Systemic risk: Conditional distortion risk measures

Risk Redistribution with Distortion Risk Measures∗

This paper studies optimal risk redistribution between firms, such as banks or insurance companies. The introduction of the Basel II regulation and the Swiss Solvency Test (SST) has increased the use of risk measures to evaluate financial or insurance risk. We consider the case where firms use a distortion risk measure (also called dual utility) to evaluate risk. The paper first characterizes a...

Estimation of Distortion Risk Measures

The concept of coherent risk measure was introduced in Artzner et al. (1999). They listed some properties, called axioms of ‘coherence’, that any good risk measure should possess, and studied the (non-)coherence of widely-used risk measure such as Value-atRisk (VaR) and expected shortfall (also known as tail conditional expectation or tail VaR). Kusuoka (2001) introduced two additional axioms c...

Measures of Systemic Risk

Beyond Value-at-Risk: GlueVaR Distortion Risk Measures.

We propose a new family of risk measures, called GlueVaR, within the class of distortion risk measures. Analytical closed-form expressions are shown for the most frequently used distribution functions in financial and insurance applications. The relationship between GlueVaR, value-at-risk, and tail value-at-risk is explained. Tail subadditivity is investigated and it is shown that some GlueVaR ...

Distortion Risk Measures: Coherence and Stochastic Dominance

In this paper it is proved that a concave distortion function is a necessary and sufficient condition for coherence, and a strictly concave distortion function is a necessary and sufficient condition for strict consistency with second order stochastic dominance. The results are related to current risk measures used in practice, such as value-at-risk (VaR) and the conditional tail expectation (C...