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Asymptotic Value-at-Risk Estimates for Sums of Dependent Random Variables

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  • Wüthrich, Mario V.

Abstract

We estimate Value-at-Risk for sums of dependent random variables. We model multivariate dependent random variables using archimedean copulas. This structure allows one to calculate the asymptotic behaviour of extremal events. An important application of such results are Value-at-Risk estimates for sums of dependent random variables.

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  • Wüthrich, Mario V., 2003. "Asymptotic Value-at-Risk Estimates for Sums of Dependent Random Variables," ASTIN Bulletin, Cambridge University Press, vol. 33(1), pages 75-92, May.
    • Handle: RePEc:cup:astinb:v:33:y:2003:i:01:p:75-92_01
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    Cited by:

    1. Peter Tankov, 2014. "Tails of weakly dependent random vectors," Papers 1402.4683, arXiv.org, revised Jan 2016.
    2. Geoffrey Nichil & Pierre Vallois, 2019. "Solvency Need Resulting from Reserving Risk in a ORSA Context," Methodology and Computing in Applied Probability, Springer, vol. 21(2), pages 567-592, June.

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