Abstract
In this paper, we develop a combined Bayesian vector autoregressive and conditional heteroskedasticity (VAR-VARCH) models. A Gibbs sampling approach is suggested for the univariate and multivariate VAR-VARCH model. Using a random coefficient formulation it is shown that full conditional distributions are derived in closed analytical forms. The method is applied to monthly exchange rate series, the Swiss Franc, and the Deutsch Mark to the U.S. Dollar.
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© 1996 Springer Science+Business Media New York
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Polasek, W., Kozumi, H. (1996). The VAR-VARCH model: A Bayesian approach. In: Lee, J.C., Johnson, W.O., Zellner, A. (eds) Modelling and Prediction Honoring Seymour Geisser. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2414-3_26
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DOI: https://doi.org/10.1007/978-1-4612-2414-3_26
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4612-7529-9
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