Quantifying time-varying forecast uncertainty and risk for the real price of oil

Event Date: 24 February 2021

Speaker: Knut Are Aastveit, Norges Bank

Time: 4.00-5.00pm

Abstract: We propose a novel and numerical efficient quantification approach to forecast uncertainty of the real price of oil using a combination of probabilistic individual model forecasts. Our combination method extends earlier approaches that have 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-dependencies among models. To illustrate the usefulness of our method, we provide an extensive set of empirical results about time-varying forecast uncertainty and risk for the real price of oil over the period 1974-2018. We show that our combination approach systematically outperforms commonly used benchmark models and combinations approaches, both in terms of point and density forecasts. The dynamic patterns of the estimated individual model weights are highly time-varying, reflecting a large time variation in the relative performance of the various individual models. Our combination approach has built-in diagnostic information measures about forecast inaccuracy and/or model set incompleteness, which provides clear signals of model incompleteness during three crisis periods.  Finally, to highlight that our approach can also be useful for policy analysis, we present a basic analysis of profit-loss and hedging against price risk.

Published: 8 April 2021