Inference for Some Multivariate Arch and GARCH Models

Journal of Forecasting, Vol. 22, pp. 427-446, 2003

Posted: 26 Oct 2004

See all articles by Ioannis D. Vrontos

Ioannis D. Vrontos

Athens University of Economics and Business

Petros Dellaportas

Athens University of Economics and Business

Dimitris N. Politis

University of California, San Diego (UCSD) - Department of Mathematics

Abstract

Multivariate time varying volatility models have attracted a lot of attention in modern finance theory. We provide an empirical study of some multivariate ARCH and GARCH models that already exist in the literature and have attracted a lot of practical interest. Bayesian and classical techniques are used for the estimation of the parameters of the models and model comparisons are addressed via predictive distributions. We provide implementation details and illustrations using daily exchange rates of the Athens exchange market.

Keywords: Autoregressive conditional heteroscedasticity, Markov chain Monte Carlo, Maximum likelihood, Model comparison, Predictive distribution

Suggested Citation

Vrontos, Ioannis D. and Dellaportas, Petros and Politis, Dimitris, Inference for Some Multivariate Arch and GARCH Models. Journal of Forecasting, Vol. 22, pp. 427-446, 2003, Available at SSRN: https://ssrn.com/abstract=609361

Ioannis D. Vrontos

Athens University of Economics and Business ( email )

76 Patission Street
Athens, 104 34
Greece

Petros Dellaportas (Contact Author)

Athens University of Economics and Business ( email )

76 Patission Street
Athens, 104 34
Greece

Dimitris Politis

University of California, San Diego (UCSD) - Department of Mathematics ( email )

9500 Gilman Drive
La Jolla, CA 92093-0112
United States
858-534-5861 (Phone)
858-534-5273 (Fax)

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
698
PlumX Metrics