TVaR-based capital allocation for multivariate compound distributions with positive continuous claim amounts

Hélène Cossette, Mélina Mailhot and Étienne Marceau

Insurance: Mathematics and Economics, 2012, vol. 50, issue 2, 247-256

Abstract: In this paper, we consider a portfolio of n dependent risks X1,…,Xn and we study the stochastic behavior of the aggregate claim amount S=X1+⋯+Xn. Our objective is to determine the amount of economic capital needed for the whole portfolio and to compute the amount of capital to be allocated to each risk X1,…,Xn. To do so, we use a top–down approach. For (X1,…,Xn), we consider risk models based on multivariate compound distributions defined with a multivariate counting distribution. We use the TVaR to evaluate the total capital requirement of the portfolio based on the distribution of S, and we use the TVaR-based capital allocation method to quantify the contribution of each risk. To simplify the presentation, the claim amounts are assumed to be continuously distributed. For multivariate compound distributions with continuous claim amounts, we provide general formulas for the cumulative distribution function of S, for the TVaR of S and the contribution to each risk. We obtain closed-form expressions for those quantities for multivariate compound distributions with gamma and mixed Erlang claim amounts. Finally, we treat in detail the multivariate compound Poisson distribution case. Numerical examples are provided in order to examine the impact of the dependence relation on the TVaR of S, the contribution to each risk of the portfolio, and the benefit of the aggregation of several risks.

Keywords: Capital allocation; Tail value at risk; Dependence models; Multivariate compound distributions; Multivariate compound Poisson distributions; Mixed Erlang distribution (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (25)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:50:y:2012:i:2:p:247-256

DOI: 10.1016/j.insmatheco.2011.11.006

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