We propose a novel and numerically efficient quantification approach to forecast uncertainty of the real price of oil … been applied to oil price forecasting, by allowing for sequentially updating of time-varying combination weights …, estimation of time-varying forecast biases and facets of miscalibration of individual forecast densities and time-varying inter …

Multi-step-ahead forecasts of forecast uncertainty in practice are often based on the horizon-specific sample means of … recent squared forecast errors, where the number of available past forecast errors decreases one-to-one with the forecast … horizon. In this paper, the efficiency gains from the joint estimation of forecast uncertainty for all horizons in such …

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 …

-order moments. Based on this model, we propose a static hedging strategy for electricity generators that participate in a … purpose, we use Monte Carlo simulation and consider information from the Colombian electricity market as the case study. The … results show that the volume of energy to be sold under long-term contracts depends on each electricity generator and the risk …

Although survey-based point predictions have been found to outperform successful forecasting models, corresponding … often produce squared forecast errors that are much larger on average. In this paper, we document the novel stylized fact … that some survey participants employ a rather judgmental approach to forecasting as opposed to using a formal model. We use …