Multiday expected shortfall under generalized t distributions : evidence from global stock market

Iqbal, R; Sorwar, G; Baker, R; Choudhry, T

Abstract

We apply seven alternative t-distributions to estimate the market risk measures Value at Risk (VaR) and its
extension Expected Shortfall (ES). Of these seven, the twin t-distribution (TT) of Baker and Jackson (2014) and
generalized asymmetric distribution (GAT) of Baker (2016) are applied for the first time to estimate market risk.
We analytically estimate VaR and ES over one-day horizon and extend this to multi-day horizon using Monte
Carlo simulation. We find that taken together TT and GAT distributions provide the best back-testing results
across individual confidence levels and horizons for majority of scenarios. Moreover, we find that with the
lengthening of time horizon, TT and GAT models performs well, such that at the ten-day horizon, GAT provides
the best back-testing results for all of the five indices and the TT model provides the second best results,
irrespective period of study and confidence level.

Citation

Iqbal, R., Sorwar, G., Baker, R., & Choudhry, T. (2020). Multiday expected shortfall under generalized t distributions : evidence from global stock market. Review of Quantitative Finance and Accounting, 55, 803-825. https://doi.org/10.1007/s11156-019-00860-1

• Journal Article Type: Article
• Acceptance Date: Nov 5, 2019
• Online Publication Date: Jan 14, 2020
• Publication Date: Jan 14, 2020
• Deposit Date: Nov 15, 2019
• Publicly Available Date: Feb 3, 2020
• Journal: Review of Quantitative Finance and Accounting
• Print ISSN: 0924-865X
• Electronic ISSN: 1573-7179
• Publisher: Springer Verlag
• Volume: 55
• Pages: 803-825
• DOI: https://doi.org/10.1007/s11156-019-00860-1
• Publisher URL: https://doi.org/10.1007/s11156-019-00860-1
• Related Public URLs: https://link.springer.com/journal/11156