Out-of-Sample Performance of Mutual Fund Predictors

• 成果类型: Article
• 署名作者: Jones, Christopher S.; Mo, Haitao
• 署名单位: University of Southern California; Louisiana State University System; Louisiana State University
• 刊物名称: REVIEW OF FINANCIAL STUDIES
• ISSN/ISSBN: 0893-9454
• DOI: 10.1093/rfs/hhaa026
• 发表日期: 2021
• 页码: 149
• 关键词: cross-section; costly information; HOT HANDS; strategies; returns; MANAGER; skill; size; persistence; EFFICIENCY

摘要

We analyze the out-of-sample performance of variables shown to forecast future mutual fund alphas. The degree of predictability, as measured by alpha spreads from quintile sorts or cross-sectional regression slopes, falls by at least half post-sample. These declines appear to be primarily the result of changes in the level of arbitrage activity in the market, with mutual fund competition appearing to play a secondary role. We find no evidence that the declines are the result of data snooping or learning by investors or fund managers. Finally, we show that corporate bond fund performance exhibits similar dependence on measures of bond market arbitrage activity.