Numerous heavy-tailed distributions are used for modeling financial data and in problems related to the modeling of economics processes. These distributions have higher peaks and heavier tails than normal distributions. Moreover, in some situations, we cannot observe complete information about...

We study regime-specific systematic comovement between two large panels of variables that exhibit an approximate factor structure. Within each panel we identify threshold-type regimes through shifts in the factor loadings. For the resulting regimes, and with regard to the relation between any...

In finance, durations between successive transactions are usually modelled by the autoregressive conditional duration model based on a continuous distribution omitting frequent zero values. Zero durations can be caused by either split transactions or independent transactions. We propose a...

We propose a local adaptive multiplicative error model (MEM) accommodating timevarying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data-driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time....

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...

This paper generalizes the ACD models of Engle and Russell (1998) using the so-called q-Weibull distribution as the conditional distribution. The new specification allows the hazard function to be non-monotonic. We document that the q-Weibull distribution recently suggested in physics as a...