Modelling the VaR Using Integral Probability and Tail Dependence

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Résumé

In this paper, a method is proposed to estimate value at risk (VaR) in a multivariate context by employing the probability integral transformation (PIT) and tail dependence function to model extreme dependence structure. The proposed method involves two vectorial measures of VaR, which use either the distribution function or the survival function. Moreover, properties of these risk measures are analysed, and a connection between them and tail dependence functions is established.

Mots-clés

copulas, stochastic finance, risk measures, extreme values theory, tail dependence, probability integral transformation (PIT)