Abstract

Extensive studies have used stock market information to forecast crude oil prices, and stock market can more easily derive high-frequency data than crude oil market due to no revisions, which raises a question that whether high-frequency stock market data can improve the forecast performance of crude oil prices. Therefore, this paper employs the MIDAS model and the high-frequency data of four stock market indices to forecast WTI and Brent crude oil prices at lower frequency. The results indicate that the high-frequency stock market indices have certain advantage over the lower-frequency data in forecasting monthly crude oil prices, and the MIDAS model using high-frequency data proves superior to the ordinary model.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call