Large deviations built on max-stability

被引:4
|
作者
Kupper, Michael [1 ]
Zapata, Jose Miguel [1 ]
机构
[1] Univ Konstanz, Dept Math & Stat, Constance, Germany
关键词
Large deviations; max-stable monetary risk measures; Large Deviation Principle; Laplace Principle; concentration function; asymptotic shortfall; MARKOV PROCESS EXPECTATIONS; ASYMPTOTIC EVALUATION; THEOREM;
D O I
10.3150/20-BEJ1263
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In this paper, we show that the basic results in large deviations theory hold for general monetary risk measures, which satisfy the crucial property of max-stability. A max-stable monetary risk measure fulfills a lattice homomorphism property, and satisfies under a suitable tightness condition the Laplace Principle (LP), that is, admits a dual representation with affine convex conjugate. By replacing asymptotic concentration of probability by concentration of risk, we formulate a Large Deviation Principle (LDP) for max-stable monetary risk measures, and show its equivalence to the LP. In particular, the special case of the asymptotic entropic risk measure corresponds to the classical Varadhan-Bryc equivalence between the LDP and LP. The main results are illustrated by the asymptotic shortfall risk measure.
引用
收藏
页码:1001 / 1027
页数:27
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