Working Paper: CEPR ID: DP9572
Authors: Christiane Baumeister; Lutz Kilian; Xiaoqing Zhou
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.
Keywords: acquisition cost; crack spread; forecast accuracy; futures; oil price; real-time data; refined products; WTI
JEL Codes: C53; G15; Q43
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| product spreads (D39) | real price of oil (Q31) |
| gasoline spread model (C54) | forecast accuracy (C53) |
| product spreads (D39) | forecasts of crude oil prices (Q47) |
| time-varying parameter model (C22) | forecast accuracy (C53) |
| product spreads (D39) | mean squared prediction error (MSPE) (C51) |
| gasoline spreads (L95) | forecast accuracy (C53) |