No abstract

In portfolio analysis, uncertainty about parameter values leads to suboptimal portfolio choices. The resulting loss in the investor's utility is a function of the particular estimator chosen for expected returns. So, this is a problem of simultaneous estimation of normal means under a well-specified loss function. In this situation, as Stein has shown, the clas? sical sample mean is inadmissible. This paper presents a simple empirical Bayes estimator that should outperform the sample mean in the context of a portfolio. Simulation analysis shows that these Bayes-Stein estimators provide significant gains in portfolio selection problems.

This paper studies the hedging activities of 119 U.S. oil and gas producers from 1998 to 2001 and evaluates their effect on firm value. Theories of hedging based on market imperfections imply that hedging should increase the firm's market value (MV). To test this hypothesis, we collect detailed information on the extent of hedging and on the valuation of oil and gas reserves. We verify that hedging reduces the firm's stock price sensitivity to oil and gas prices. Contrary to previous studies, however, we find that hedging does not seem to affect MVs for this industry. Copyright 2006 by The American Finance Association.