Brent prices and oil stock behaviors: evidence from Nigerian listed oil stocks

Amarachi Uzo-Peters (), Temitope Laniran () and Adeola Adenikinju ()
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Amarachi Uzo-Peters: University of Ibadan
Temitope Laniran: University of Ibadan
Adeola Adenikinju: University of Ibadan

Financial Innovation, 2018, vol. 4, issue 1, 1-15

Abstract: Abstract Background Given the shale oil glut that culminated in the most recent and continuing oil price drop from June 2014 and the global financial crisis of 2008 that triggered a cyclical downturn in oil prices and stock market activity, this study investigates the impact of Brent oil price shocks on oil related stocks in Nigeria. Methods This study uses a vector autoregressive (VAR) model with the impulse response function and the forecast variance decomposition error. Findings The empirical evidence reveals that oil price shocks have a negative impact on Nigerian oil and gas company stocks. In theory, this situation should apply to oil importing countries and is therefore uncharacteristic of an oil exporting country like Nigeria. Conclusions The findings suggest that oil companies operating in Nigeria should diversify their investments to protect their business from single-sector market forces, and can also embrace the advantages of outsourcing some of their operations to specialist providers to increase flexibility and reduce operating costs. Finally, for vertically integrated oil and gas companies, oil price hedging and energy risk management will be beneficial because it will mean that these companies will take a position in the crude oil futures market. This will allow for better cash flow management and flexibility. Originality/value This study extends the existing literature in two distinct ways. First, it provides, to the best of our knowledge, the first examination of the impact of oil price shocks on stock market activities with a focus on the market returns of oil and gas companies listed in the Nigerian Stock Exchange. Second, this study uses daily data because high frequency data contain more information than lower frequency data does, and lower frequency data average out too much important information.

Keywords: Oil price shock; Stock markets; VAR; Impulse response; Nigeria (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1186/s40854-018-0092-2

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