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Likelihood-based estimation of latent generalised ARCH structures

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  • Fiorentini, Gabriele
  • Sentana, Enrique
  • Shephard, Neil

Abstract

GARCH models are commonly used as latent processes in econometrics, financial economics and macroeconomics. Yet no exact likelihood analysis of these models has been provided so far. In this paper we outline the issues and suggest a Markov chain Monte Carlo algorithm which allows the calculation of a classical estimator via the simulated EM algorithm or a Bayesian solution in O(T) computational operations, where T denotes the sample size. We assess the performance of our proposed algorithm in the context of both artificial examples and an empirical application to 26 UK sectorial stock returns, and compare it to existing approximate solutions.

Suggested Citation

  • Fiorentini, Gabriele & Sentana, Enrique & Shephard, Neil, 2003. "Likelihood-based estimation of latent generalised ARCH structures," LSE Research Online Documents on Economics 24852, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:24852
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    More about this item

    Keywords

    Bayesian inference; dynamic heteroskedasticity; factor models; Markov chain Monte Carlo; simulated EM algorithm; volatility;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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