4.7 Article

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

期刊

ENERGY ECONOMICS
卷 78, 期 -, 页码 192-201

出版社

ELSEVIER
DOI: 10.1016/j.eneco.2018.11.015

关键词

Stock market; Crude oil price forecast; MIDAS model; High frequency data

资金

  1. National Natural Science Foundation of China [71322103, 71431008, 71774051]
  2. National Program for Support of Top-notch Young Professionals [W02070325]
  3. Changjiang Scholars Program of the Ministry of Education of China [Q2016154]
  4. Hunan Youth Talent Program
  5. China Scholarship Council [201606135020]

向作者/读者索取更多资源

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. (C) 2018 Elsevier B.V. All rights reserved.

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