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Risk Measures from Risk-Reducing Experiments

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  • Philippe Delquié

    (The George Washington University School of Business, Washington, DC 20052)

Abstract

This paper introduces the concept of risk-reducing experiments as a basis for designing risk measures. A risk-reducing experiment provides the option to mitigate the impact of less favorable outcomes in a gamble, and the gamble's risk is measured as the increase in value brought about by such an experiment. Two examples are presented, including one based on the concept of expected value of perfect information. Both examples yield familiar risk measures, and extensions of them are discussed. A risk measure derived from a risk-reducing experiment makes explicit the sense in which the riskiness of a gamble is captured. Risk-reducing experiments offer a new approach for conceiving, or choosing among, risk measures.

Suggested Citation

  • Philippe Delquié, 2012. "Risk Measures from Risk-Reducing Experiments," Decision Analysis, INFORMS, vol. 9(2), pages 96-102, June.
  • Handle: RePEc:inm:ordeca:v:9:y:2012:i:2:p:96-102
    DOI: 10.1287/deca.1120.0232
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    References listed on IDEAS

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    1. Fishburn, Peter C, 1977. "Mean-Risk Analysis with Risk Associated with Below-Target Returns," American Economic Review, American Economic Association, vol. 67(2), pages 116-126, March.
    2. Dean P. Foster & Sergiu Hart, 2009. "An Operational Measure of Riskiness," Journal of Political Economy, University of Chicago Press, vol. 117(5), pages 785-814.
    3. Ogryczak, Wlodzimierz & Ruszczynski, Andrzej, 1999. "From stochastic dominance to mean-risk models: Semideviations as risk measures," European Journal of Operational Research, Elsevier, vol. 116(1), pages 33-50, July.
    4. 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.
    5. Pyatt, Graham, 1976. "On the Interpretation and Disaggregation of Gini Coefficients," Economic Journal, Royal Economic Society, vol. 86(342), pages 243-255, June.
    6. Acerbi, Carlo & Tasche, Dirk, 2002. "On the coherence of expected shortfall," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1487-1503, July.
    7. Hiroshi Konno & Hiroaki Yamazaki, 1991. "Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market," Management Science, INFORMS, vol. 37(5), pages 519-531, May.
    8. Yitzhaki, Shlomo, 1983. "On an Extension of the Gini Inequality Index," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 24(3), pages 617-628, October.
    9. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    10. Rothschild, Michael & Stiglitz, Joseph E., 1970. "Increasing risk: I. A definition," Journal of Economic Theory, Elsevier, vol. 2(3), pages 225-243, September.
    11. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    12. Stone, Bernell K, 1973. "A General Class of Three-Parameter Risk Measures," Journal of Finance, American Finance Association, vol. 28(3), pages 675-685, June.
    13. Hans Föllmer & Alexander Schied, 2002. "Convex measures of risk and trading constraints," Finance and Stochastics, Springer, vol. 6(4), pages 429-447.
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