Faculty of Business Administration
Visiting Scholar Seminar
Equilibrium investment strategy with learning about equity return
Prof. Yongwu LI
Beijing University of Technology
Date: 9 December 2021, Thursday
Time: 11:00am – 12:00pm
Join from PC, Mac, Linux, iOS or Android: https://umac.zoom.us/j/92072425446?pwd=UTVjR2dXNVNYeWQ1UlE4MjdBMU1Ydz09
Passcode: 431572
Abstract
This paper investigates a dynamic investment decision problem with mean-variance criterion under partial information, where the stock return is assumed to consist of an observable factor and an unobservable factor, which both follow mean reversion processes. Through the Bayesian learning mechanism, the unobservable components of stock returns can be learned by investors from available information, including stock prices and observable returns. Due to lack of time consistency in dynamic investment decision problem with mean-variance criterion, we solve this problem by using a game theory approach developed in Bjork et al. (2017) [6] and seek the equilibrium investment strategy. Through the extended Hamilton-Jacobi-Bellman equation (HJB) equations system, we obtain the analytic solution of the dynamic mean-variance model. In addition, the influence of unobserved predictor and learning mechanism on the equilibrium investment strategy is also analyzed by utilizing numerical examples.
Biography
Prof. Yongwu Li is an associate professor in the School of Economics and Management, Beijing University of Technology. He received his Ph.D. from Lanzhou University and worked as a postdoctoral researcher at both the Chinese Academy of Sciences and Hong Kong Polytechnic University. His research focuses on financial asset allocation and risk management, optimal dividend distribution, pension fund investment management and insurance contract design. He has published in “Insurance: Mathematics and Economics”, “Journal of Optimization Theory and Applications”, “IEEE Systems Journal”, “Applied Stochastic Models in Business and Industry”, and “Operations Research Letters”.
