The Loan Fee Anomaly: A Short Seller's Best Ideas

• 成果类型: Article
• 署名作者: Engelberg, Joseph E.; Evans, Richard B.; Leonard, Greg; Reed, Adam, V; Ringgenberg, Matthew C.
• 署名单位: University of California System; University of California San Diego; University of Virginia; Virginia Polytechnic Institute & State University; University of North Carolina; University of North Carolina Chapel Hill; Utah System of Higher Education; University of Utah
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2023.00152
• 发表日期: 2025
• 页码: 5529-5551
• 关键词: Asset pricing anomalies; equity loan fees; Short selling

摘要

We find that equity loan fees, which have been largely ignored by the anomalies literature, are the best predictor of cross-sectional returns. When compared with 102 other anomalies and other short-selling measures, the loan fee anomaly has the highest monthly long-short return (4.01%), the highest monthly Sharpe Ratio (0.66), and, unlike other anomalies, exhibits strong persistence throughout the sample. Although prior work has shown that existing anomalies reside in high loan fee stocks, we find that 42% of loan fee outperformance is due to unique information not contained in other anomalies. Future papers that examine cross-sectional predictors of returns should include the single most effective predictor: loan fees.