A Comparison of Financial Duration Models Via Density Forecasts.

Using density forecasts, we compare the predictive performance of dur ation models that have been developed fo modelling intra-day data on stock markets. Our model portfolio encompasses the auto regressive conditional duration (ACD) model, its logarithmic version (Log-ACD), the threshold ACD(TACD) model - in each case with alternative error distr ibutions -, the stochastic conditional duration model (SCD), and the stochastic volatility duration model (SVD). The evaluation is done on tr ansaction, price, and volume durations of four stocks listed at the NYSE. The results lead us to conclude that the ACD/log-ACD/TACD/SCD models capture the dynamic dependence in the data in a satisfactory way.