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An Efficient Approach to High-Dimensional Portfolio Optimization in Volatile Markets

作者: 发布时间:2024-05-20 点击数:
主讲人:杨松山
主讲人简介:

杨松山,中国人民大学统计与大数据研究院助理教授、博士生导师。研究兴趣包括高维数据分析,模型算法优化,机器学习以及统计模型在金融学、生理学和心理学中的应用。在JASA、JOE、JCGS等国际统计学期刊发表十余篇文章。

主持人:刘婧媛
讲座简介:

With the global financial market experiencing continuous expansion and escalating volatility, the development of efficient strategies for high-dimensional portfolio allocation has become critically important. Previous approaches to high-dimensional portfolio selection have mainly focused on large-cap companies, presenting challenges when confronted with datasets such as the Russell 2000 index. This paper aims to address portfolio optimization challenges within this context, using the 2020-2021 U.S. stock market as a case study. We propose a Dantzig-type portfolio optimization (DPO) model, and present efficient parallel computing algorithms based on asset-splitting. Through empirical analysis on the S&P 500 and Russell 2000 indices, we demonstrate the consistent outperformance of the DPO portfolios over Markowitz mean-variance and Lasso-type mean-variance models, as well as corresponding ETFs, in terms of Sharpe and Sortino ratios. This outperformance is particularly pronounced for the Russell 2000 index. We provide a new effective approach for investors seeking to optimize their portfolios in complex market environments.

时间:2024-05-27 (Monday) 16:40-18:10
地点:经济楼N302
讲座语言:中文
主办单位:永利集团3044官网欢迎您、王亚南经济研究院、邹至庄经济研究院
承办单位:
期数:
联系人信息:周梦娜:2182886,zmn1994@xmu.edu.cn
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