Template-type: ReDIF-Paper 1.0
Author-Name: Gabriele Fiorentini
Author-Email: gabriele.fiorentini@jrc.it
Author-Workplace-Name:IPSC-JRC and University of Alicante, Italy
Author-Name: Enrique Sentana
Author-Email:sentana@cemfi.es 
Author-Workplace-Name: CEMFI, Spain
Author-Name: Neil Shephard
Author-Email: neil.shephard@nuffield.ox.ac.uk
Author-Workplace-Name:Nuffield College, Oxford, UK
Title: Likelihood-based estimation of latent generalised ARCH structures
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.
Length:42 pages
Creation-Date: 2002-09-12
Number:2002-W19
File-URL:http://www.nuff.ox.ac.uk/economics/papers/2002/w19/newneil5.pdf
File-Format: application/pdf
Handle: RePEc:nuf:econwp:0219