Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/87688
Authors: 
Baumeister, Christiane
Kilian, Lutz
Year of Publication: 
2013
Series/Report no.: 
CFS Working Paper 2013/09
Abstract: 
Notwithstanding a resurgence in research on out-of-sample forecasts of the price of oil in recent years, there is one important approach to forecasting the real price of oil which has not been studied systematically to date. This approach is based on the premise that demand for crude oil derives from the demand for refined products such as gasoline or heating oil. Oil industry analysts such as Philip Verleger and financial analysts widely believe that there is predictive power in the product spread, defined as the difference between suitably weighted refined product market prices and the price of crude oil. Our objective is to evaluate this proposition. We derive from first principles a number of alternative forecasting model specifications involving product spreads and compare these models to the no-change forecast of the real price of oil. We show that not all product spread models are useful for out-of-sample forecasting, but some models are, even at horizons between one and two years. The most accurate model is a time-varying parameter model of gasoline and heating oil spot spreads that allows the marginal product market to change over time. We document MSPE reductions as high as 20% and directional accuracy as high as 63% at the two-year horizon, making product spread models a good complement to forecasting models based on economic fundamentals, which work best at short horizons.
Subjects: 
oil price
Futures
WTI
Brent
Acquisition Cost
Refined products
Crack spread
Forecast accuracy
Real-time data
JEL: 
Q43
C53
G15
Document Type: 
Working Paper

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