CVaR-cardinality enhanced indexation optimization with tunable short-selling constraints. Issue 3 (6th February 2021)

• Record Type: Journal Article
• Authors: Zhao, Zhihua; Wang, Hao; Yang, Xiangyu; Xu, Fengmin
• Is Part Of: Applied economics letters. Volume 28:Issue 3(2021)
• Page Start: 201
• Page End: 207
• Publication Date: 2021-02-06
• Subjects: Enhanced indexation -- CVaR -- cardinality -- out-of-sample analysis -- mixed-integer program; G11 -- C44 -- C61; Economics -- Periodicals; Economics, Mathematical -- Periodicals; 330
• DOI: 10.1080/13504851.2020.1740156
• Languages: English
• ISSNs: 1350-4851

Abstract

ABSTRACT: Enhanced-index-funds have attracted considerable attention from investors over the last decade, which aims at outperforming a benchmark index while maintaining a similar risk level. In this article, we investigate an enhanced indexation methodology using Conditional Value-at-Risk (CVaR). In particular, we adopt CVaR of excess returns as risk measurement subject to cardinality constraint for controlling the tracking portfolio scale precisely and tunable short-selling constraints for adjusting the margin of each risky asset adaptively within the budget of short-selling. As the resulted model is a mixed 0–1 binary program, we propose an improved hybrid heuristic method, where a customized relax-round-polish is embedded to improve the quality of the iterative population. Computational results on five standard data sets from OR-library show that our proposed method is generally superior to the naive portfolio strategy and the CVaR-LASSO method in terms of the out-of-sample excess return, Sharpe ratio and maximum drawdown of the portfolio.