Dynamic robust portfolio selection under market distress
Dynamic robust portfolio selection under market distress
This article proposes a dynamic robust portfolio selection model that is based on minimizing portfolio’s worst case scenarios using the Conditional Value at Risk as relevant risk measure. Our proposed empirical model for the dynamics of portfolio constituents has three main features: i) accommodates tail dependence between assets by means of a mixture of copula functions; ii) conditional heteroscedasticity and leverage effects are considered through the implementation of a GJR-GARCH model; and iii) extreme events are taken into account by considering parametric and semiparametric hybrid models for the marginal distribution of asset returns. We illustrate the performance of this portfolio before and during the COVID-19 pandemic using statistical measures such as the Sharpe ratio, cumulative returns, and volatility. The results show the outperformance of our WCVaR portfolio during the turmoil period against benchmark portfolios commonly used by practitioners. The method also exhibits good performance during calm periods.
Conditional value-at-risk, Dynamic multivariate copula, Financial crisis, GJR-GARCH-EVT, Robust portfolio selection
Jiang, Yifu
cff1ccf8-1299-45de-95ec-f449f30fa0b8
Olmo, Jose
706f68c8-f991-4959-8245-6657a591056e
Atwi, Majed
a713c2fd-6b12-412d-9065-8a72ae788ad7
January 2024
Jiang, Yifu
cff1ccf8-1299-45de-95ec-f449f30fa0b8
Olmo, Jose
706f68c8-f991-4959-8245-6657a591056e
Atwi, Majed
a713c2fd-6b12-412d-9065-8a72ae788ad7
Jiang, Yifu, Olmo, Jose and Atwi, Majed
(2024)
Dynamic robust portfolio selection under market distress.
The North American Journal of Economics and Finance, 69 (Part B), [102037].
(doi:10.1016/j.najef.2023.102037).
Abstract
This article proposes a dynamic robust portfolio selection model that is based on minimizing portfolio’s worst case scenarios using the Conditional Value at Risk as relevant risk measure. Our proposed empirical model for the dynamics of portfolio constituents has three main features: i) accommodates tail dependence between assets by means of a mixture of copula functions; ii) conditional heteroscedasticity and leverage effects are considered through the implementation of a GJR-GARCH model; and iii) extreme events are taken into account by considering parametric and semiparametric hybrid models for the marginal distribution of asset returns. We illustrate the performance of this portfolio before and during the COVID-19 pandemic using statistical measures such as the Sharpe ratio, cumulative returns, and volatility. The results show the outperformance of our WCVaR portfolio during the turmoil period against benchmark portfolios commonly used by practitioners. The method also exhibits good performance during calm periods.
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Accepted/In Press date: 31 October 2023
e-pub ahead of print date: 4 November 2023
Published date: January 2024
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© 2023 The Author(s)
Keywords:
Conditional value-at-risk, Dynamic multivariate copula, Financial crisis, GJR-GARCH-EVT, Robust portfolio selection
Identifiers
Local EPrints ID: 484683
URI: http://eprints.soton.ac.uk/id/eprint/484683
ISSN: 1062-9408
PURE UUID: 8d4e6ea4-da62-43c3-8661-5da6c3294546
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Date deposited: 20 Nov 2023 17:41
Last modified: 18 Mar 2024 03:25
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Author:
Yifu Jiang
Author:
Majed Atwi
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