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Estimating value-at-risk using a multivariate copula-based volatility model: Evidence from European banks

Sampid, Marius and Hasim, Haslifah (2018) 'Estimating value-at-risk using a multivariate copula-based volatility model: Evidence from European banks.' International Economics, 156. 175 - 192. ISSN 2110-7017

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Abstract

This paper proposes a multivariate copula-based volatility model for estimating Value-at-Risk (VaR) in the banking sector of selected European countries by combining dynamic conditional correlation (DCC) multivariate GARCH (M-GARCH) volatility model and copula functions. Non-normality in multivariate models is associated with the joint probability of the univariate models' marginal probabilities –the joint probability of large market movements, referred to as tail dependence. In this paper, we use copula functions to model the tail dependence of large market movements and test the validity of our results by performing back-testing techniques. The results show that the copula-based approach provides better estimates than the common methods currently used and captures VaR reasonably well based on the differences in the numbers of exceptions produced during different observation periods at the same confidence level.

Item Type: Article
Uncontrolled Keywords: Value-at-risk; Dynamic conditional correlation; GARCH; Copulas; Volatility
Subjects: H Social Sciences > HG Finance
Q Science > QA Mathematics
Divisions: Faculty of Science and Health > Mathematical Sciences, Department of
Depositing User: Elements
Date Deposited: 09 Mar 2018 16:15
Last Modified: 09 Sep 2019 01:00
URI: http://repository.essex.ac.uk/id/eprint/20817

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