Using density forecast evaluation techniques we compare the predictive performance of econometric specifications that have been developed for modeling duration processes in intra-day financial markets. The model portfolio encompasses various variants of the Autoregressive Conditional Duration...

We introduce a class of models for the analysis of durations, which we call stochastic conditional duration (SCD) models. These models are based on the assumption that the durations are generated by a dynamic stochastic latent variable. The model yields a wide range of shapes of hazard...

Using density forecasts, we compare the predictive performance of duration models that have been developed for modelling intra-day data on stock markets. Our model portfolio encompasses the autoregressive conditional duration (ACD) model, its logarithmic version (Log-ACD), the threshold ACD...

A new model for the analysis of durations, the stochastic conditional duration (SCD) model, is introduced. This model is based of the assumption that the durations are generated by a latent stochastic factor that follows a first order autoregressive process. The latent factor is pertubed...

Using density forecasts, we compare the predictive performance of duration models that have been developed for modelling intra-day data on stock markets. The compared models are the autoregressive conditional duration (ACD) models, their logarithmic versions, in each case with three...

We study the impact of the arrival of macroeconomic news on the informational and noise-driven components in high-frequency quote processes and their conditional variances. Bid and ask returns are decomposed into a common ('efficient return') factor and two market-side-specific components...

We study the impact of the arrival of macroeconomic news on the informational and noise-driven components in high-frequency quote processes and their conditional variances. Bid and ask returns are decomposed into a common ('efficient return') factor and two market-side-specific components...