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Likelihood-Based Estimation of Latent Generalized ARCH Structures

Listed author(s):
  • Gabriele Fiorentini
  • Enrique Sentana
  • Neil Shephard

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. Copyright The Econometric Society 2004.

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File URL: http://hdl.handle.net/10.1111/j.1468-0262.2004.00541.x
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Article provided by Econometric Society in its journal Econometrica.

Volume (Year): 72 (2004)
Issue (Month): 5 (09)
Pages: 1481-1517

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Handle: RePEc:ecm:emetrp:v:72:y:2004:i:5:p:1481-1517
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