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On the Third Order Stochastic Dominance for Risk-Averse and Risk-Seeking Investors

Chan, Raymond H. andClark, Ephraim andWong, Wing-Keung(2012):On the Third Order Stochastic Dominance for Risk-Averse and Risk-Seeking Investors.

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    Abstract

    This paper studies some properties of stochastic dominance(SD) for risk-averse and risk-seeking investors, especially for the third order SD (TSD). We call the former ascending stochastic dominance (ASD) and the latter descending stochastic dominance(DSD). We first discuss the basic property of ASD and DSD linking the ASD and DSD of the first three orders to expected-utility maximization for risk-averse and risk-seeking investors. Thereafter, we prove that a hierarchy exists in both ASD and DSD relationships and that the higher orders of ASD and DSD cannot be replaced by the lower orders of ASD and DSD. Furthermore, we study conditions in which third order ASD preferences will be 'the opposite of' or 'the same as' their counterpart third order DSD preferences. In addition,we construct examples to illustrate all the properties developed in this paper. The theory developed in this paper provides investors with tools to identify first, second, and third order ASD and DSD prospects and thus they could make wiser choices on their investment decision.

    Item Type: MPRA Paper
    Original Title:On the Third Order Stochastic Dominance for Risk-Averse and Risk-Seeking Investors
    Language:English
    Keywords:Third order stochastic dominance, ascending stochastic dominance, descending stochastic dominance, expected-utility maximization, risk averters, risk seekers
    Subjects:D - Microeconomics >D8 - Information, Knowledge, and Uncertainty >D81 - Criteria for Decision-Making under Risk and Uncertainty
    G - Financial Economics >G1 - General Financial Markets >G11 - Portfolio Choice ; Investment Decisions
    C - Mathematical and Quantitative Methods >C0 - General >C02 - Mathematical Methods
    Item ID:42676
    Depositing User:Wing-Keung Wong
    Date Deposited:18 Nov 2012 13:52
    Last Modified:26 Sep 2019 16:09
    References:

    Anderson, G.J. (2004). Toward an Empirical Analysis of Polarization. Journal of Econometrics, 122, 1-26.

    Bawa, V.S. (1975), Optimma Rules for Ordering Uncertain Prospects, Journal of Financial Economics, 2, 95-121.

    Bawa, V.S., E.B., Lindenberg, L.C., Rafsky, (1979), Anefficient algorithm to determine stochastic dominance admissible sets, Management Science, 25(7), 609-622.

    Davies, J., Hoy, M., 1994. The normative significance of using 3rd-degree stochastic-dominance in comparing income distributions, Journal of economic theory 64(2), 520-530.

    Dillinger, A.M., Stein, W.E., Mizzi, P.J., 1992. Risk aversedecisions in business planning, Decision Sciences 23, 1003-1008.

    Eeckhoudt, L., and M., Kimball, (1992), Background risk,prudence, and the demand for insurance, Contributions to insurance economics, ed. by G. Dionne. Boston: Kluwer, 239-254.

    Fishburn, P.C. (1964), Decision and Value Theory, (New York: Wiley).

    Fishburn, P.C. (1974). Convex stochastic dominance withcontinuous distribution functions. Journal of Economic Theory, 7, 143-158.

    Fishburn, P., Vickson, R. (1978). Theoreticalfoundations of stochastic dominance. In G. Whitmore M. Findlay (Eds.), Stochastic dominance: An approach to decision-making under risk. Lexington: Lexington Books, D.C. Heath and Company.

    Fong, W.M., H.H. Lean, and W.K. Wong, 2008, StochasticDominance and Behavior towards Risk: The Market for Internet Stocks, Journal of Economic Behavior and Organization, 68(1), 194-208.

    Fong, W.M., W.K. Wong, and H.H. Lean, 2005, InternationalMomentum Strategies: A Stochastic Dominance Approach, Journal of Financial Markets, 8, 89-109.

