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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by arXiv.org in its series Papers with number 1005.2862.
Date of creation: May 2010
Date of revision: Dec 2011
Contact details of provider:
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)
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (arXiv administrators).
If references are entirely missing, you can add them using this form.