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Bayesian Inference on Mixture-of-Experts for Estimation of Stochastic Volatility

In: Econometric Analysis of Financial and Economic Time Series

Author

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  • Alejandro Villagran
  • Gabriel Huerta

Abstract

The problem of model mixing in time series, for which the interest lies in the estimation of stochastic volatility, is addressed using the approach known as Mixture-of-Experts (ME). Specifically, this work proposes a ME model where the experts are defined through ARCH, GARCH and EGARCH structures. Estimates of the predictive distribution of volatilities are obtained using a full Bayesian approach. The methodology is illustrated with an analysis of a section of US dollar/German mark exchange rates and a study of the Mexican stock market index using the Dow Jones Industrial index as a covariate.

Suggested Citation

  • Alejandro Villagran & Gabriel Huerta, 2006. "Bayesian Inference on Mixture-of-Experts for Estimation of Stochastic Volatility," Advances in Econometrics, in: Econometric Analysis of Financial and Economic Time Series, pages 277-296, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-9053(05)20030-0
    DOI: 10.1016/S0731-9053(05)20030-0
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