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...

Statistical models usually rely on the assumption that the shape of the distribution is fixed and that it is only the mean and volatility that varies. Although the fitting of heavy tail distributions has become easier due to computational advances, the fitting of the appropriate heavy tail...

Most executives know that overarching paints of plausible futures will profoundly affect the competitiveness and survival of their organisation. Initially from the perspective of Shell, this article discuses oil scenarios and their relevance for upstream investments. Scenarios are then...

This study combines regression analysis with machine learning analysis to study the merit order effect of renewable energy focusing on German market, the largest market in Europe with high renewable energy penetration. The results show that electricity from wind and solar sources reduced the...