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Estimation of Dynamic Bivariate Mixture Models: Comments on Watanabe (2000)
Ist Teil von
Journal of business & economic statistics, 2003-10, Vol.21 (4), p.570-576
Ort / Verlag
Alexandria: Taylor & Francis
Erscheinungsjahr
2003
Link zum Volltext
Quelle
Taylor & Francis
Beschreibungen/Notizen
This note compares a Bayesian Markov chain Monte Carlo approach implemented by Watanabe with a maximum likelihood ML approach based on an efficient importance sampling procedure to estimate dynamic bivariate mixture models. In these models, stock price volatility and trading volume are jointly directed by the unobservable number of price-relevant information arrivals, which is specified as a serially correlated random variable. It is shown that the efficient importance sampling technique is extremely accurate and that it produces results that differ significantly from those reported by Watanabe.