    Gasbarro, D., W.K. Wong, and J.K. Zumwalt, 2007, Stochasticdominance analysis of iShares, European Journal of Finance 13, 89-101.

    J Gotoh, H Konno, 2000, Third degree stochastic dominance and mean-risk analysis, Management Science, 46, 2, 289-301.

    Hadar J., and Russell W.R. (1971), Stochastic Dominance andDiversification, Journal of Economic Theory 3, 288-305.

    Hammond, J.S. 1974. Simplifying the choice between uncertainprospects where preference is nonlinear. Management Science, 20(7), 1047-1072.

    Hanoch, G, H. Levy. 1969. The efficiency analysis of choicesinvolving risk. Review of Economic Studies, 36(3) 335-346.

    Michel Le Breton, Eugenio Peluso 2009. Third-degree stochastic dominance and inequality measurement. Journal of Economic Inequality, 7(3), 249-268.

    Levy, M., and H. Levy, 2002, Prospect Theory: Much Ado About Nothing? Management Science, 48(10), 1334-1349.

    Li, C.K., and W.K. Wong, (1999). Extension of StochasticDominance Theory to Random Variables, RAIRO RechercheOperationnelle, 33, 509-524.

    Menezes, C., Geiss, C., Tressler, J. (1980). Increasingdownside risk. American Economic Review, 70, 921–932.

    Meyer, J.(1977), Second Degree Stochastic Dominance with Respect to a Function, International Economic Review, 18, 476-487.

    Ng, M.C. (2000). A Remark on Third Degree Stochastic Dominance, Management Science, 46(6), 870-873.

    T Post, H Levy, 2005, Does risk seeking drive stock prices? A stochastic dominance analysis of aggregate investor preferences and beliefs, Review of Financial Studies 18(3), 925-953.

    T Post, P Versijp, 2007, Multivariate tests for stochasticdominance efficiency of a given portfolio, Journal of Financial and Quantitative Analysis, 42(2), 489-515.

    Quirk J.P.,and Saposnik R.(1962), Admissibility and Measurable Utility Functions, Review of Economic Studies, 29, 140-146.

    Rothschild, M. and Stiglitz, J.E. (1970), Increasing risk: I. A definition, Journal of Economic Theory 2, 225-243.

    Rothschild, M. and Stiglitz, J.E. (1971),Increasing risk: II. Its economic consequences, Journal of Economic Theory 3, 66-84.

    Schmid, F. 2005. A note on third degree stochastic dominance. OR SPECTRUM 27(4), 653-655.

    Stoyan, D. (1983), Comparison Methods for Queues and OtherStochastic Models, (New York: Wiley).

    Tesfatsion, L.(1976), Stochastic Dominance and Maximization of Expected Utility, Review of Economic Studies 43, 301-315.

    Thorlund-Petersen, L., 2001. Third-degree stochastic dominance and axioms for a convex marginal utility function, Mathematical Social Sciences 41(2), 167-199.

    von Neumann, John, and Oskar Morgenstern (1944), Theory of Games and Economic Behavior, Princeton University Press, Princeton N.J.

    Weeks, J.K., 1985. Stochastic dominance: a methodological approach to enhancing the conceptual foundations of operations management theory. Academy of Management Review 10(1), 31-38.

    Whitmore, G. A. (1970), Third-Degree Stochastic Dominance, American Economic Review 60(3), 457 - 59.

    Wong, W.K. (2007): Stochastic Dominance and Mean-VarianceMeasures of Profit and Loss for Business Planning and Investment, European Journal of Operational Research, 182, 829-843.

    Wong, W.K., and C.K. Li (1999): A Note on Convex Stochastic Dominance Theory, Economics Letters, 62,293-300.

    Wong, W.K., and C. Ma, 2008, Preferences over Meyer'slocation-scale family, Economic Theory 37(1), 119-146.

    R Zagst, J Kraus, 2011, Stochastic dominance of portfolioinsurance strategies, Annals of Operations Research 185, 75-103.

    URI:https://mpra.ub.uni-muenchen.de/id/eprint/42676

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