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Inf-convolution of g_\Gamma-solution and its applications

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  • Yuanyuan Sui
  • Helin Wu

Abstract

A risk-neutral method is always used to price and hedge contingent claims in complete market, but another method based on utility maximization or risk minimization is wildly used in more general case. One can find all kinds of special risk measure in literature. In this paper, instead of using market modified risk measure, we use a kind of risk measure induced by g_\Gamma-solution or the minimal solution of a Constrained Backward Stochastic Differential Equation (CBSDE) directly when constraints on wealth and portfolio process comes to our consideration. Such g_\Gamma-solution and the risk measure generated by it is well defined on appropriate space under suitable conditions. We adopt the inf-convolution of convex risk measures to solve some optimization problem. A dynamic version risk measures defined through g_\Gamma-solution and some similar results about optimal problem can be got in our new framework and by our new approach.

Suggested Citation

  • Yuanyuan Sui & Helin Wu, 2011. "Inf-convolution of g_\Gamma-solution and its applications," Papers 1103.1050, arXiv.org, revised May 2012.
    • Handle: RePEc:arx:papers:1103.1050
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    References listed on IDEAS

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    1. Rosazza Gianin, Emanuela, 2006. "Risk measures via g-expectations," Insurance: Mathematics and Economics, Elsevier, vol. 39(1), pages 19-34, August.
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