Oil Price Forecast Evaluation with Flexible Loss Functions
AbstractThe empirical literature is very far from any consensus about the appropriate model for oil price forecasting that should be implemented. Relative to the previous literature, this paper is novel in several respects. First of all, we test and systematically evaluate the ability of several alternative econometric specifications proposed in the literature to capture the dynamics of oil prices. Second, we analyse the effects of different data frequencies on the coefficient estimates and forecasts obtained using each selected econometric specification. Third, we compare different models at different data frequencies on a common sample and common data. Fourth, we evaluate the forecasting performance of each selected model using static forecasts, as well as different measures of forecast errors. Finally, we propose a new class of models which combine the relevant aspects of the financial and structural specifications proposed in the literature (“mixed” models). Our empirical findings suggest that, irrespective of the shape of the loss function, the class of financial models is to be preferred to time series models. Both financial and time series models are better than mixed and structural models. Results of the Diebold and Mariano test are not conclusive, for the loss differential seems to be statistically insignificant in the large majority of cases. Although the random walk model is not statistically outperformed by any of the alternative models, the empirical findings seem to suggest that theoretically well-grounded financial models are valid instruments for producing accurate forecasts of the WTI spot price.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Fondazione Eni Enrico Mattei in its series Working Papers with number 2011.91.
Date of creation: Dec 2011
Date of revision:
Oil Price; WTI Spot and Futures Prices; Forecasting; Econometric Models;
Find related papers by JEL classification:
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- Q32 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Exhaustible Resources and Economic Development
- Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-02-01 (All new papers)
- NEP-ENE-2012-02-01 (Energy Economics)
- NEP-FOR-2012-02-01 (Forecasting)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Zeng Tian & Swanson Norman R., 1998.
"Predictive Evaluation of Econometric Forecasting Models in Commodity Futures Markets,"
Studies in Nonlinear Dynamics & Econometrics,
De Gruyter, vol. 2(4), pages 1-21, January.
- Zeng, T. & Swanson, N.R., 1997. "Predictive Evaluation of Econometric Forecasting Models in Commodity Futures Markets," Papers 9-97-4, Pennsylvania State - Department of Economics.
- Auffhammer, Maximilian, 2007.
"The rationality of EIA forecasts under symmetric and asymmetric loss,"
Resource and Energy Economics,
Elsevier, vol. 29(2), pages 102-121, May.
- Auffhammer, Maximilian, 2005. "The rationality of EIA forecasts under symmetric and asymmetric loss," CUDARE Working Paper Series 1009, University of California at Berkeley, Department of Agricultural and Resource Economics and Policy.
- Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501, September.
- John R. Moroney & M. Douglas Berg, 1999. "An Integrated Model of Oil Production," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 105-124.
- Ye, Michael & Zyren, John & Shore, Joanne, 2005. "A monthly crude oil spot price forecasting model using relative inventories," International Journal of Forecasting, Elsevier, vol. 21(3), pages 491-501.
- Serletis, Apostolos, 1991. "Rational expectations, risk and efficiency in energy futures markets," Energy Economics, Elsevier, vol. 13(2), pages 111-115, April.
- A Garratt & K Lee & M H Pesaran & Yongcheol Shin, 2004. "Forecast Uncertainties in Macroeconomics Modelling: An Application to the UK Economy," ESE Discussion Papers 64, Edinburgh School of Economics, University of Edinburgh.
- Bopp, Anthony E. & Lady, George M., 1991. "A comparison of petroleum futures versus spot prices as predictors of prices in the future," Energy Economics, Elsevier, vol. 13(4), pages 274-282, October.
- Robert K. Kaufmann, Stephane Dees, Pavlos Karadeloglou and Marcelo Sanchez, 2004. "Does OPEC Matter? An Econometric Analysis of Oil Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 67-90.
- Menzie D. Chinn & Michael LeBlanc & Olivier Coibion, 2005. "The Predictive Content of Energy Futures: An Update on Petroleum, Natural Gas, Heating Oil and Gasoline," NBER Working Papers 11033, National Bureau of Economic Research, Inc.
- Morana, Claudio, 2001. "A semiparametric approach to short-term oil price forecasting," Energy Economics, Elsevier, vol. 23(3), pages 325-338, May.
- Dees, Stephane & Karadeloglou, Pavlos & Kaufmann, Robert K. & Sanchez, Marcelo, 2007. "Modelling the world oil market: Assessment of a quarterly econometric model," Energy Policy, Elsevier, vol. 35(1), pages 178-191, January.
- Moosa, Imad A. & Al-Loughani, Nabeel E., 1994. "Unbiasedness and time varying risk premia in the crude oil futures market," Energy Economics, Elsevier, vol. 16(2), pages 99-105, April.
- Saeed Moshiri & Faezeh Foroutan, 2006. "Forecasting Nonlinear Crude Oil Futures Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 81-96.
- Kaufmann, Robert K., 1995. "A model of the world oil market for project LINK Integrating economics, geology and politics," Economic Modelling, Elsevier, vol. 12(2), pages 165-178, April.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (barbara racah).
If references are entirely missing, you can add them using this form.