Using a dataset of 3,234 letters sent by 434 hedge funds to their investors during 1995-2011, we study what motivates hedge fund managers to make voluntary disclosures. Contrary to the hedge fund industry's reputation for opacity, we observe that managers provide their investors with an array of...

We take up Cochrane's (2011) challenge to identify the firm characteristics that provide independent information about average U.S. monthly stock returns by simultaneously including 94 characteristics in Fama-MacBeth regressions that avoid overweighting microcaps and adjust for data snooping...

Using a proprietary and unusually comprehensive database of hedge fund returns, we seek to identify abnormal performance consistent with opportunistic trading (e.g., bear raids) or synchronized actions (e.g., widespread forced liquidations) that could generate systemic risk. We find no evidence...

We study the economic importance of accounting information as defined by the value that a sophisticated investor can extract from publicly available financial statements when optimizing a portfolio of U.S. equities. Our approach applies the elegant new parametric portfolio policy method of...

This study speaks to investment academics and practitioners by describing and analyzing the population of return predictive signals (RPS) publicly identified during the period 1970-2010. Our supraview brings to light a number of new facts about the population of RPS, including that more than 330...

We separate the forecasted one-year-ahead stock return implied by an analyst's target price into two parts: the expected compensation for bearing risk, and analyst-claimed mispricing. We use the cost of equity disclosed by analysts in their reports for the former, and the difference between the...

This paper sheds light on how and why the stock market values high technology by examining the pricing of 606 biotechnology firms that were publicly traded at some time during the period 1989:q1-2000:q3. Contrary to the common view that the primary value drivers of biotechnology are...

In this paper I measure the importance of three groups of factors in the pricing of U.S. Internet stocks: economic fundamentals, web traffic, and supply and demand forces. Using log-linear regression on a panel of data for Net and non-Net stocks on 2/1/2000, I highlight five findings. First,...

This paper sheds light on the economics of Internet firms by extracting information on major value-drivers from their stock prices. Contrary to conventional Wall Street wisdom that there is little or no method in the pricing of Net stocks, I find that basic accounting data are highly...

This study uses out-of-sample equity value estimates to determine whether earnings disaggregation, imposing valuation model linear information (LIM) structure, and separate industry estimation of valuation model parameters aid in predicting contemporaneous equity values. We consider three levels...