Multivariate Heavy-Tailed Models For Value-At-Risk Estimation
AbstractFor 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 InfoArticle 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 ()
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Web page: http://www.worldscinet.com/ijtaf/ijtaf.shtml
Other versions of this item:
- Carlo Marinelli & Stefano d'Addona & Svetlozar T. Rachev, 2010. "Multivariate heavy-tailed models for Value-at-Risk estimation," Papers 1005.2862, arXiv.org, revised Dec 2011.
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