Journal
ENERGIES
Volume 14, Issue 19, Pages -Publisher
MDPI
DOI: 10.3390/en14196043
Keywords
crude oil prices; exchange rates; nonlinear causality; forecasting; support vector regression; machine learning
Categories
Funding
- National Science Centre [2019/35/B/HS4/00642]
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The study found strong bidirectional causal relations between crude oil prices and EUR/USD, GBP/USD, and weaker relations with JPY/USD. The significance of these relations has changed in recent years, and Support Vector Regression (SVR) was used for forecasting crude oil prices and exchange rates.
The relationships between crude oil prices and exchange rates have always been of interest to academics and policy analysts. There are theoretical transmission channels that justify such links; however, the empirical evidence is not clear. Most of the studies on causal relationships in this area have been restricted to a linear framework, which can omit important properties of the investigated dependencies that could be exploited for forecasting purposes. Based on the nonlinear Granger causality tests, we found strong bidirectional causal relations between crude oil prices and two currency pairs: EUR/USD, GBP/USD, and weaker between crude oil prices and JPY/USD. We showed that the significance of these relations has changed in recent years. We also made an attempt to find an effective strategy to forecast crude oil prices using the investigated exchange rates as regressors and vice versa. To this aim, we applied Support Vector Regression (SVR)-the machine learning method of time series modeling and forecasting.
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