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Stochastic Volatility: Likelihood Inference And Comparison With Arch Models

Author

Listed:
  • Sangjoon Kim

    (Salomon Brothers Asia Limited, Tokyo, Japan)

  • Neil Shephard

    (Nuffield College, Oxford University, Oxford)

  • Siddhartha Chib

    (Washington University, St. Louis)

Abstract

In this paper, Markov chain Monte Carlo sampling methods are exploited to provide a unified, practical likelihood-based framework for the analysis of stochastic volatility models. A highly effective method is developed that samples all the unobserved volatilities at once using an approximating offset mixture model, followed by an importance reweighting procedure. This approach is compared with several alternative methods using real data. The paper also develops simulation- based methods for filtering, likelihood evaluation and model failure diagnostics. The issue of model choice using non-nested likelihood ratios and Bayes factors is also investigated. These methods are used to compare the fit of stochastic volatility and GARCH models. All the procedures are illustrated in detail.

Suggested Citation

  • Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1996. "Stochastic Volatility: Likelihood Inference And Comparison With Arch Models," Econometrics 9610002, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:9610002
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Bayes estimation; Bayes factors; GARCH; Gibbs sampler; Heteroscedasticity; Maximum~likelihood; Likelihood ratio; Markov chain Monte Carlo; Quasi-maximum likelihood; Simulation; Stochastic EM algorithm; Stochastic volatility; Stock returns.;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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