Forecasting the dynamic relationship between crude oil and stock prices since the 19th century

Kris Ivanovski and Abebe Hailemariam

Journal of Commodity Markets, 2021, vol. 24, issue C

Abstract: In this paper, we model and forecast the volatility and correlation between oil prices and stock returns. Employing a recently innovated generalized autoregressive score (GAS) model based on the score function and using long historical data spanning from 1871 to 2020, we find a time-varying relationship between oil prices and stock returns. Specifically, the dynamic correlations between crude oil and stock returns tend to rise during turbulent events over the sample period significantly. Our results show that the GAS(1,1) model outperforms the DCC-GARCH model. Our results on the dependent patterns between oil price and stock returns provide useful information for investors, portfolio managers and market participants.

Keywords: Forecasting; Oil price; Stock price; Volatility and correlation; Multivariate GAS model; DCC-GARCH model (search for similar items in EconPapers)
JEL-codes: C3 E5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S2405851321000039
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:jocoma:v:24:y:2021:i:c:s2405851321000039

DOI: 10.1016/j.jcomm.2021.100169

Access Statistics for this article

Journal of Commodity Markets is currently edited by Marcel Prokopczuk, Betty Simkins and Sjur Westgaard

More articles in Journal of Commodity Markets from Elsevier
Bibliographic data for series maintained by Catherine Liu ().