报告题目：Portfolio diversification and model uncertainty: a robust dynamic mean-variance approach

时间：2018年12月4日（周二）下午4:30

地点：南校区院系楼152会议室

主办单位：数学与统计学院

报告人：周超 博士

报告人简介：周超博士毕业于法国著名的巴黎九大和巴黎综合理工大学，现任新加坡国立大学量化金融中心研究员。主要研究领域：金融数学、随机控制。曾在多个国际权威的金融数学杂志上发表文章。

内容简介：This talk is concerned with multi-asset mean-variance portfolio selection problem under model uncertainty. We develop a continuous time framework for taking into account ambiguity aversion about both expected rate of return and correlation matrix of stocks, and for studying the effects on portfolio diversification. We prove a separation principle for the associated robust control problem formulated as a mean-field type differential game, which allows to reduce the determination of the optimal dynamic strategy to the parametric computation of the minimal risk premium function. Our results provide a justification for under-diversification, as documented in empirical studies, and that we explicitly quantify in terms of correlation and Sharpe ratio ambiguity parameters.  In particular, we show that an investor with a poor confidence in the expected return estimation does not hold any risky asset, and on the other hand, trades only one risky asset when the level of ambiguity on correlation matrix is large.