Oil prices and stock market anomalies
Muhammad A. Cheema and
Energy Economics, 2019, vol. 83, issue C, 578-587
This paper examines the relationship between oil prices and stock market anomalies in China, the largest oil importer country in the world. Prior literature documents both a positive and negative relationship between oil prices and the stock market. The explanation of a positive relationship is supported by the argument that rising oil prices are interpreted as a positive signal by investors, especially when the rise in oil prices is associated with a higher demand for oil. Consequently, rising oil prices lead stock prices above their fundamental values and that they subsequently correct. Therefore, we hypothesize that stock market anomalies are stronger following rising oil prices when the rise in oil prices is due to the higher demand for oil since returns associated with anomalies reflect mispricing. The results, consistent with the hypothesis, show stronger return predictability for individual anomalies following an increase in oil prices than for a decrease in oil prices. The results are even stronger once we construct a mispricing score based on composite mispricing of all the anomalies.
Keywords: Oil prices; Stock market anomalies; Mispricing score; Chinese stock market (search for similar items in EconPapers)
JEL-codes: G14 G15 Q43 (search for similar items in EconPapers)
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)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:83:y:2019:i:c:p:578-587
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 Haili He ().