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Likelihood-Based Estimation of Latent Generalized Arch Structures

Gabriele Fiorentini, Enrique Sentana and Neil Shephard
Econometrica
Vol. 72, No. 5 (Sep., 2004), pp. 1481-1517
Published by: The Econometric Society
Stable URL: http://www.jstor.org/stable/3598896
Page Count: 37
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Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Likelihood-Based Estimation of Latent Generalized Arch Structures
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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.

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