TY  - UNPD
A1  - Baumeister, Christiane
A1  - Guérin, Pierre
A1  - Kilian, Lutz
T1  - Do high-frequency financial data help forecast oil
prices? The MIDAS touch at work : [version november 20, 2013]
T2  - Center for Financial Studies (Frankfurt am Main): CFS working paper series ; No. 2013,22
N2  - 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.
T3  - CFS working paper series - 2013, 22 
KW  - mixed frequency
KW  - real-time data
KW  - oil price
KW  - forecasts
Y1  - 2013
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/32499
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-324998
IS  - version november 20, 2013
PB  - Center for Financial Studies
CY  - Frankfurt, M.
ER  -