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 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 InfoPaper provided by arXiv.org in its series Papers with number 1005.2862.
Date of creation: May 2010
Date of revision: Dec 2011
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Web page: http://arxiv.org/
Other versions of this item:
- 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 1250029-1-1.
- NEP-ALL-2010-05-29 (All new papers)
- NEP-ETS-2010-05-29 (Econometric Time Series)
- NEP-RMG-2010-05-29 (Risk Management)
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