Many economic studies on inflation forecasting have found favorable results when inflation is modeled as a stationary … process around a slowly time-varying trend. In contrast, the existing studies on interest rate forecasting either treat yields … the problem of forecasting the term structure of interest rates with the assumption that the yield curve is driven by …

-of-fit and clearly reduces the forecasting uncertainty particularly in low-volatility periods. The proposed approach is shown to …

-parametric estimation is impractical given commonly available predictive sample sizes. Instead, this paper derives the approximate …

forecasting the term structure of interest rates. As expected, I find that using more flexible models leads to a better in …-step state-space estimation approach the four-factor model produces accurate forecasts and outperforms competitor models across …

forecasting financial volatility. We use the auto-covariances of log increments of the multi-fractal process in order to estimate … ?scaling? approach. Our empirical estimates are used in out-of-sample forecasting of volatility for a number of important …

aggregates are time-varying, much of the literature on forecasting aggregates considers the case of linear aggregates with fixed … theoretical setup and the forecasting results. …

-term predictions. Due to the characteristics of the residuals, a bootstrapping method of forecasting was also used, yielding even …

-memory counterparts. Since long memory models should have a particular advantage over long forecasting horizons, we consider predictions …

-memory counterparts. Since long memory models should have a particular advantage over long forecasting horizons, we consider predictions …