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Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions

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  • Jos� A. Fioruci
  • Ricardo S. Ehlers
  • Marinho G. Andrade Filho

Abstract

The main goal in this paper is to develop and apply stochastic simulation techniques for GARCH models with multivariate skewed distributions using the Bayesian approach. Both parameter estimation and model comparison are not trivial tasks and several approximate and computationally intensive methods (Markov chain Monte Carlo) will be used to this end. We consider a flexible class of multivariate distributions which can model both skewness and heavy tails. Also, we do not fix tail behaviour when dealing with fat tail distributions but leave it subject to inference.

Suggested Citation

  • Jos� A. Fioruci & Ricardo S. Ehlers & Marinho G. Andrade Filho, 2014. "Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(2), pages 320-331, February.
    • Handle: RePEc:taf:japsta:v:41:y:2014:i:2:p:320-331
    DOI: 10.1080/02664763.2013.839635
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    4. Foos, Daniel & Lütkebohmert, Eva & Markovych, Mariia & Pliszka, Kamil, 2017. "Euro area banks' interest rate risk exposure to level, slope and curvature swings in the yield curve," Discussion Papers 24/2017, Deutsche Bundesbank.
    5. Kai Dong & Ching-Ter Chang & Shaonan Wang & Xiaoxi Liu, 2021. "The Dynamic Correlation among Financial Leverage, House Price, and Consumer Expenditure in China," Sustainability, MDPI, vol. 13(5), pages 1-18, March.
    6. Marcelo Scherer Perlin & Mauro Mastella & Daniel Francisco Vancin & Henrique Pinto Ramos, 2021. "A GARCH Tutorial with R," RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration), ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração, vol. 25(1), pages 200088-2000.

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