EconPapers    
Economics at your fingertips  
 

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 (2) Track citations by RSS feed

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0140988318304559
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

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

Access Statistics for this article

Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant

More articles in Energy Economics from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().

 
Page updated 2019-10-07
Handle: RePEc:eee:eneeco:v:78:y:2019:i:c:p:192-201