Likelihood-based estimation of latent generalised ARCH structures

Gabriele Fiorentini, Enrique Sentana and Neil Shephard ()

OFRC Working Papers Series from Oxford Financial Research Centre

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.

Date: 2004
New Economics Papers: this item is included in nep-ecm and nep-ets
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Related works:
Journal Article: Likelihood-Based Estimation of Latent Generalized 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 (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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