inflation forecasts. Our forecasting approach is based on extracting the factors from the subcomponents of the CPI at the … disaggregated price data improves forecasting performance. The forecasts of the factor models that extract the information from the …

forecasting US inflation by mixing density forecasts from an autoregressive model and the Survey of Professional Forecasters. …

-of-sample forecasting ability to examine the significance of each macro variable in explaining the stock returns behaviour. In addition, we …

This paper investigates the empirical relevance of structural breaks in forecasting stock return volatility using both … return volatility in South Africa. However, based on the out-of-sample forecasting exercise, we find that even though there …-horizon forecasting of stock return volatility. …

improvements in forecasting performance. The overnight returns exhibit some in-sample forecasting power. However, the accuracy …

model using Bayesian techniques and evaluate the forecasting properties. Additionally, we provide an impulse response …

The increasing interest aroused by more advanced forecasting techniques, together with the requirement for more … evaluate the forecasting performance of neural modelling relative to that of time series methods at a regional level … compare the forecasting performance of linear models to that of nonlinear alternative approaches. Pre-processed official …

In this study we investigate the yield curve forecasting performance of Dynamic Nelson–Siegel Model (DNS), affine term … variables in forecasting the yield curve. We have reached numbers of important results: 1—Macroeconomic variables are very … useful in forecasting the yield curve. 2—The forecasting performances of the models depend on the period under review. 3 …