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

Multiday expected shortfall under generalized t distributions: evidence from global stock market
Multiday expected shortfall under generalized t distributions: evidence from global stock market
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 (in Twin t distribution, University of Salford Manchester. https://arxiv.org/abs/1408.3237, 2014) and generalized asymmetric distribution (GAT) of Baker (in A new asymmetric generalization of the t-distribution, University of Salford Manchester. https://arxiv.org/abs/1606.05203, 2016) are applied for the first time to estimate market risk. We analytically estimate VaR and ES over 1-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 10-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.
0924-865X
1-23
Choudhry, Taufiq
6fc3ceb8-8103-4017-b3b5-2d38efa57728
Iqbal, Robina
9a6b71c7-f565-4fee-ac69-12f75b646484
Sorwar, Ghulam
aa71cb8a-4d75-4f5b-8223-9cedbb725142
Baker, Rose
14452a38-b007-4be7-a326-eafc243d47ee
Choudhry, Taufiq
6fc3ceb8-8103-4017-b3b5-2d38efa57728
Iqbal, Robina
9a6b71c7-f565-4fee-ac69-12f75b646484
Sorwar, Ghulam
aa71cb8a-4d75-4f5b-8223-9cedbb725142
Baker, Rose
14452a38-b007-4be7-a326-eafc243d47ee

Choudhry, Taufiq, Iqbal, Robina, Sorwar, Ghulam and Baker, Rose (2020) Multiday expected shortfall under generalized t distributions: evidence from global stock market. Review of Quantitative Finance and Accounting, 1-23. (doi:10.1007/s11156-019-00860-1).

Record type: Article

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 (in Twin t distribution, University of Salford Manchester. https://arxiv.org/abs/1408.3237, 2014) and generalized asymmetric distribution (GAT) of Baker (in A new asymmetric generalization of the t-distribution, University of Salford Manchester. https://arxiv.org/abs/1606.05203, 2016) are applied for the first time to estimate market risk. We analytically estimate VaR and ES over 1-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 10-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.

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Accepted/In Press date: 5 November 2019
e-pub ahead of print date: 14 January 2020

Identifiers

Local EPrints ID: 436036
URI: http://eprints.soton.ac.uk/id/eprint/436036
ISSN: 0924-865X
PURE UUID: ca0d5bb4-aeca-452d-9db2-9d4c43402386
ORCID for Taufiq Choudhry: ORCID iD orcid.org/0000-0002-0463-0662

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Date deposited: 26 Nov 2019 17:30
Last modified: 16 May 2020 00:31

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