A sequential Monte Carlo method for estimating GARCH models subject to an unknown number of structural breaks is proposed. Particle filtering techniques allow for fast and efficient updates of posterior quantities and forecasts in real time. The method conveniently deals with the path dependence...

A sequential Monte Carlo method for estimating GARCH models subject to an unknown number of structural breaks is proposed. Particle filtering techniques allow for fast and efficient updates of posterior quantities and forecasts in real time. The method conveniently deals with the path dependence...

This paper introduces a new approach to forecast pooling methods based on a nonparametric prior for the weight vector combining predictive densities. The first approach places a Dirichlet process prior on the weight vector and generalizes the static linear pool. The second approach uses a...

This paper examines whether sell-side analysts struggle to cope with macroeconomic uncertainty. We find that analysts issue more accurate earnings forecasts when facing higher economic policy uncertainty, which conflicts with the conclusions in the US. We provide a novel explanation for this...

This paper examines whether sell-side analysts struggle to cope with macroeconomic uncertainty. We find that analysts issue more accurate earnings forecasts when facing higher economic policy uncertainty, which conflicts with the conclusions in the US. We provide a novel explanation for this...