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Vigilant Measures of Risk and the Demand for Contingent Claims

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  • Mario Ghossoub

Abstract

I examine a class of utility maximization problems with a not necessarily law-invariant utility, and with a not necessarily law-invariant risk measure constraint. The objective function is an integral of some function U with respect to some probability measure P, and the constraint set contains some risk measure constraint which is not necessarily P-law-invariant. This introduces some heterogeneity in the perception of uncertainty. The primitive U is a function of some given underlying random variable X and of a contingent claim Y on X. Many problems in economic theory and financial theory can be formulated in this manner, when a heterogeneity in the perception of uncertainty is introduced. Under a consistency requirement on the risk measure that will be called Vigilance, supermodularity of the primitive U is sufficient for the existence of optimal continent claims, and for these optimal claims to be comonotonic with the underlying random variable X. Vigilance is satisfied by a large class of risk measures, including all distortion risk measures. An explicit characterization of an optimal contingent claim is also provided in the case where the risk measure is a convex distortion risk measure.

Suggested Citation

  • Mario Ghossoub, 2012. "Vigilant Measures of Risk and the Demand for Contingent Claims," Discussion Papers 1555, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
  • Handle: RePEc:nwu:cmsems:1555
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    Cited by:

    1. Mario Ghossoub, 2015. "Equimeasurable Rearrangements with Capacities," Mathematics of Operations Research, INFORMS, vol. 40(2), pages 429-445, February.
    2. Massimiliano Amarante & Mario Ghossoub, 2016. "Optimal Insurance for a Minimal Expected Retention: The Case of an Ambiguity-Seeking Insurer," Risks, MDPI, vol. 4(1), pages 1-27, March.
    3. Mario Ghossoub, 2016. "Optimal Insurance with Heterogeneous Beliefs and Disagreement about Zero-Probability Events," Risks, MDPI, vol. 4(3), pages 1-28, August.
    4. Amarante, Massimiliano & Ghossoub, Mario & Phelps, Edmund, 2015. "Ambiguity on the insurer’s side: The demand for insurance," Journal of Mathematical Economics, Elsevier, vol. 58(C), pages 61-78.

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    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • D89 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Other
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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