Forecasting the Real Price of Oil Using Online Search Data

International Journal of Computational Economics and Econometrics, 4(1-2), 4-31, (2014)

Posted: 12 Apr 2014

See all articles by Dean Fantazzini

Dean Fantazzini

Moscow School of Economics, Moscow State University; National Research University Higher School of Economics

Nikita Fomichev

Independent

Date Written: April 10, 2014

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: Google; oil price; real price of oil; forecasting; forecasting oil prices; crude oil inventories; global real activity; refiners’ acquisition cost for oil

JEL Classification: C22, C32, C52, C53, C55, C58, G17, O13, Q47

Suggested Citation

Fantazzini, Dean and Fomichev, Nikita, Forecasting the Real Price of Oil Using Online Search Data (April 10, 2014). International Journal of Computational Economics and Econometrics, 4(1-2), 4-31, (2014). Available at SSRN: https://ssrn.com/abstract=2423513

Dean Fantazzini (Contact Author)

Moscow School of Economics, Moscow State University ( email )

GSP-2, Leninskie Gory
Moscow, 119992
Russia
+7 495 5105256 (Phone)
+7 495 5105267 (Fax)

HOME PAGE: https://sites.google.com/site/deanfantazzini/

National Research University Higher School of Economics ( email )

Myasnitskaya street, 20
Moscow, Moscow 119017
Russia

HOME PAGE: http://www.hse.ru/org/persons/11532644

Nikita Fomichev

Independent ( email )

Register to save articles to
your library

Register

Paper statistics

Abstract Views
288
PlumX Metrics