Divergence-Based Risk Measures: A Discussion on Sensitivities and Extensions

Abstract

This paper introduces a new family of the convex divergence-based risk measure by specifying (h, $phi$)-divergence, corresponding with the dual representation. First, the sensitivity characteristics of the modified divergence risk measure with respect to profit and loss (P&L) and the reference probability in the penalty term are discussed, in view of the certainty equivalent and robust statistics. Secondly, a similar sensitivity property of (h, $phi$)-divergence risk measure with respect to P&L is shown, and boundedness by the analytic risk measure is proved. Numerical studies designed for Renyi- and Tsallis-divergence risk measure are provided. This new family integrates a wide spectrum of divergence risk measures and relates to divergence preferences.

Publication
Entropy, 21(7), 634
Meng Xu
Meng Xu
(Bio)Statistician

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