Efficient Portfolio Estimation in Large Risky Asset Universes
Dr. Leheng CHEN
Post-Doctoral Fellow in Operations Management (Business Statistics)
HKUST Business School
The Hong Kong University of Science and Technology
Date: 20 May 2026 (Wednesday)
Time: 10:30-12:00
Venue: E22-G015
Host: Prof. Shen ZHAO, Associate Professor in Finance
Abstract
This paper introduces CORE (COnstrained sparse Regression for Efficient portfolios), a novel method for estimating the efficient portfolios from an investment universe composed exclusively of risky assets. We establish the asymptotic mean-variance efficiency of the CORE portfolio as both the number of assets and the sample size proportionally approach infinity. In extensive simulations and empirical studies on S&P 500 Index constituents, the CORE portfolio meets the specified risk levels, delivers superior Sharpe ratios, and outperforms various benchmarks both before and after transaction costs.
Speaker
Dr. Leheng CHEN is currently a Post-doctoral Fellow in the Department of Information Systems, Business Statistics and Operations Management at the Hong Kong University of Science and Technology (HKUST). He received his Ph.D. in Business Statistics from HKUST in August 2025, under the supervision of Professor Yingying Li and Professor Xinghua Zheng. His research interests lie at the intersection of asset pricing, financial econometrics, and high-dimensional statistics.
All are welcome!
