Likelihood-based estimation of latent generalised ARCH structures

Gabriele Fiorentini, Enrique Sentana and Neil Shephard ()

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

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.

Keywords: Bayesian inference; dynamic heteroskedasticity; factor models; Markov chain Monte Carlo; simulated EM algorithm; volatility (search for similar items in EconPapers)
JEL-codes: C11 (search for similar items in EconPapers)
Pages: 42 pages
Date: 2003-06
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://eprints.lse.ac.uk/24852/ Open access version. (application/pdf)

Related works:
Journal Article: Likelihood-Based Estimation of Latent Generalized ARCH Structures (2004)
Working Paper: Likelihood-based estimation of latent generalised ARCH structures (2004)
Working Paper: Likelihood-based estimation of latent generalised ARCH structures (2003)
Working Paper: LIKELIHOOD-BASED ESTIMATION OF LATENT GENERALISED ARCH STRUCTURES (2003)
Working Paper: Likelihood-Based Estimation of Latent Generalised ARCH Structures (2002)
Working Paper: Likelihood-based estimation of latent generalised ARCH structures (2002)
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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:24852

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