Multivariate heavy-tailed models for Value-at-Risk estimation
Risk Management
2011-12-20 v3
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 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.
Cite
@article{arxiv.1005.2862,
title = {Multivariate heavy-tailed models for Value-at-Risk estimation},
author = {Carlo Marinelli and Stefano d'Addona and Svetlozar T. Rachev},
journal= {arXiv preprint arXiv:1005.2862},
year = {2011}
}