Forecasting the real price of oil using online search data

Dean Fantazzini and Nikita Fomichev

International Journal of Computational Economics and Econometrics, 2014, vol. 4, issue 1/2, 4-31

Abstract: New models to forecast the real price of oil on the basis of macroeconomic indicators and Google search data are proposed. A large-scale out-of-sample forecasting analysis comparing the different models is performed. It is found that models including both Google data and macroeconomic aggregates statistically outperform the competing models in the short term, while multivariate models including only Google data perform best also for medium and long term forecasts up to 24 months ahead. This finding is confirmed by different robustness checks.

Keywords: oil prices; real price of oil; oil price forecasting; crude oil inventories; global real activity; refiner acquisition cost; multivariate modelling; macroeconomic indicators; Google search data. (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (22)

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