Portfolio optimization with relative tail risk

IF 4.4 3区 管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Annals of Operations Research Pub Date : 2024-08-31 DOI:10.1007/s10479-024-06204-0
Young Shin Kim, Frank J. Fabozzi
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Abstract

This paper proposes analytic forms of portfolio conditional value at risk (CoVaR) and the mean of the portfolio loss conditional on it being in financial distress (CoCVaR) on the normal tempered stable market model. Since CoCVaR captures the relative risk of the portfolio with respect to a benchmark return, we apply it to relative portfolio optimization. Moreover, we derive analytic forms for the marginal contribution to CoVaR and the marginal contribution to CoCVaR. We discuss the Monte-Carlo simulation method for calculating CoCVaR and the marginal contributions of CoVaR and CoCVaR. We provide an empirical illustration to show relative portfolio optimization with 30 stocks included in the Dow Jones Industrial Average under distressed conditions. Finally, we apply the risk budgeting method to reduce the CoVaR and CoCVaR of the portfolio based on the marginal contributions to CoVaR and CoCVaR.

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具有相对尾部风险的投资组合优化
本文在正态节制稳定市场模型上提出了投资组合条件风险价值(CoVaR)和处于财务困境条件下的投资组合损失均值(CoCVaR)的分析形式。由于 CoCVaR 反映了投资组合相对于基准收益的相对风险,因此我们将其应用于相对投资组合优化。此外,我们还推导出了 CoVaR 的边际贡献和 CoCVaR 的边际贡献的解析形式。我们讨论了计算 CoCVaR 以及 CoVaR 和 CoCVaR 边际贡献的蒙特卡洛模拟方法。我们提供了一个经验图解,展示了在困境条件下,道琼斯工业平均指数中 30 种股票的相对投资组合优化。最后,我们应用风险预算方法,根据 CoVaR 和 CoCVaR 的边际贡献降低投资组合的 CoVaR 和 CoCVaR。
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来源期刊
Annals of Operations Research
Annals of Operations Research 管理科学-运筹学与管理科学
CiteScore
7.90
自引率
16.70%
发文量
596
审稿时长
8.4 months
期刊介绍: The Annals of Operations Research publishes peer-reviewed original articles dealing with key aspects of operations research, including theory, practice, and computation. The journal publishes full-length research articles, short notes, expositions and surveys, reports on computational studies, and case studies that present new and innovative practical applications. In addition to regular issues, the journal publishes periodic special volumes that focus on defined fields of operations research, ranging from the highly theoretical to the algorithmic and the applied. These volumes have one or more Guest Editors who are responsible for collecting the papers and overseeing the refereeing process.
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