In many settings of empirical interest, time variation in the distribution parameters is important for capturing the dynamic behaviour of time series processes. Although the fitting of heavy tail distributions has become easier due to computational advances, the joint and explicit modelling of...

This paper reports on concepts and methods to incorporate the Markov-Switching Multifractal model for stochastic volatility introduced by Calvet and Fisher (2004) within the GAMLSS model introduced by Rigby and Stasinopoulos (2005), allowing generalization to a non-normal distribution. The...