A Bayesian Semiparametric Analysis of ARCH Models

  • Hideo Kozumi
  • Wolfgang Polasek


This paper provides a Bayesian analysis of a semiparametric autoregressive conditional heteroscedasticity (ARCH) model. We propose a semiparametric ARCH model using a Dirichlet process prior and show a Markov chain Monte Carlo method for the posterior inference. The model is estimated with a data set of monthly exchange rate for the Deutsche Mark to the U. S. Dollar.


Conditional Variance American Statistical Association Markov Chain Monte Carlo Method Dirichlet Process Semiparametric Model 
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© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Hideo Kozumi
    • 1
  • Wolfgang Polasek
    • 2
  1. 1.Faculty of EconomicsHokkaido University, Kita-kuSapporoJapan
  2. 2.Institute of Statistics and EconometricsUniversity of BaselBaselSwitzerland

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