general. In this paper, we used the Diebold-Li interpretation to the Nelson Siegel model in order to fit and forecast the … and efficiently estimated using the Kalman filter. The results obtained for the fit and for the forecast showed that the … Kalman filter is the most suitable method for the estimation of the model, generating better forecast for all maturities when …

.e., betas. We study the effect of different data sampling frequencies, forecast adjustments, and model combinations for beta …

analytical tractability. -- ARMA-GARCH models ; neural networks ; nonparametric density estimation ; forecast accuracy ; option …

Recently, several institutions have increased their forecast horizons, and many institutions rely on their past … forecast errors to estimate measures of forecast uncertainty. This work addresses the question how the latter estimation can be … accomplished if there are only very few errors available for the new forecast horizons. It extends upon the results of Knüppel …

forecast accuracy over and above the constituent methods. Second, a handful of macroeconomic predictors are found to have …

Consider forecasting the economic variable Y_{t h} with predictors X_{t}, where h is the forecast horizon. This paper … introduces a semiparametric method that generates forecast intervals of Y_{t h}|X_{t} from point forecast models. First, the … point forecast model is estimated, thereby taking advantage of its predictive power. Then, nonparametric estimation of the …