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...

Using a novel three-phase model based upon a conditional autoregressive Wishart (CAW) framework for the realized (co)variances of the US Dow Jones and the German stock index DAX, we analyze intra-daily volatility spillovers between the US and German stock markets. The proposed model explicitly...

In this paper we develop a dynamic model for integer counts to capture the dis- creteness of price changes for financial transaction prices. Our model rests on an autoregressive multinomial component for the direction of the price change and a dynamic count data component for the size of the...

We propose a Conditional Autoregressive Wishart (CAW) model for the analysis of realized covariance matrices of asset returns. Our model assumes a generalized linear autoregressive moving average structure for the scale matrix of the Wishart distribution allowing to accommodate for complex...