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

Yue-Jun Zhang () and Jin-Li Wang

Energy Economics, 2019, vol. 78, issue C, 192-201

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.

Keywords: Stock market; Crude oil price forecast; MIDAS model; High frequency data (search for similar items in EconPapers)
JEL-codes: Q02 Q47 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (52)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:78:y:2019:i:c:p:192-201

DOI: 10.1016/j.eneco.2018.11.015

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