题　目：Coevolution of Trader Networks and Follower Dynamics in Social Trading

嘉　宾：Mingwen Yang，助理教授，华盛顿大学

主持人：江浦平 助理教授 上海交通大学安泰经济与管理学院

时　间：2024年6月12日（周三）10:00-11:30am

地　点：腾讯会议（校内师生如需会议号和密码，请发邮件至yuxin.su@sjtu.edu.cn获取）

内容简介：

Social trading platforms have been gaining popularity against traditional mutual funds over the past few years. Compared to those on traditional financial markets, traders on social trading platforms often demonstrate more similar trading strategies. Rather than focusing solely on individual attributes, such as financial performance, we delve into the effects of strategy similarity patterns on the popularity of traders. We first construct similarity networks among traders, allowing for dynamic changes. Recognizing that similarity level could be a part of a trader's strategy, we employ a coevolution model to illustrate the interplay between the formation of traders' similarity networks and follower dynamics. We find that as the number of traders adopting similar strategies to a particular trader increases, the trader's number of followers and the total investment following her tend to decrease over time. We further validate our results with additional robustness checks. Our study identifies several managerial implications for social trading platforms.

演讲人简介：

Mingwen Yang is an Assistant Professor in Department of Information Systems & Operations Management at Michael G. Foster School of Business, University of Washington. Her current research interests are social trading, fintech, and cybersecurity. She received her PhD from Jindal School of Management, University of Texas at Dallas, and received Nunamaker-Chen Dissertation Award (Runner-up) from INFORMS Information Systems Society in 2019. Her work has been published in Management Science, Information Systems Research, MIS Quarterly, and Production and Operations Management.

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