Green and Hollifield (1992) argue that the presence of a dominant factor would result in extreme negative weights in mean-variance efficient portfolios even in the absence of estimation errors. In that case, imposing no-short-sale constraints should hurt, whereas empirical evidence is often to...

We find that on average, an announcement of rising unemployment is good news for stocks during economic expansions and bad news during economic contractions. Unemployment news bundles three types of primitive information relevant for valuing stocks: information about future interest rates, the...

Knowledge of the one-month interest rate is useful in forecasting the sign, as well as the variance, of the excess return on stocks. The services of a portfolio manager who makes use of the forecasting model to shift funds between bills and stocks would be worth an annual management fee of 2...

In measuring performance persistence, we use hedge fund style benchmarks. This allows us to identify managers with valuable skills, and also to control for option-like features inherent in returns from hedge fund strategies. We take into account the possibility that reported asset values may be...

The authors find support for a negative relation between conditional expected monthly return and conditional variance of monthly return using a GARCH-M model modified by allowing (1) seasonal patterns in volatility, (2) positive and negative innovations to returns having different impacts on...

Without the assumption of conditional homoskedasticity, a general asymptotic distribution theory for the two-stage cross-sectional regression method shows that the standard errors produced by the Fama-MacBeth procedure do not necessarily overstate the precision of the risk premium estimates....

The stochastic discount factor (SDF) method provides a unified general framework for econometric analysis of asset-pricing models. There have been concerns that, compared to the classical beta method, the generality of the SDF method comes at the cost of efficiency in parameter estimation and...