Portfolio Optimization based on the Risk Minimization by the Weight-Modified CVaR vs. CVaR Method

M. E. Fadaeinejad, Mohamad Taghi Vaziri, Hossein Asadi, Mohammad Javad Faryadras
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Abstract

Given the lack of a specific approach to the explanation of values of optimal portfolio weights in the portfolio optimization, the present study aimed to examine large-scale portfolio optimization according to both stock weighting and utilization of SCAD function to minimize the portfolio risk based on the "weight-modified conditional value at risk (CVaR)" and its comparison with 71 Portfolio Optimization based on the Risk Minimization by... the "conditional value at risk (CVaR)" method in the Tehran Stock Exchange. Therefore, the price information of companies listed in the Tehran Stock Exchange and Over-the-counter (OTC) from 2012 to the end of September 2020 was collected, screened, and analyzed daily, and then the risk and return of the portfolios were examined by forming optimal portfolios. The results indicated that the efficiency limit of the stock portfolio and also the ranks of different companies were different according to the types of the optimization method. Based on the behavior of the TEDPIX, the investors' degrees of risktaking, and the risk management, diversification, and computational complexity of each method, the weight-modified CVaR had a better performance due to better diversification and risk management. Furthermore, the SCAD function added computational complexity to this method.
基于权重修正CVaR与CVaR方法的风险最小化投资组合优化
鉴于在投资组合优化中缺乏对最优投资组合权重值解释的具体方法,本研究旨在研究基于股票加权和利用SCAD函数最小化投资组合风险的大规模投资组合优化,并将其与基于风险最小化的71种投资组合优化进行比较。德黑兰证券交易所的“有条件风险值(CVaR)”方法。因此,每天收集2012年至2020年9月底在德黑兰证券交易所和场外交易(OTC)上市公司的价格信息,进行筛选和分析,然后通过形成最优投资组合来检验投资组合的风险和收益。结果表明,不同类型的优化方法所产生的股票投资组合的效率极限和不同公司的排名是不同的。综合考虑TEDPIX的行为、投资者的风险承担程度以及各方法的风险管理、分散化和计算复杂度,权重修正CVaR由于分散化和风险管理较好而具有较好的表现。此外,SCAD函数增加了该方法的计算复杂度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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