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 fmancial markets. In this class of m odels 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 t he price-volume system. In this paper, 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.