数学与统计学院学术报告[2023] 044号
(高水平大学建设系列报告815号)
报告题目: An Enhanced Factor Model for Portfolio Selection in High Dimensions
报告人： 舒连杰 教授（澳门大学）
报告时间：2023年 6 月 10日（周六）上午 10:30—11:30
报告地点：汇星楼514
报告内容: This paper extends Fama & French (FF) models of observed factors by introducing latent factors (LFs) to further extract information from FF residual returns. A diagonally dominant (DD) rather than a diagonal or sparse matrix structure is adopted in this study to estimate remaining covariance between disturbance terms. Such an enhanced factor (EF) model provides a more comprehensive analysis for portfolio selection in high dimensions, and also has certain advantages of estimation stability and computational efficiency. It is shown that the proposed EF-DD approach achieves overall better performance than competing models in terms of portfolio variance and the net Sharpe ratio.
报告人简历：Dr. Lianjie Shu is currently Professor in Faculty of Business Administration (FBA) at University of Macau. He received his Bachelor degree in Mechanical Engineering and Automation from Xi'an Jiao Tong University, and his Ph.D. in Industrial Engineering and Engineering Management from the Hong Kong University of Science and Technology (HKUST), respectively. Also, he currently serves an Associate Editor on Journal of Statistical Computation and Simulation. He is a senior member of Institute of Industrial and Systems Engineers (IISE) and American Society for Quality (ASQ). His recent research interests include Quantitative Finance, High-dimensional Statistics, and Statistical Quality Control. He has published more than 70 journal papers. His publications appear on a wide variety of journals such as Journal of Financial and Quantitative Analysis, Journal of Financial Econometrics, Journal of Empirical Finance, Quantitative Finance, Technometrics, Statistica Sinica, Naval Research Logistics, IISE Transactions, etc. He won the best application paper award in the IISE Transactions 2018.
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报告邀请人：周彦
数学与统计学院
2023年6月7日
