Investigating the Connectedness between Oil and Stock Markets in GCC countries: Evidence from Rolling-Window Frequency Domain Causality

Abstract This study aims to investigate the causal relationship between oil prices and stock markets in GCC countries. We use weekly stock index and crude oil price data from November 21, 2003, to August 6, 2021, to analyze the spillover effect on the returns and variances of these countries. First, the link between the variables is examined using the frequency domain causality test. Since our sample includes important financial episodes such as the global financial crisis and the global COVID-19 pandemic, we employ rolling-window frequency domain causality test to determine whether such causal relationships exist in these financial crises. To the best of our knowledge, the paper is among the first to employ rolling-window frequency domain causality test to investigate the relationship between the variables. The analysis reveals that the Omani, Kuwaiti, and Bahraini stock markets have limited portfolio diversification benefits due to their high dependence on the price of oil. In addition, Saudi Arabia has the most pronounced divergence in the oil price interaction among GCC stock markets. Investors can benefit from the empirical results practical implications, particularly regarding portfolio diversification. The shifting link between oil and stock markets across different countries and time periods underscores the importance of dynamic diversification strategies that adapt to business cycles.

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Publication Details

Journal
Computational Economics
Published
2025-02-04
DOI
https://doi.org/10.1007/s10614-025-10859-7
Citations
1
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
3.13

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article

Investigating the Connectedness between Oil and Stock Markets in GCC countries: Evidence from Rolling-Window Frequency Domain Causality

Serhat Sezen, Emrah İsmail Çevik, Eisa A. Aleisa, Mehmet Akif Destek et al.
1 citations
Computational Economics
Market Dynamics and Volatility
3.13
article

Investigating the Connectedness between Oil and Stock Markets in GCC countries: Evidence from Rolling-Window Frequency Domain Causality

Serhat Sezen, Emrah İsmail Çevik, Eisa A. Aleisa, Mehmet Akif Destek, Mehmet Fatih Buğan
article en
1 citations

Abstract

Abstract This study aims to investigate the causal relationship between oil prices and stock markets in GCC countries. We use weekly stock index and crude oil price data from November 21, 2003, to August 6, 2021, to analyze the spillover effect on the returns and variances of these countries. First, the link between the variables is examined using the frequency domain causality test. Since our sample includes important financial episodes such as the global financial crisis and the global COVID-19 pandemic, we employ rolling-window frequency domain causality test to determine whether such causal relationships exist in these financial crises. To the best of our knowledge, the paper is among the first to employ rolling-window frequency domain causality test to investigate the relationship between the variables. The analysis reveals that the Omani, Kuwaiti, and Bahraini stock markets have limited portfolio diversification benefits due to their high dependence on the price of oil. In addition, Saudi Arabia has the most pronounced divergence in the oil price interaction among GCC stock markets. Investors can benefit from the empirical results practical implications, particularly regarding portfolio diversification. The shifting link between oil and stock markets across different countries and time periods underscores the importance of dynamic diversification strategies that adapt to business cycles.

Computational EconomicsVol. 66(6)
Tekirdağ Namık Kemal University (TR), Korea University (KR), Western Caspian University (AZ), Azerbaijan State University of Economics (AZ), Al Yamamah University (SA), University of Business and Technology (SA), Baku Eurasian University, Gaziantep University (TR)
Gaziantep Üniversitesi
Openalex Percentile: Top 10%
Market Dynamics and Volatility
3.13
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