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

Author

Listed:
  • 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.

Suggested Citation

  • Carlo Marinelli & Stefano D'Addona & Svetlozar T. Rachev, 2012. "Multivariate Heavy-Tailed Models For Value-At-Risk Estimation," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 15(04), pages 1-32.
    • Handle: RePEc:wsi:ijtafx:v:15:y:2012:i:04:n:s021902491250029x
    DOI: 10.1142/S021902491250029X
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    References listed on IDEAS

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    1. John C. Frain, 2008. "Value at Risk (VaR) and the alpha-stable distribution," Trinity Economics Papers tep0308, Trinity College Dublin, Department of Economics, revised May 2008.
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    Cited by:

    1. Simon Hediger & Jeffrey Näf & Marc S. Paolella & Paweł Polak, 2023. "Heterogeneous tail generalized common factor modeling," Digital Finance, Springer, vol. 5(2), pages 389-420, June.

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