False Discoveries in Mutual Fund Performance: Measuring Luck in Estimated Alphas

• 成果类型: Article
• 署名作者: Barras, Laurent; Scaillet, Olivier; Wermers, Russ
• 署名单位: McGill University; University of Geneva; University System of Maryland; University of Maryland College Park
• 刊物名称: JOURNAL OF FINANCE
• ISSN/ISSBN: 0022-1082
• DOI: 10.1111/j.1540-6261.2009.01527.x
• 发表日期: 2010
• 页码: 179-216
• 关键词: persistence; bootstrap; returns; regret; stocks; rates

摘要

This paper develops a simple technique that controls for false discoveries, or mutual funds that exhibit significant alphas by luck alone. Our approach precisely separates funds into (1) unskilled, (2) zero-alpha, and (3) skilled funds, even with dependencies in cross-fund estimated alphas. We find that 75% of funds exhibit zero alpha (net of expenses), consistent with the Berk and Green equilibrium. Further, we find a significant proportion of skilled (positive alpha) funds prior to 1996, but almost none by 2006. We also show that controlling for false discoveries substantially improves the ability to find the few funds with persistent performance.