Gibbs Sampling for ARCH Models in Finance
The paper develops a simple estimation procedure for Bayesian ARCH models: The Gibbs-importance algorithm (also called independence chain) is applied for the simulation step involving the ARCH parameters. We demonstrate this approach to model the volatility between the Dollar, the DM and the Yen. An extension of the model to multivariate VAR-VARCH models is proposed.
Unable to display preview. Download preview PDF.
- Diebold J. und Robert C. (1990) Bayesian estimation of finite mixture distributions (I): Technical aspects, Tech. report 110, University Paris.Google Scholar
- Gelfand A.E., and Dey D.K. (1992) Bayesian model choice: Asymp-totics and exact calculation, University of Connecticut, mimeoGoogle Scholar
- Jacquier E., Poison N.G. and Rossi P.E. (1992) Bayesian analysis of stochastic volatility models,Working paper 92–141, University of Chicago.Google Scholar
- Müller P. (1991) A Bayesian Vector ARCH Model for Exchange Rate Data,WWZ discussion paper #9109, University of Basel.Google Scholar
- Polasek W. (1994) Bayesian VAR models with tightness priors, WWZ discussion paper, University of Basel.Google Scholar
- Polasek W. (1994) Bayesian augmented ARCH and VARCH models, WWZ discussion paper, University of Basel.Google Scholar
- Polasek W. and Jin S. (1994) Variable selection in regression models,ISO University of Basel.Google Scholar
- Tierney L. (1991) Markov chains for exploring posterior distributions,Univ. of Minnesota, Tech. report No. 560, to appear in Annual of StatisticsGoogle Scholar