Oil Price Forecast Evaluation with Flexible Loss Functions

35 Pages Posted: 25 Jan 2012

See all articles by Andrea Bastianin

Andrea Bastianin

Università degli Studi di Milano-Bicocca - Department of Economics, Management and Statistics (DEMS); Università degli Studi di Milano-Bicocca - Center for European Studies (CefES)

Matteo Manera

University of Milan-Bicocca, Italy - Department of Economics, Management and Statistics (DEMS); Fondazione Eni Enrico Mattei (FEEM), Milan, Italy

Anil Markandya

Basque Centre for Climate Change (BC3); University of Bath

Elisa Scarpa

Edison Trading

Date Written: January 23, 2012

Abstract

The 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.

Keywords: Oil Price, WTI Spot and Futures Prices, Forecasting, Econometric Models

JEL Classification: C52, C53, Q32, Q43

Suggested Citation

Bastianin, Andrea and Manera, Matteo and Markandya, Anil and Scarpa, Elisa, Oil Price Forecast Evaluation with Flexible Loss Functions (January 23, 2012). FEEM Working Paper No. 91.2011. Available at SSRN: https://ssrn.com/abstract=1990195 or http://dx.doi.org/10.2139/ssrn.1990195

Andrea Bastianin

Università degli Studi di Milano-Bicocca - Department of Economics, Management and Statistics (DEMS) ( email )

Piazza dell'Ateneo Nuovo, 1
Milan, 20126
Italy

Università degli Studi di Milano-Bicocca - Center for European Studies (CefES)

U6 Building
Viale Piero e Alberto Pirelli, 22
Milano, 20126
Italy

Matteo Manera (Contact Author)

University of Milan-Bicocca, Italy - Department of Economics, Management and Statistics (DEMS) ( email )

Via Bicocca degli Arcimboldi, 8
Milan, 20126
Italy
+39 02 6448 5819 (Phone)
+39 02 6448 5878 (Fax)

HOME PAGE: http://www.matteomanera.it

Fondazione Eni Enrico Mattei (FEEM), Milan, Italy ( email )

Corso Magenta, 63
Milan, 20123
Italy
+39 02 520 36944 (Phone)

HOME PAGE: http://www.feem.it

Anil Markandya

Basque Centre for Climate Change (BC3)

Gran Vía 35-2
Bilbao, Vizcaya 48009
Spain

University of Bath ( email )

Claverton Down
Bath, BA2 7AY
United Kingdom

Elisa Scarpa

Edison Trading ( email )

Foro Buonaparte, 31
Milan, 20121
Italy

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