题目：Estimating Large Efficient Portfolios with Heteroscedastic Returns

主讲人：香港科技大学 李莹莹教授

主持人：西南财经大学统计学院 常晋源教授

时间：2020年6月16日（星期二）15:30-16:50

直播平台及会议ID：腾讯会议，798 538 577

报告摘要：

We study how to estimate large mean-variance efficient portfolios when asset returns can be heavy-tailed and conditionally heteroscedastic. Our proposed approach builds upon MAXSER (Ao, Li and Zheng (2019, RFS)) and utilizes robust statistical methods and random matrix theory under elliptical distribution. We show that our portfolio asymptotically achieves the maximum expected return and meanwhile meets the risk constraint. Simulation and empirical studies demonstrate superior properties of our approach.

主讲人简介：

Yingying Li is Professor at the Department of Information System, Business Statistics and Operations Management and the Department of Finance at Hong Kong University of Science and Technology (HKUST). Before joining HKUST, Dr Li also held positions as lecturer and postdoctoral fellow at the Bendheim Center for Finance and the Operations Research and Financial Engineering department at Princeton University.

Dr. Li’s research focuses on  high-dimensional and/or high-frequency financial data, volatility estimation and prediction, market microstructure, large portfolio optimization, individualized financial decision making, etc.  Dr. Li has published on top journals in finance, economics and statistics, such as Econometrica, Review of Financial Studies, Journal of Financial Economics, Annals of Statistics, Journal of American Statistical Association ...

She is an elected fellow of the Society for Financial Econometrics (SoFiE). She serves on the editorial boards of Journal of Econometrics, Journal of Business & Economic Statistics and Journal of Financial Econometrics.

Dr. Li received her BSc in Mathematics from Beijing Normal University, and Ph. D in Statistics from the University of Chicago.