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The Shapley Value Decomposition Of Optimal Portfolios

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  • Haim Shalit

    (BGU)

Abstract

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.
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Suggested Citation

  • Haim Shalit, 2017. "The Shapley Value Decomposition Of Optimal Portfolios," Working Papers 1701, Ben-Gurion University of the Negev, Department of Economics.
  • Handle: RePEc:bgu:wpaper:1701
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    References listed on IDEAS

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    1. Shalit, Haim, 2012. "Using OLS to test for normality," Statistics & Probability Letters, Elsevier, vol. 82(11), pages 2050-2058.
    2. Luigi Zingales, 1995. "What Determines the Value of Corporate Votes?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(4), pages 1047-1073.
    3. Riccardo Colini-Baldeschi & Marco Scarsini & Stefano Vaccari, 2018. "Variance Allocation and Shapley Value," Methodology and Computing in Applied Probability, Springer, vol. 20(3), pages 919-933, September.
    4. Schechtman, E. & Yitzhaki, S., 1999. "On the proper bounds of the Gini correlation," Economics Letters, Elsevier, vol. 63(2), pages 133-138, May.
    5. Shorrocks, A F, 1982. "Inequality Decomposition by Factor Components," Econometrica, Econometric Society, vol. 50(1), pages 193-211, January.
    6. Shalit, Haim & Yitzhaki, Shlomo, 1984. "Mean-Gini, Portfolio Theory, and the Pricing of Risky Assets," Journal of Finance, American Finance Association, vol. 39(5), pages 1449-1468, December.
    7. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    8. Karl Michael Ortmann, 2016. "The link between the Shapley value and the beta factor," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 39(2), pages 311-325, November.
    9. Lemaire, Jean, 1984. "An Application of Game Theory: Cost Allocation," ASTIN Bulletin, Cambridge University Press, vol. 14(1), pages 61-81, April.
    10. Samuelson, Paul A., 1967. "General Proof that Diversification Pays*," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 2(1), pages 1-13, March.
    11. Mercedes Sastre & Alain Trannoy, 2002. "Shapley inequality decomposition by factor components: Some methodological issues," Journal of Economics, Springer, vol. 77(1), pages 51-89, December.
    12. Merton, Robert C., 1972. "An Analytic Derivation of the Efficient Portfolio Frontier," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 7(4), pages 1851-1872, September.
    13. Haim Shalit & Shlomo Yitzhaki, 2005. "The Mean‐Gini Efficient Portfolio Frontier," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 28(1), pages 59-75, March.
    14. repec:ebl:ecbull:v:3:y:2007:i:25:p:1-7 is not listed on IDEAS
    15. Anthony Shorrocks, 2013. "Decomposition procedures for distributional analysis: a unified framework based on the Shapley value," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 11(1), pages 99-126, March.
    16. Stephane Mussard & Virginie Terraza, 2008. "The Shapley decomposition for portfolio risk," Applied Economics Letters, Taylor & Francis Journals, vol. 15(9), pages 713-715.
    17. Yitzhaki, Shlomo, 1982. "Stochastic Dominance, Mean Variance, and Gini's Mean Difference," American Economic Review, American Economic Association, vol. 72(1), pages 178-185, March.
    18. Haim Shalit & Shlomo Yitzhaki, 2003. "An Asset Allocation Puzzle: Comment," American Economic Review, American Economic Association, vol. 93(3), pages 1002-1008, June.
    19. virginie terraza & stephane mussard, 2007. "New trading risk indexes: application of the shapley value in finance," Economics Bulletin, AccessEcon, vol. 3(25), pages 1-7.
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    3. Haim Shalit, 2020. "The Shapley value of regression portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 21(6), pages 506-512, October.
    4. Bastien Lextrait, 2022. "Optimizing portfolios in the illiquid, unlisted market of SME crowdlending," EconomiX Working Papers 2022-23, University of Paris Nanterre, EconomiX.
    5. Patrick S. Hagan & Andrew Lesniewski & Georgios E. Skoufis & Diana E. Woodward, 2021. "Portfolio risk allocation through Shapley value," Papers 2103.05453, arXiv.org.

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    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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