i-manager Publications

Risk Assessment using Shapley Value and Comparing Results with Optimum Portfolio Weights

Aastha Gupta*

S & P Global Market Intelligence, Gurgaon, Haryana, India.

Periodicity:December - February'2020
DOI : https://doi.org/10.26634/jmgt.14.3.16639

Abstract

Every investor wants to know the risk of the assets they hold in a portfolio. Variance is commonly used for measuring risk and there are other tools as well. Yet, the modern analytical tools provide partial risk measure only. This paper includes a method for evaluating risk of an asset in a portfolio using cooperative game theory. In this approach, a portfolio of securities is viewed as a cooperative game played by securities, for which the risk they individually contribute to the portfolio can be determined. This value is known as the Shapley Value. It is calculated by computing the marginal utility of a player to the portfolio risk by looking at all the possible combination of coalitions in which the player would participate. The Shapley values of the assets so obtained are then compared with the weights of those assets in Global Minimum Variance Portfolio (GMPV). The historical data for assets have been taken for three sectoral indices of Indian Stock Exchange.

Keywords

Shapley Value, Portfolio Risk, Cooperative Games, Global Minimum Variance Portfolio (GMPV), Risk Assessment, Indian Stock Exchange.

How to Cite this Article?

Gupta, A. (2020). Risk Assessment using Shapley Value and Comparing Results with Optimum Portfolio Weights. i-manager's Journal on Management, 14(3), 20-24. https://doi.org/10.26634/jmgt.14.3.16639

References

[1]. Cao, Z. (2013). Multi-CoVar and shapley value: A systemic risk measure. Working Paper - Banque de France. (pp. 1-34).

[2]. Ferguson, T. S. (2014). Game Theory Part IV: Games in Coalitional Form.

[3]. Hamers, H., Husslage, B., Lindelauf, R. & Campen, T. (2016). A New Approximation Method for the Shapley Value Applied to the WTC 9/11 Terrorist Attack. Discussion Paper 2016-042, (CentER Discussion Paper; Vol. 2016-042). CentER, Center for Economic Research, Tilburg University.

[4]. Harsanyi J. C. (1977). Rational Behaviour and Bargaining Equilibrium in Games and Social Situations (pp. Ix-Xii). Cambridge: Cambridge University Press.

[5]. Kuhn, H. W., & Tucker, A. W. (Eds.). (1953). Contributions to the Theory of Games (Vol. 2). Princeton University Press.

[6]. Lamadrid, D. C. L., Ríos, D. G. R., Rodado, D. N., Negrete, K. P., & Niño, J. P. C. (2017). Shapley value: Its algorithms and application to supply chains. INGE CUC, 13(1), 57-66.

[7]. Lemaire, J. (1984). An application of game theory: Cost allocation. ASTIN Bulletin: The Journal of the IAA, 14(1), 61-81.

[8]. Mango, D.F. (1998).An application of game theory: Property catastrophe risk load. Insurance Mathematics and Economics, 20(3),157-186.

[9]. Markowitz, H. (1952). Portfolio selection. Journal of Finance, 7(1), 77-91.

[10]. Mussard, S., & Terraza, V. (2007). New trading risk indexes: Application of the Shapley value in finance. Economics Bulletin, 3(25), 1-7.

[11]. Mussard, S., & Terraza. V. (2008). The shapley decomposition for portfolio risk. Applied Economics Letters, 15(9), 713-715.

[12]. Narayanam, R., & Narahari, Y. (2010). A shapley value-based approach to discover influential nodes in social networks. IEEE Transactions on Automation Science and Engineering, 8(1), 130-147.

[13]. National Stock Exchange. (n.d.). Explore Our World of Indices.

[14]. PMI. (2008). The Standard for Portfolio Management - 2^nd Edition. Pennsylvania: Project Management Institute, Inc.

[15]. Shalit, H. (2017). The Shapley Value Decomposition Of Optimal Portfolios. Working Papers 1701, Department of Economics, Ben-Gurion University of the Negev.

[16]. Slišković, M., & Škrinjarić, T. (2019, January). Asset risk th evaluation using shapley value. In FEB Zagreb 10^th International Odyssey Conference on Economics and Business (pp. 509-518).

[17]. Von Neumann, J., & Morgenstern, O. (1944). Theory of Games and Economic Behavior (2^nd Ed.). Princeton, NJ: Princeton University Press.

	North Americas,UK, Middle East,Europe		India	Rest of world
	USD	EUR	INR	USD-ROW
Pdf	35	35	200	20
Online	15	15	200	15
Pdf & Online	35	35	400	25

Risk Assessment using Shapley Value and Comparing Results with Optimum Portfolio Weights

Abstract

Keywords

How to Cite this Article?

References

If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Options for accessing this content: