Bayesian Comparison of Bivariate Copula-GARCH and MGARCH Models
DOI:
https://doi.org/10.24425/cejeme.2019.129362Keywords:
Bayesian model comparison, Copula-GARCH model, Multivariate GARCH model, Monte Carlo Importance SamplingAbstract
The aim of the study is to formally compare the explanatory power of CopulaGARCH and MGARCH models. The models are estimated for logarithmic daily
rates of return of two exchange rates: EUR/PLN, USD/PLN and stock market
indices: SP500, BUX. The analysis is performed within the Bayesian framework.
The posterior model probabilities point to AR(1)-tSBEKK(1,1) for the exchange
rates and VAR(1)-tCopula-GARCH(1,1) for the stock market indices, as the
superior specifications. If the marginal sampling distributions are different in
terms of tail thickness, the Copula-GARCH models have higher explanatory
power than the MGARCH models.
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Published
2019-03-09
How to Cite
Mokrzycka, J. (2019). Bayesian Comparison of Bivariate Copula-GARCH and MGARCH Models. Central European Journal of Economic Modelling and Econometrics, 11(1), 47–71. https://doi.org/10.24425/cejeme.2019.129362
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ARTICLES
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Copyright (c) 2025 Justyna Mokrzycka
This work is licensed under a Creative Commons Attribution 4.0 International License.
