The new benchmark for forecasts of the real price of crude oil

Arbeitspapier

We propose a new no-change benchmark to evaluate forecasts of series that are temporally aggregated. The new benchmark is the last high-frequency observation and reflects the null hypothesis that the underlying series, rather than the aggregated series, is unpredictable. Under the random walk null hypothesis, using the last high-frequency observation improves the mean squared prediction errors of the no-change forecast constructed from average monthly or quarterly data by up to 45 percent. We apply this insight to forecasts of the real price of crude oil and show that a new benchmark that relies on monthly closing prices dominates the conventional no-change forecast in terms of forecast accuracy. Although model-based forecasts also improve when models are estimated using closing prices, only the futures-based forecast significantly outperforms the new benchmark. Introducing a more suitable benchmark changes the assessments of different forecasting approaches and of the general predictability of real oil prices.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Bank of Canada Staff Working Paper ; No. 2020-39

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Forecasting Models; Simulation Methods ; Energy Forecasting
• Thema: Econometric and statistical methods ; International topics

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Benmoussa, Amor Aniss ; Ellwanger, Reinhard ; Snudden, Stephen
• Ereignis: Veröffentlichung
• (wer): Bank of Canada
• (wo): Ottawa
• (wann): 2020

Weitere Informationen

• DOI: doi:10.34989/swp-2020-39
• Handle: http://hdl.handle.net/10419/241205
• Letzte Aktualisierung: 10.03.2025, 11:42 MEZ