We propose an affine term structure model that allows for tenor-dependence of yield curves andthus for different risk categories in interbank rates, an important feature of post-crisis interestrate markets. The model has a Nelson-Siegel factor loading structure and thus economicallywell...

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...

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...

Classification models are very sensitive to data uncertainty, and finding robust classifiers that are less sensitive to data uncertainty has raised great interest in the machine learning literature. This paper aims to construct robust support vector machine classifiers under feature data...