Author:
Baumeister Christiane,Kilian Lutz,Zhou Xiaoqing
Abstract
Many oil industry analysts 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. We derive a number of alternative forecasting model specifications based on product spreads and compare the implied forecasts 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 price spreads that allows for structural change in product markets. We document mean-squared prediction error 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.
Publisher
Cambridge University Press (CUP)
Subject
Economics and Econometrics
Reference38 articles.
1. Bernard Jean-Thomas , Lynda Khalaf , Maral Kichian , and Clement Yelou (in press) Oil price forecasts for the long term: Expert outlooks, models, or both? Macroeconomics Dynamics.
2. Do high-frequency financial data help forecast oil prices? The MIDAS touch at work
3. Strumpf Dan (2013) Goldman Cuts the Near-Term Brent Crude Forecast to $100 a Barrel. Wall Street Journal, April 23.
4. Reeve Trevor A. and Robert J. Vigfusson (2011) Evaluating the Forecasting Performance of Commodity Futures Prices. International finance discussion paper no. 1025, Board of Governors of the Federal Reserve System.
Cited by
62 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献