We develop an easy-to-implement method for forecasting a stationary autoregressive fractionally integrated moving … rates illustrates the usefulness of our forecasting procedure. The empirical success of the HAR-RV model is explained, from …

changes in the dynamics of the series, for specifying models parsimoniously, and may be helpful in forecasting. We propose the …

– 2010 I exhaustively evaluate the forecasting properties of Bayesian shrinkage in regressions with many predictors. Results …

-term contracts and the new model achieves higher forecasting performance compared to a standard DCC model. …

is assessed in forecasting three major macroeconomic time series of the UK economy. Databased restrictions of VAR … coefficients can help improve upon their unrestricted counterparts in forecasting, and in many cases they compare favorably to …

This paper compares the performance of "aggregate" and "disaggregate" predictors in forecasting contemporaneously … aggregated vector ARMA processes. An aggregate predictor is built by forecasting directly the aggregate process, as it results … sufficient (not necessary) for the equality of mean squared errors. Finally, it is shown that the equality of forecasting …

approach,based on the S-estimation method, to construct forecasting models that are less sensitive to data contamination by … accuracy and sign predictability measures. We find that robust models tend to improve the forecasting accuracy of the AR and of …