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Multivariate Heavy-Tailed Models For Value-At-Risk Estimation

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  • CARLO MARINELLI

    (Facoltà di Economia, Università di Bolzano, Piazza Università 1, I-39100 Bolzano, Italy)

  • STEFANO D'ADDONA

    ()
    (Department of International Studies, University of Rome 3, Via G. Chiabrera, 199, I-00145 Rome, Italy)

  • SVETLOZAR T. RACHEV

    (Department of Applied Mathematics & Statistics, Stony Brook University, Stony Brook, NY 11794-3600, USA)

Abstract

For purposes of Value-at-Risk estimation, we consider several multivariate families of heavy-tailed distributions, which can be seen as multidimensional versions of Paretian stable and Student's t distributions allowing different marginals to have different indices of tail thickness. After a discussion of relevant estimation and simulation issues, we conduct a backtesting study on a set of portfolios containing derivative instruments, using historical US stock price data.

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Bibliographic Info

Article provided by World Scientific Publishing Co. Pte. Ltd. in its journal International Journal of Theoretical and Applied Finance.

Volume (Year): 15 (2012)
Issue (Month): 04 ()
Pages: 1250029-1-1250029-32

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Handle: RePEc:wsi:ijtafx:v:15:y:2012:i:04:p:1250029-1-1250029-32

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Related research

Keywords: Value-at-Risk; multidimensional stable-like distribution; multidimensional t-like distribution; tail thickness; tail dependence; backtesting;

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  1. Kotz,Samuel & Nadarajah,Saralees, 2004. "Multivariate T-Distributions and Their Applications," Cambridge Books, Cambridge University Press, number 9780521826549.
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