The stochastic conditional duration model: a latent variable model for the analysis of financial durations

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 functions. The estimation of the parameters is performed by quasi-maximum likelihood and using the Kalman filter. The model is applied to trade, price and volume durations of stocks traded at NYSE. We also investigate the relation between price durations, spread, trade intensity and volume.