Topic: Opposing Styles as Ideologies
Speaker: Yushui Shi，Monash University
Time: Friday, October 8, 10:00–11:30 a.m.，Beijing Time
Place: Room 217, Guanghua Building 2
Combining machine learning with traditional economics, this paper explores whether retail investors’ opposing styles regarding a range of stock characteristics can be categorized by opposing investment ideologies such as “conservative” and “aggressive.” Based on the machine learning results of clustering investors into distinct groups, we construct a conservative-through- aggressive ideological index to capture investors’ dichotomous styles. We test the validity of such an index using out-of-sample survey data and show its relationship with other investor characteristics and behavioral biases. We further find that the conservative-through-aggressive ideological index negatively predicts individual performance and provides novel insights on the patterns of return comovements.
Coauthor: Yu-Jane Liu（Peking University）
Yushui Shi (施雨水) is Assistant Professor at the Department of Banking and Finance,Monash University. He received his Ph.D. in Finance from University of California, Irvine in 2021. He published in leading finance journals such as Journal of Financial Economics. His research focuses on empirical asset pricing, behavioral finance, financial network, and machine learning application on retail investor behavior. He also completed his Ph.D. and B.A. at Peking University.
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