trader is shown to reduce his risk exposure either by selling at a decreasing rate over time or by selling and then buying back some of the shares sold. When the time between trades is small, the strategic trader reveals the information regarding his endowment very quickly.

We study standard mutual fund performance measures, using simulated funds whose characteristics mimic actual funds. We find that performance measures used in previous mutual fund research have little ability to detect economically large magnitudes (e.g., three percent per year) of abnormal fund performance, particularly if a fund's style characteristics differ from those of the value‐weighted market portfolio. Power can be substantially improved, however, using event‐study procedures that analyze a fund's stock trades. These procedures are feasible using time‐series data sets on mutual fund portfolio holdings.

We investigate the expectations hypotheses of the term structure of interest rates and of the foreign exchange market using vector autoregressive methods for U.S. dollar, Deutsche mark, and British pound interest rates and exchange rates. We examine Wald, Lagrange multiplier, and distance metric tests by iterating on approximate solutions that require only matrix inversions. Bias‐corrected, constrained VARs provide Monte Carlo simulations. Wald tests grossly overreject the null, Lagrange multiplier tests slightly underreject, and distance metric tests overreject. A common interpretation emerges from the small sample statistics. The evidence against the expectations hypotheses is much less strong than under asymptotic inference.

The intertemporal CAPM predicts that an asset's price is equal to the expectation of the product of the asset's payoff and a representative consumer's intertemporal marginal rate of substitution. This paper develops an alternative approach to asset pricing based on corporations' desire to hoard liquidity. Our corporate finance approach suggests new determinants of asset prices such as the distribution of wealth within the corporate sector and between the corporate sector and the consumers. Also, leverage ratios, capital adequacy requirements, and the composition of savings affect the corporate demand for liquid assets and, thereby, interest rates.

We investigate the role of limit orders in the liquidity provision in a pure order‐driven market. Results show that market depth rises subsequent to an increase in transitory volatility, and transitory volatility declines subsequent to an increase in market depth. We also examine how transitory volatility affects the mix between limit orders and market orders. When transitory volatility arises from the ask (bid) side, investors will submit more limit sell (buy) orders than market sell (buy) orders. This result is consistent with the existence of limit‐order traders who enter the market and place orders when liquidity is needed.

This paper examines problems in the CRSP Survivor Bias Free U.S. Mutual Fund Database (CRSP, 1998) and compares returns contained in it to those in Morningstar. The CRSP database has an omission bias that has the same effects as survivorship bias. Although all mutual funds are listed in CRSP, return data is missing for many and the characteristics of these funds differ from the populations. The CRSP return data is biased upward and merger months are inaccurately recorded about half the time. Differences in returns in Morningstar and CRSP are a problem for older data and small funds.

Stocks and other financial assets are traded at prices that lie on a fixed grid determined by the minimum tick size. Observed prices and quoted spreads do not correspond to the equilibrium prices and true spreads that would exist in a market with no minimum tick size. Using Monte Carlo Markov Chain methods, this paper estimates the equilibrium prices and true spreads. For large stocks, most of the quoted spread is attributable to the rounding of prices and the adverse selection component is small. The true spread and the adverse selection component are greater for mid‐sized stocks.