Investors want the ability to evaluate the true and complete risk of the financial assets held in a portfolio. Yet, the current analytic methods provide only partial risk measures. I suggest that, by viewing a portfolio of securities as a cooperative game played by the assets that minimize portfolio risk, investors can calculate the exact value, each security contributes to the common payoff of the game, which is known as the Shapley value. It is determined by computing the contribution of each asset to the portfolio risk by looking at all the possible coalitions in which the asset would participate. I develop this concept in order to decompose the risk of mean-variance and mean-Gini efficient portfolios. This decomposition gives us a better rank of assets by their comprehensive contribution to the risk of optimal portfolios. Such a procedure allows investors to make unbiased decisions when they analyze the inherent risk of their holdings. The Shapley value is calculated for index classes and the empirical results based on asset allocation data are contrary to some of the findings of conventional wisdom and beta analysis.

投资者希望能够评估投资组合中所持有金融资产的真实和完整风险。但是，当前的分析方法仅提供部分风险度量。我建议，通过将证券投资组合看成是一种资产最小化的资产所扮演的合作博弈，投资者可以计算出确切的价值，每种证券都有助于博弈的共同收益，即所谓的Shapley价值。它是通过查看资产将参与的所有可能的联盟来计算每种资产对投资组合风险的贡献来确定的。我提出这个概念是为了分解均值方差和均值基尼有效投资组合的风险。通过对最佳投资组合风险的全面贡献，这种分解为我们提供了更好的资产等级。这样的程序使投资者在分析其持有的内在风险时可以做出公正的决定。Shapley值是针对指数类别计算的，基于资产分配数据的经验结果与传统观点和Beta分析的某些发现相反。