We propose a naïve model averaging (NMA) method that averages the OLS out-of-sample forecasts and the historical means and produces mostly positive out-of-sample R2s for the variables significant in sample in forecasting market returns. Surprisingly, more sophisticated weighting schemes that combine the predictive variable and historical mean do not consistently perform better. With unstable economic relations and a limited sample size, sophisticated methods may lead to overfitting or be subject to more estimation errors. In such situations, our simple methods may work better. Model misspecification, rather than declining return predictability, likely explains the predictive performance of the NMA method.

We study the relation between hedge fund equity holdings and measures of informational efficiency of stock prices derived from intraday transactions as well as daily data. Our findings support the role of hedge funds as arbitrageurs who reduce mispricing in the market. Hedge funds invest in stocks that are relatively inefficiently priced, and the price efficiency of these stocks improves after hedge funds increase their holdings. Hedge fund ownership contributes more to efficient pricing than ownership by other types of institutional investors. However, stocks held by hedge funds experienced large declines in price efficiency during several liquidity crises.Received July 27, 2016; editorial decision January 07, 2017 by Editor Wayne Ferson.

We examine the consistency of several prominent multifactor models from the empirical asset pricing literature with the arbitrage pricing theory (APT) framework. We follow the APT-related literature and estimate the common factor structure from a rich cross-section (associated with 42 major CAPM anomalies) by employing the asymptotic principal components method. Our benchmark model contains six statistical factors and clearly dominates, in both economic and statistical terms, most of the empirical multifactor models proposed in the literature by a good margin. These results represent a critical challenge to the current workhorse models in terms of explaining large-scale equity risk premiums. (JEL G10, G12) Received December 27, 2019; editorial decision October 20, 2020 by Editor Thierry Foucault.