other sources of information. The combination weights are time-varying and may depend on past predictive forecasting …

. Results show that the proposed model is viable and flexible for purposes of forecasting volatility. Model uncertainty is …

GARCH volatility models with fixed parameters are too restrictive for long time series due to breaks in the volatility … process. Flexible alternatives are Markov-switching GARCH and change-point GARCH models. They require estimation by MCMC …

relatively parsimonious model which explains data well and performs well in a real time out of sample forecasting. The dynamic …

The use of large-dimensional factor models in forecasting has received much attention in the literature with the … model which is better suited for forecasting compared to the traditional principal components (PC) approach.We provide an … asymptotic analysis of the estimator and illustrate its merits empirically in a forecasting experiment based on US macroeconomic …

-sample forecasting regressions. The predictive power of the model stays high at longer horizons. The estimated factors are strongly …

variable selection and estimation in one step. We evaluate the forecasting accuracy of these estimators for a large set of …

Macroeconomic forecasting using factor models estimated by principal components has become a popular research topic … simply screen datasets prior to estimation and remove anomalous observations.We investigate whether forecasting performance … Carlo simulation studies. Finally, we apply our proposed estimator in a simulated real-time forecasting exercise to test its …