A dynamic quantile regression model for the relationship between oil price and stock markets in oil-importing and oil-exporting countries. (15th December 2020)

• Record Type: Journal Article
• Authors: Mokni, Khaled
• Is Part Of: Energy. Volume 213(2020)
• Publication Date: 2020-12-15
• Subjects: Oil price -- Stock markets -- Quantile regression -- Time-varying; C5 -- C22 -- G15 -- Q40; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2020.118639
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: This paper investigates the relationship between oil price and stock markets in the major oil-exporting (Russia, Norway, Canada) and oil-importing (USA, China, Japan) countries. We apply a time-varying asymmetric quantile regression (TV-AQR) model that conducts to provide a more comprehensive picture of the oil-stock market nexus by accounting for the time-varying propriety and the asymmetric effect of oil price on the stock returns under different market conditions. Using weekly data from January 2000 to October 2018, our results reveal that the reaction of the stock markets to crude oil price is time-varying and highly heterogeneous across conditional stock returns' distribution. Moreover, the relationship between oil and stock markets is asymmetrical and the stock markets respond to negative oil price changes more intensively than to positive changes. We also find that the two considered markets are highly dependent during the financial crisis. These results carry crucial implications for investors as well as for policymakers regarding investment strategies and decision making. Highlights: A time-varying asymmetric quantile regression (TV-AQR) model for the oil price-stock markets relationship is proposed. The response of the stock markets to oil price changes varies through market conditions. The relationship between oil price and stock markets changes over time. The impact of oil price on the stock markets increases during stress periods. The stock markets respond more intensively to negative oil shocks.