Dynamic Bivariate Mixture Models: Modeling the Behavior of Prices and Trading Volume
用模拟最大似然法估计了具有序列相关混合变量的双变量混合模型，并检验其能否解释德国股市中价格变化方差的持续性，结果发现该模型无法解释这一现象。
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 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 mi-xing variable determines the dynamics of the price-volume system. In this paper, bivariate mixture specifications with a serially correlated mixing variable are estimated by simula-ted 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.