RISK MEASURES DERIVED FROM A REGULATOR’S PERSPECTIVE ON THE REGULATORY CAPITAL REQUIREMENTS FOR INSURERS

2020 ◽  
Vol 50 (3) ◽  
pp. 1065-1092
Author(s):  
Jun Cai ◽  
Tiantian Mao
Keyword(s):  
Value At Risk ◽  
Risk Measures ◽  
Wasserstein Distance ◽  
Capital Requirements ◽  
Translation Invariance ◽  
Coherent Risk Measures ◽  
Regulatory Capital ◽  
Coherent Risk ◽  
Positive Homogeneity ◽  
Stop Loss

AbstractIn this study, we propose new risk measures from a regulator’s perspective on the regulatory capital requirements. The proposed risk measures possess many desired properties, including monotonicity, translation-invariance, positive homogeneity, subadditivity, nonnegative loading, and stop-loss order preserving. The new risk measures not only generalize the existing, well-known risk measures in the literature, including the Dutch, tail value-at-risk (TVaR), and expectile measures, but also provide new approaches to generate feasible and practical coherent risk measures. As examples of the new risk measures, TVaR-type generalized expectiles are investigated in detail. In particular, we present the dual and Kusuoka representations of the TVaR-type generalized expectiles and discuss their robustness with respect to the Wasserstein distance.

ON SOME PROPERTIES OF TWO VECTOR-VALUED VAR AND CTE MULTIVARIATE RISK MEASURES FOR ARCHIMEDEAN COPULAS

2014 ◽  
Vol 44 (3) ◽  
pp. 613-633 ◽  
Author(s):  
Werner Hürlimann
Keyword(s):  
Value At Risk ◽  
Integral Transform ◽  
Risk Measures ◽  
Usual Sense ◽  
Translation Invariance ◽  
Archimedean Copulas ◽  
Coherent Risk ◽  
Multivariate Risk Measures ◽  
Stop Loss ◽  
Conditional Tail Expectation

AbstractWe consider the multivariate Value-at-Risk (VaR) and Conditional-Tail-Expectation (CTE) risk measures introduced in Cousin and Di Bernardino (Cousin, A. and Di Bernardino, E. (2013) Journal of Multivariate Analysis, 119, 32–46; Cousin, A. and Di Bernardino, E. (2014) Insurance: Mathematics and Economics, 55(C), 272–282). For absolutely continuous Archimedean copulas, we derive integral formulas for the multivariate VaR and CTE Archimedean risk measures. We show that each component of the multivariate VaR and CTE functional vectors is an integral transform of the corresponding univariate VaR measures. For the class of Archimedean copulas, the marginal components of the CTE vector satisfy the following properties: positive homogeneity (PH), translation invariance (TI), monotonicity (MO), safety loading (SL) and VaR inequality (VIA). In case marginal risks satisfy the subadditivity (MSA) property, the marginal CTE components are also sub-additive and hitherto coherent risk measures in the usual sense. Moreover, the increasing risk (IR) or stop-loss order preserving property of the marginal CTE components holds for the class of bivariate Archimedean copulas. A counterexample to the (IR) property for the trivariate Clayton copula is included.

scholarly journals Risk Measures and Multivariate Extensions of Breiman's Theorem

2012 ◽  
Vol 49 (2) ◽  
pp. 364-384 ◽  
Author(s):  
Anne-Laure Fougeres ◽  
Cecile Mercadier
Keyword(s):  
Ruin Probability ◽  
Value At Risk ◽  
Risk Measures ◽  
Risk Measure ◽  
Capital Requirements ◽  
Regulatory Capital ◽  
Tail Probabilities ◽  
Solvency Capital ◽  
Finite Time Horizon ◽  
Standard Risk

The modeling of insurance risks has received an increasing amount of attention because of solvency capital requirements. The ruin probability has become a standard risk measure to assess regulatory capital. In this paper we focus on discrete-time models for the finite time horizon. Several results are available in the literature to calibrate the ruin probability by means of the sum of the tail probabilities of individual claim amounts. The aim of this work is to obtain asymptotics for such probabilities under multivariate regular variation and, more precisely, to derive them from extensions of Breiman's theorem. We thus present new situations where the ruin probability admits computable equivalents. We also derive asymptotics for the value at risk.

scholarly journals Risk Measures and Multivariate Extensions of Breiman's Theorem

2012 ◽  
Vol 49 (02) ◽  
pp. 364-384 ◽  
Author(s):  
Anne-Laure Fougeres ◽  
Cecile Mercadier
Keyword(s):  
Ruin Probability ◽  
Value At Risk ◽  
Risk Measures ◽  
Risk Measure ◽  
Capital Requirements ◽  
Regulatory Capital ◽  
Tail Probabilities ◽  
Solvency Capital ◽  
Finite Time Horizon ◽  
Standard Risk

The modeling of insurance risks has received an increasing amount of attention because of solvency capital requirements. The ruin probability has become a standard risk measure to assess regulatory capital. In this paper we focus on discrete-time models for the finite time horizon. Several results are available in the literature to calibrate the ruin probability by means of the sum of the tail probabilities of individual claim amounts. The aim of this work is to obtain asymptotics for such probabilities under multivariate regular variation and, more precisely, to derive them from extensions of Breiman's theorem. We thus present new situations where the ruin probability admits computable equivalents. We also derive asymptotics for the value at risk.

scholarly journals Teoria de Medidas de Risco: uma revisão abrangente

2014 ◽  
Vol 12 (3) ◽  
pp. 411
Author(s):  
Marcelo Brutti Righi ◽  
Paulo Sergio Ceretta
Keyword(s):  
Risk Management ◽  
Literature Review ◽  
Value At Risk ◽  
Risk Measures ◽  
Fundamental Aspect ◽  
Coherent Risk Measures ◽  
Convex Risk Measures ◽  
Coherent Risk ◽  
Comprehensive Literature Review ◽  
Generalized Deviation

A fundamental aspect of proper risk management is the measurement, especially forecasting of risk measures. Measures such as variance, volatility and Value at Risk had been considered valid because of their practical intuition. However, a solid theoretical framework it is important to ensure better properties for risk measures. Such background is the risk measures theory. This paper presents a comprehensive literature review on risk measures theory, focusing in basic theory and extensions to this fundamental outline. The paper is structured in order to cover the main risk measures classes from literature, which are coherent risk measures, convex risk measures, spectral and distortion risk measures and generalized deviation measures.

scholarly journals Coherent Risk Measures and Convex Combinations of the Conditional Value at Risk (C V@R)

2016 ◽  
Vol 31 (1) ◽  
pp. 73-75 ◽  
Author(s):  
Georg Ch. Pflug
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Risk Measures ◽  
Risk Measure ◽  
Conditional Value At Risk ◽  
Coherent Risk Measures ◽  
Coherent Risk

The conditional-value-at-risk (C V@R) has been widely used as a risk measure. It is well known, that C V@R is coherent in the sense of Artzner, Delbaen, Eber, Heath (1999). The class of coherent risk measures is convex. It was conjectured, that all coherent risk measures can be represented as convex combinations of C V@R’s. In this note we show that this conjecture is wrong.

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