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 …

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 …

been proposed. A related strand of literature focuses on dynamic models and covariance forecasting for high-frequency data … address, is the relative importance of the quality of the realized measure as an input in a given forecasting model vs. the …

evaluation. An important implication is that forecasting superiority of models using high frequency data is likely to be …