Holder： Tengjia Shu（University of Illinois Chicago）
Time：2025-12-18 15:10-17:00
Location：Room 217, Guanghua Building 2
Abstract:
Are mutual fund managers skilled at exploiting asset pricing anomalies? I address this question using a customized machine learning framework that captures the interdependence between mutual funds and individual stocks while effectively handling multicollinearity. Based on the model, I find that although fund managers may hold anomaly-related stocks in either the correct or incorrect direction, intentionally or not, these positions do not enhance fund performance overall. However, the ability to extract value from anomalies varies meaningfully across fund types: value and quality funds, small funds, active managers, high-cost funds, and team-managed structures show stronger alignment with return-predictive anomalies, whereas growth funds, large funds, passive strategies, low-cost funds, and solo-managed funds tend to hold performance-detracting exposures. This paper bridges the literature on the “factor zoo" and mutual fund skill evaluation, offering new insights into both domains.
About the Speaker:
Tengjia Shu is an Assistant Professor of Finance at the University of Illinois Chicago. She received her Ph.D. in Finance from the University of Iowa. Her research interests are asset pricing, investments, machine learning, and labor economics.
Your participation is warmly welcomed!
欢迎扫码关注北大统计科学中心公众号，了解更多讲座信息!
