报告题目：Evolution of Portfolio Optimization

报告时间：5月28日，星期一，下午4:00-5：00

报告地点：云顶国际4008服务平台北五楼319

报告人：Dr. Lianjie Shu, University of Macau

报告摘要：

The classical mean-variance portfolio model was originally proposed by Markowitz (1952). It has now undergone 65 years of development. In the mean-variance portfolio model, the mean and the covariance matrix of asset returns are often unknown and need to be estimated. However, the sampling errors have adverse effects on portfolio performance, leading to sub-optimal and unstable portfolio weights. Various strategies have been proposed to reduce the sampling errors. In this talk, both the traditional methods and some modern high-dimensional statistical approaches are widely reviewed. Moreover, a new approach based on the shrinkage of the sample eigenvalues is proposed, aimed at reducing the over-dispersion issue of the sample eigenvalues. The empirical studies show that the proposed approach can often achieve a lower out-of-sample variance and higher Sharpe ratio than the existing portfolio strategies in most real data sets.

报告人简介：

Dr. Lianjie Shu is currently Professor in Faculty of Business Administration at University of Macau. He received his Bachelor degree in Mechanical Engineering and Automation from Xi'an Jiao Tong University in 1998, and his Ph.D. in Industrial Engineering and Engineering Management from the Hong Kong University of Science and Technology (HKUST) in 2002. He currently serves an Associate Editor on Journal of Statistical Computation and Simulation and a Senior Editor on Journal of Industrial and Production Engineering. He is a senior member of American Society for Quality (ASQ), and also a senior member of Institute of Industrial Engineers (IIE). His recent research interests include portfolio optimization, high-dimensional statistics and monitoring, quality control and management, and statistical computing.