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

Iqbal, R, Sorwar, G ORCID: https://orcid.org/0000-0001-8778-7966, Baker, R and Choudhry, T 2020, 'Multiday expected shortfall under generalized t distributions : evidence from global stock market' , Review of Quantitative Finance and Accounting .

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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.

Item Type:	Article
Schools:	Schools > Salford Business School
Journal or Publication Title:	Review of Quantitative Finance and Accounting
Publisher:	Springer US
ISSN:	0924-865X
Related URLs:	Publication
Depositing User:	G Sorwar
Date Deposited:	15 Nov 2019 15:07
Last Modified:	03 Feb 2020 15:45
URI:	http://usir.salford.ac.uk/id/eprint/53043

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