Do high-frequency financial data help forecast oil prices? The MIDAS touch at work : [version november 20, 2013]

The substantial variation in the real price of oil since 2003 has renewed interest in the question of how to forecast monthly and quarterly oil prices. There also has been increased interest in the link between financial
The substantial variation in the real price of oil since 2003 has renewed interest in the question of how to forecast monthly and quarterly oil prices. There also has been increased interest in the link between financial markets and oil markets, including the question of whether financial market information helps forecast the real price of oil in physical markets. An obvious advantage of financial data in forecasting oil prices is their availability in real time on a daily or weekly basis. We investigate whether mixed-frequency models may be used to take advantage of these rich data sets. We show that, among a range of alternative high-frequency predictors, especially changes in U.S. crude oil inventories produce substantial and statistically significant real-time improvements in forecast accuracy. The preferred MIDAS model reduces the MSPE by as much as 16 percent compared with the no-change forecast and has statistically significant directional accuracy as high as 82 percent. This MIDAS forecast also is more accurate than a mixed-frequency realtime VAR forecast, but not systematically more accurate than the corresponding forecast based on monthly inventories. We conclude that typically not much is lost by ignoring high-frequency financial data in forecasting the monthly real price of oil.
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Metadaten
Author:Christiane Baumeister, Pierre Guérin, Lutz Kilian
URN:urn:nbn:de:hebis:30:3-324998
Parent Title (German):Center for Financial Studies (Frankfurt am Main): CFS working paper series ; No. 2013,22
Series (Serial Number):CFS working paper series (2013, 22)
Publisher:Center for Financial Studies
Place of publication:Frankfurt, M.
Document Type:Working Paper
Language:English
Year of Completion:2013
Year of first Publication:2013
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2013/12/16
Tag:forecasts; mixed frequency; oil price; real-time data
Issue:version november 20, 2013
HeBIS PPN:349976821
Institutes:Center for Financial Studies (CFS)
Dewey Decimal Classification:330 Wirtschaft
JEL-Classification:C53 Forecasting and Other Model Applications
G14 Information and Market Efficiency; Event Studies
Q43 Energy and the Macroeconomy
Sammlungen:Universitätspublikationen
Licence (German):License Logo Veröffentlichungsvertrag für Publikationen

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