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Oil prices and stock market price in Nigeria

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  • Philip Ifeakachukwu Nwosa

Abstract

This paper examined the relationship between oil prices (international oil price and domestic oil price) and stock market price in Nigeria for the period spanning 1985:1 to 2010:4. The study utilised the Johansen's multivariate cointegration test and the vector error correction model (VECM). The Johansen's test showed that the variables are cointegrated, and the cointegration equation revealed that oil prices have significant relationship with stock market price in the long run. The VECM estimate only revealed a unidirectional causality from stock market price to international oil price in the long run. A unidirectional causality was also observed from domestic oil price to stock market price in the long run. The study recommended that policymakers, financial analyst and shareholders should into cognizance changes in international oil price and domestic oil price in their financial decisions given the significant impact of oil prices on stock market price in Nigeria.

Suggested Citation

  • Philip Ifeakachukwu Nwosa, 2014. "Oil prices and stock market price in Nigeria," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 38(1), pages 59-74, March.
    • Handle: RePEc:bla:opecrv:v:38:y:2014:i:1:p:59-74
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    File URL: http://hdl.handle.net/10.1111/opec.12013
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    Cited by:

    1. Moses Tule & Afees A. Salisu & Charles Chimeke, 2018. "You are what you eat: The role of oil price in Nigeria inflation forecast," Working Papers 040, Centre for Econometric and Allied Research, University of Ibadan.
    2. Moses Tule & Afees Salisu & Charles Chiemeke, 2020. "Improving Nigeria’s Inflation Forecast with Oil Price: The Role of Estimators," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(1), pages 191-229, March.
    3. Isiaka Akande Raifu & Alarudeen Aminu & Abiodun O. Folawewo, 2020. "Investigating the relationship between changes in oil prices and unemployment rate in Nigeria: linear and nonlinear autoregressive distributed lag approaches," Future Business Journal, Springer, vol. 6(1), pages 1-18, December.

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