Energy price volatilities and correlations have been modeled extensively using short-memory multivariate GARCH models. This paper investigates the potential benefits from using multivariate fractionally integrated GARCH models from a forecasting and a risk management perspective. Several...

We propose a novel approach to modelling structural changes in asset returns correlations. Our framework allows for breaks of different type in the conditional and unconditional correlation components by capturing abrupt regime switches in the short-run correlations and smooth transitions...

The availability of many variables with predictive power makes their selection in a regression context difficult. This study considers robust and understandable low-dimensional estimators as building blocks to improve overall predictive power by optimally combining these building blocks. Our new...

This paper studies the impact of modelling time-varying variances of stock returns in terms of risk measurement and extreme risk spillover. Using a general class of regime-dependent models, we find that volatility can be disaggregated into distinct components: a persistent stable process with...

Stock return predictability by investor sentiment has been subject to constant updating, but reaching a decisive conclusion seems rather challenging as academic research relies heavily on US data. We provide fresh evidence on stock return predictability in an international setting and show that...