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Liner and nonliner sectoral response of stock markets to oil price movements: The case of Saudi Arabia

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  • Reem Khamis Hamdan
  • Allam Mohammed Hamdan

Abstract

With respect to Saudi Arabia for the period 2007–2016, this study employs linear (ordinary least square and causality tests) and nonlinear (Markov switching technique) to determine the long‐run relationship between stock market returns, in aggregate, and oil prices, as independent variable on the one hand, with sectoral returns in stock markets, and as dependent variable on the other. Results suggest that sectors in the Saudi market generally respond asymmetrically to oil prices. Overall, in the long run, the Saudi market, in aggregate, was found to be cointegrated with sectoral returns being affected more by overall stock market returns than by oil returns. When nonlinear Markov switching technique was employed, results were only significant in certain sectors namely cement, petrochemical industries, building and construction, and energy and utilities where regime switching between high and low volatilities was detected around the global financial crisis in 2008. Based on these findings, the study recommends investors to consider investing in sectors that balance between those with returns that vary directly and inversely with oil prices in an effort to create “oil‐neutral” portfolios rather than uniformly investing across all sectors in the Saudi market or consider investing in Saudi market sectors in the case of high oil prices.

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  • Reem Khamis Hamdan & Allam Mohammed Hamdan, 2020. "Liner and nonliner sectoral response of stock markets to oil price movements: The case of Saudi Arabia," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(3), pages 336-348, July.
  • Handle: RePEc:wly:ijfiec:v:25:y:2020:i:3:p:336-348
    DOI: 10.1002/ijfe.1755
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    4. Libo Yin, 2022. "The role of intermediary capital risk in predicting oil volatility," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 401-416, January.
    5. Abdou, Hussein A. & Elamer, Ahmed A. & Abedin, Mohammad Zoynul & Ibrahim, Bassam A., 2024. "The impact of oil and global markets on Saudi stock market predictability: A machine learning approach," Energy Economics, Elsevier, vol. 132(C).
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    7. Ngo Thai Hung & Xuan Vinh Vo, 2023. "Multi-scale Features of Interdependence Between Oil Prices and Stock Prices," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 30(3), pages 475-504, September.

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