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Using the Shapley value of stocks as systematic risk

机译:利用福普利股票作为系统风险

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Purpose - This study aims to propose the Shapley value that originates from the game theory to quantify the relative risk of a security in an optimal portfolio. Design/methodology/approach - Systematic risk as expressed by the relative covariance of stock returns to market returns is an essential measure in pricing risky securities. Although very much in use, the concept has become marginalized in recent years because of the difficulties that arise estimating beta. The idea is that portfolios can be viewed as cooperative games played by assets aiming at minimizing risk. With the Shapley value, investors can calculate the exact contribution of each risky asset to the joint payoff. For a portfolio of three stocks, this study exemplifies the Shapley value when risk is minimized regardless of portfolio return. Findings - This study computes the Shapley value of stocks and indices for optimal mean-variance portfolios by using daily returns for the years 2016-2019. This results in the risk attributes allocated to securities in optimal portfolios. The Shapley values are analyzed and compared to the standard beta estimates to determine the ranking of assets with respect to pertinent risk and return. Research limitations/implications - An alternative approach to value risk and return in optimal portfolios is presented in this study. The logic and the mechanics of Shapley value theory in portfolio analysis have been explained, and its advantages relative to standard beta analysis are presented. Hence, financial analysts when adding or removing specific assets from present positions will have the true and exact impact of their actions by using the Shapley value instead of the beta. Practical implications - When computing the Shapley value, portfolio risk is decomposed exactly among its assets because it considers all possible coalitions of portfolios. In that sense, financial analysts when adding or removing specific securities from present holdings will be able to predict the true and exact impact of their transactions by using the Shapley value instead of the beta. The main implication for investors is that risk is ultimately priced relative to their holdings. This prevents the subjective mispricing of securities, as standard beta is not used and might allow investors to gain from arbitrage conditions. Originality/value - The logic and the methodology of Shapley value theory in portfolio analysis have been explained as an alternative to value risk and return in optimal portfolios by presenting its advantages relative to standard beta analysis. The conclusion is that the Shapley value theory contributes much more financial optimization than to standard systematic risk analysis because it enables looking at the contribution of each security to all possible coalitions of portfolios.
机译:目的 - 本研究旨在提出源于博弈论的福利价值,以量化最佳投资组合中安全性的相对风险。设计/方法论/方法 - 股票回报到市场回报的相对协方差所表达的系统风险是定价风险证券的重要措施。虽然在使用中非常多,但近年来,概念已经被估计估计β的困难。这个想法是,投资组合可以被视为旨在最大限度地减少风险的资产播放的合作游戏。通过福芙价值,投资者可以计算每个风险资产对联合收益的确切贡献。对于三个股票的投资组合,本研究表明,无论投资组合返回如何,风险最小化时福利值。调查结果 - 本研究通过使用2016 - 2019年的日期回报来计算最佳平均值组合的股票和指数的福利价值。这导致在最佳投资组合中分配给证券的风险属性。分析福利值并与标准测试估计进行比较,以确定关于相关风险和返回的资产排名。研究限制/含义 - 在本研究中介绍了价值风险和返回的替代方法。已经解释了福利价值理论在组合分析中的逻辑和力学,并提出了其相对于标准测试β分析的优点。因此,金融分析师在附加或移除当前职位的特定资产时,通过使用福谢价值而不是测试版,他们的行动将具有真实和确切的影响。实际意义 - 计算福利价值时,投资组合风险正恰好在其资产中分解,因为它考虑了所有可能的投资组合联盟。从这个意义上说,金融分析师在从目前的持有中添加或移除特定证券将能够通过使用福谢价值而不是测试版来预测交易的真实和确切的影响。投资者的主要含义是,风险最终是相对于其持股的价值。这可以防止证券的主观性错误,因为没有使用标准测试版,并且可能允许投资者从套利条件中获得。原创性/值 - 福利价值理论在投资组合分析中的逻辑和方法已被解释为价值风险的替代方案,并通过相对于标准测试β分析呈现其优点来返回最佳投资组合。结论是,福利价值理论贡献比标准系统风险分析更多的财务优化,因为它可以看出每个安全对投资组合的所有可能联盟的贡献。

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