This paper builds on recent empirical studies that document the general impact of analyst recommendations on mutual fund trading. We argue that the use of analyst research might be a strategic decision depending on the type of mutual fund. Therefore, we identify the funds that trade in...

I use machine learning methods to identify stock characteristics important for predicting both stock returns and mutual fund performance. My customized machine learning models can successfully predict both stock returns and fund performance, and a nonlinear model delivers better performance....

The 52-week high share price has been shown by George and Hwang (2004) to carry significant predictive ability for individual stock returns, dominating other common momentum-based trading strategies. This study examines the performance of trading strategies for mutual funds based on (1) an...

This study applies an innovative return-based approach to determine the style-shifting activity of mutual funds. Based on daily returns, we measure style-shifting activity as inter-quarterly changes in the style exposures of a fund. In order to test the robustness of style-shifting activity we...

Change point models using hierarchical priors share in the information of each regime when estimating the parameter values of a regime. Because of this sharing, hierarchical priors have been very successful when estimating the parameter values of short-lived regimes and predicting the...

A great deal of research effort has sought to understand whether fund managers have skill. However, most of this research draws inferences from fund returns attributable to funds that may have been managed by many different managers over the years. In this paper we focus on the fund manager. We...

We propose and test a methodological framework to examine the relation between mutual fund fees and return predictability. Gil-Bazo and Ruiz-Verdu (2009) drew attention to the puzzling fact that funds with worse before-fee performance charge higher fees. We make another contribution to the...

Stock momentum, long-term reversal, and other past return characteristics that predict future returns also predict future realized betas, suggesting these characteristics capture time-varying risk compensation. We formalize this argument with a conditional factor pricing model. Using...

This study introduces an innovative approach to measuring the “style-shifting activity” (SSA) of mutual funds using daily returns. Applying our new measure to a comprehensive sample of 2631 active US equity mutual funds, we show (i) that SSA predicts future performance, especially for...

We compare the stock return forecasting performance of alternative payout yields. The net payout yield produces more accurate forecasts relative to alternatives, including the traditional dividend yield. This remains true even after excluding several years during the Great Depression when...