Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models

By Yue‐Jun Zhang, Jin-li Wang. Energy Economics, 2019

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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.

Subfields: Analytical Chemistry, Economics and Econometrics, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/ca3a13d9de5a88f3d9554d367e7b3500e1b8446c