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Journal of Economic Integration 2015 March;30(1) :172-205.
DOI: https://doi.org/10.11130/jei.2015.30.1.172
Measuring Risk of Portfolio: GARCH-Copula Model
Samia Ben Messaoud and 
Chaker Aloui 
Faculty of Economics and Management of tunis, Tunis, Tunisia
College of Business Admnistration, King Saud University, Riyadh, KSA
Corresponding Author: Samia Ben Messaoud ,Tel: +216 20874894, Fax: +216 71870277, Email: samia.benmessaoud@yahoo.fr
Copyright ©2015 Journal of Economic Integration
ABSTRACT
In this paper, we use the copulas functions in financial application, namely to examine the assumption of asymmetric dependence and to calculate some measures of risk. The first step consists of deducing filtered residuals for each return series by an asymmetric Glosten-Jagannathan-Runkle Generalized Autoregressive conditional Hetero skedasticity (GJR-GARCH) model. For the second step, we use an estimation of a Generalized Pareto Distribution for the upper and lower tails to determine the empirical semiparametric marginal Cumulative Distribution Function. In our approach, we propose to use a portfolio consisting of increments from five countries. The GJR-GARCH copula is then applied to the data and used to reduce correlation between the simulated residuals of each series. The marginal distributions of filtered residuals are fitted with a semi-parametric Cumulative Distribution Function using the copulas’ functions and Generalized Pareto Distribution for tails. For each series, we compute Value-at-Risk and Conditional Value-at-Risk.

JEL Classification
E32: Business Fluctuations; Cycles
F15: Economic Integration
F42: International Policy Coordination and Transmission
Keywords: GJR-GARCH | Copula Model | Portfolio Risk | Value at Risk | Conditional Value at Risk
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