Dynamic bivariate mixture models: Modeling the behavior of prices and trading volume

Bivariate mixture models have been used to explain the stochastic behavior of daily price changes and trading volume on financial markets. In this class of models, price changes and volume follow a mixture of bivariate distributions with the unobservable number of price-relevant information serving as the mixing variable. The time series behavior of this mixing variable determines the dynamics of the price-volume system. In this article, bivariate mixture specifications with a serially correlated mixing variable are estimated by simulated maximum likelihood and analyzed concerning their ability to account for the observed dynamics on financial markets, especially the persistence in the variance of price changes. The results, based on German stock-market data, reveal that the dynamic bivariate mixture models cannot account for the persistence in the price-change variance.

[1]  T. Andersen.  Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility , 1996 .

[2]  Peter E. Rossi,et al.  Bayesian Analysis of Stochastic Volatility Models , 1994 .

[3]  Jón Dańıelsson.  Stochastic volatility in asset prices estimation with simulated maximum likelihood , 1994 .

[4]  E. Ruiz.  Quasi-maximum likelihood estimation of stochastic volatility models , 1994 .

[5]  Christopher G. Lamoureux,et al.  Endogenous Trading Volume and Momentum in Stock-Return Volatility , 1994 .

[6]  M. Richardson,et al.  A Direct Test of the Mixture of Distributions Hypothesis: Measuring the Daily Flow of Information , 1994, Journal of Financial and Quantitative Analysis.

[7]  J. Richard,et al.  Accelerated gaussian importance sampler with application to dynamic latent variable models , 1993 .

[8]  Christopher G. Lamoureux,et al.  Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects , 1990 .

[9]  J. Geweke,et al.  Bayesian Inference in Econometric Models Using Monte Carlo Integration , 1989 .

[10]  Lawrence Harris,et al.  Transaction Data Tests of the Mixture of Distributions Hypothesis , 1987, Journal of Financial and Quantitative Analysis.

[11]  T. Bollerslev,et al.  Generalized autoregressive conditional heteroskedasticity , 1986 .

[12]  A. Kyle.  Continuous Auctions and Insider Trading , 1985 .

[13]  Paul R. Milgrom,et al.  Bid, ask and transaction prices in a specialist market with heterogeneously informed traders , 1985 .

[14]  George Tauchen,et al.  THE PRICE VARIABILITY-VOLUME RELATIONSHIP ON SPECULATIVE MARKETS , 1983 .

[15]  R. Engle.  Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation , 1982 .

[16]  G. Schwarz.  Estimating the Dimension of a Model , 1978 .

[17]  P. Clark.  A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices , 1973 .