{"title":"Weighted Shapley values of efficient portfolios","authors":"Haim Shalit","doi":"10.3233/rda-231507","DOIUrl":null,"url":null,"abstract":"Shapley value theory, which originally emerged from cooperative game theory, was established for the purpose of measuring the exact contribution of agents playing the game. Subsequently, the Shapley value was used in finance to decompose the risk of optimal portfolios, attributing to the various assets their exact contribution to total risk and return. In the present paper, the Shapley value results of Shalit [Annals of Finance 17(1) (2021), 1–25] are extended by using weighted Shapley values to decompose the risk of optimal portfolios. The weighted concept, as axiomatized by Kalai and Samet [Journal of Game Theory 16(3) (1987), 205–222], provides a solution to cooperative games when the symmetry of players cannot be justified. The weighted Shapley value theory is applied to model efficient mean-variance portfolios and price their constituents. The computation is carried out for the 13 most traded US stocks in 2020 and the results are compared with the standard Shapley values.","PeriodicalId":38805,"journal":{"name":"Risk and Decision Analysis","volume":"210 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Risk and Decision Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/rda-231507","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
引用次数: 0
Abstract
Shapley value theory, which originally emerged from cooperative game theory, was established for the purpose of measuring the exact contribution of agents playing the game. Subsequently, the Shapley value was used in finance to decompose the risk of optimal portfolios, attributing to the various assets their exact contribution to total risk and return. In the present paper, the Shapley value results of Shalit [Annals of Finance 17(1) (2021), 1–25] are extended by using weighted Shapley values to decompose the risk of optimal portfolios. The weighted concept, as axiomatized by Kalai and Samet [Journal of Game Theory 16(3) (1987), 205–222], provides a solution to cooperative games when the symmetry of players cannot be justified. The weighted Shapley value theory is applied to model efficient mean-variance portfolios and price their constituents. The computation is carried out for the 13 most traded US stocks in 2020 and the results are compared with the standard Shapley values.
Shapley价值理论起源于合作博弈论,其建立的目的是衡量参与博弈的代理人的确切贡献。随后,Shapley值在金融中被用于分解最优投资组合的风险,赋予各种资产对总风险和总收益的确切贡献。本文对Shalit [Annals of Finance 17(1)(2021), 1 - 25]的Shapley值结果进行扩展,采用加权Shapley值对最优投资组合的风险进行分解。Kalai和Samet [Journal of Game Theory, 16(3)(1987), 205-222]将加权概念公式化,为无法证明参与者对称性的合作博弈提供了解决方案。运用加权Shapley值理论对有效均值-方差组合进行建模,并对其组成部分进行定价。对2020年交易量最大的13只美国股票进行了计算,并将结果与标准Shapley值进行了比较。