MULTIVARIATE HEAVY-TAILED MODELS FOR VALUE-AT-RISK ESTIMATION

Carlo Marinelli, Stefano d'Addona and Svetlozar T. Rachev
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Carlo Marinelli: Facoltà di Economia, Università di Bolzano, Piazza Università 1, I-39100 Bolzano, Italy
Svetlozar T. Rachev: Department of Applied Mathematics & Statistics, Stony Brook University, Stony Brook, NY 11794-3600, USA

International Journal of Theoretical and Applied Finance (IJTAF), 2012, vol. 15, issue 04, 1-32

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.

Keywords: Value-at-Risk; multidimensional stable-like distribution; multidimensional t-like distribution; tail thickness; tail dependence; backtesting (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (2)

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Working Paper: Multivariate heavy-tailed models for Value-at-Risk estimation (2011)
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DOI: 10.1142/S021902491250029X

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