Dynamic Mean-Variance Efficient Fractional Kelly Portfolios in a Stochastic Volatility Model
报告人： Xuedong He(The Chinese University of Hong Kong)
Fractional Kelly portfolios are popular investment strategies in the market. In this work, we improve the mean-variance efficiency of a fractional Kelly portfolio by minimizing the variance of the return of a portfolio subject to the constraint that the expected return rate of the portfolio is as high as that of the fractional Kelly portfolio. We consider so-called equilibrium portfolio strategies due to time inconsistency caused by the mean-variance criterion. We drive an equilibrium strategy in closed form and show that it reduces the variance of portfolio return compared to the fractional Kelly portfolio. Using real data, we show that the reduction can be economically significant. This is a joint work with Zhaoli Jiang.
About the Speaker:
Xuedong He is a professor in the Department of Systems Engineering and Engineering Management at the Chinese University of Hong Kong. He received the B.Sc. degree in Mathematics and Applied Mathematics from Peking University in 2005 and the Ph.D. degree in Mathematical Finance from the University of Oxford in 2009. He was an assistant professor at Columbia University in 2009--2015 and an associate professor at the Chinese University of Hong Kong in 2016--2022. Xuedong He's research interests include behavioral finance and economics, risk management, stochastic control, and financial technology. He has published papers in leading journals such as Management Science, Operations Research, Mathematical Finance, and Mathematics of Operations Research. He is serving as Associate Editors for Operations Research, Mathematics and Financial Economics, Operations Research Letters, and Digital Finance. He also organized clusters and sessions in international conferences such as the INFORMS Annual Meetings and SIAM Financial Mathematics and Engineering Conferences.
Tencent Meeting: https://meeting.tencent.com/dm/bmSLVZNncbRh
Your participation is warmly welcomed!