revealing time-varying conditional variances and correlations. Modeling the variables' conditional mean processes using a … likelihood which is sufficiently flexible to be applicable in high dimensions. Strong empirical evidence for time … explicitly into account significantly improves the goodness-of-fit of the multiplicative error model and allows capturing time …

We propose a new class of observation-driven time-varying parameter models for dynamic volatilities and correlations to … handle time series from heavy-tailed distributions. The model adopts generalized autoregressive score dynamics to obtain a … time-varying covariance matrix of the multivariate Student's t distribution. The key novelty of our proposed model concerns …

application to the income-consumption relationship, using monthly US time series. Evidence is found to support the claim that the …

We propose a model for forecasting extreme electricity prices in real time (high frequency) settings. The unique …