Shortfall Risk Through Fenchel Duality

Zhenyu Cui, Jun Deng
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引用次数: 1

Abstract

In this paper, we propose a Fenchel duality approach to study the minimization problem of the shortfall risk. We consider a general increasing and strictly convex loss function, which may be more general than the situation of convex risk measures usually assumed in the literature. We first translate the associated stochastic optimization problem to an equivalent static optimization problem, and then obtain the explicit structure of the optimal randomized test for both complete and incomplete markets. For the incomplete market case, to the best of our knowledge, we obtain for the first time the explicit randomized test, while previous literature only established the existence through the supermartingale optional decomposition approach. We also solve the shortfall risk minimization problem for an insider through the enlargement of filtrations approach.
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通过Fenchel二元性分析短缺风险
本文提出了一种Fenchel对偶方法来研究短缺风险的最小化问题。我们考虑一个一般递增的严格凸损失函数,它可能比文献中通常假设的凸风险测度的情况更一般。首先将相关的随机优化问题转化为等效的静态优化问题,然后得到完全市场和不完全市场的最优随机检验的显式结构。对于不完全市场案例,据我们所知,我们首次获得了显式随机检验,而以往的文献只是通过上鞅可选分解方法来确定存在性。我们还通过扩大过滤方法解决了内部人员的短缺风险最小化问题。
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