Fiorentini, Gabriele, Sentana, Enrique and Shephard, Neil (2003) Likelihood-based estimation of latent generalised ARCH structures. Discussion paper, 453. Financial Markets Group, London School of Economics and Political Science, London, UK.
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.
|Item Type:||Monograph (Discussion Paper)|
|Additional Information:||© 2003 The Authors|
|Uncontrolled Keywords:||Bayesian inference, Dynamic heteroskedasticity, Factor models, Markov chain Monte Carlo, Simulated EM algorithm, Volatility|
|Library of Congress subject classification:||H Social Sciences > HG Finance
H Social Sciences > HB Economic Theory
|Sets:||Research centres and groups > Financial Markets Group (FMG)
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