We develop a numerical procedure that facilitates efficient likelihood evaluation in applications involving non-linear and non-Gaussian state-space models. The procedure employs continuous approximations of filtering densities, and delivers unconditionally optimal global approximations of...

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...

This paper investigates the Information content of daily trading volume with respect to the long-run or high persistent and the short-run or transitory components of the volatility of daily stock market returns using bivariate mixture models. For this purpose, the Standard bivariate mixture...