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Spillover from oil market to stock market in Nigeria: Evidence from granger causality in risk

Author

Listed:
  • Olayeni O. Richard*
  • Olofin O. Philip*

    (Obafemi Awolowo University, Nigeria)

Abstract

It has been stated that the activities of the commercial banks on the Nigerian stock market exposed the economy to global economic crisis. This view is premised on the huge and disproportionate investment of the Nigerian commercial banks in the oil and gas sector, which was directly affected by the recession between 2007 and 2009. With falling oil price and asset value of the banks, the resulting mismatch in the balance sheets of these banks resulted in financial and economic crisis. The Central Bank of Nigeria (CBN) consequently responded by reconsolidating banking sector for effective monitoring. This study then examines the impact of global risk exposure on Nigerian economy by focusing on the connection between oil price and stock market activity. The study employs the method of Granger causality in risk. This method is used to infer the predictive information in risk of one variable from another. It makes use of the sample cross-correlation function (CCF) of the binary indicators for value at risk (VaR). The study successfully implements the method for the relationship between oil price and stock returns for Nigeria. This study uses daily data over the period January 2, 2003 through December 31, 2013. To clean the data of the holiday effects of daily data, we apply the Gallant-Rossi-Tauchen filter. The data were then transformed to obtain their daily returns by computing the first difference of their natural logarithm in percentage. The study finds that oil price return causes stock returns in extreme risk. This phenomenon is found absent prior to January 1, 2007 but present in the sub-sample between January, 2007 and December, 2013. The results indicate that the sudden and unprecedented fall in crude oil price during the global recession between 2007 and 2009 undermined the balance sheets of banks in Nigeria. The study further finds that the market participants not only care about the changes in the oil price and stock index but also in the rate of change in them. The study indicates the need to consolidate the financial sector for effective monitoring and to reduce the exposure to global risk in particular to oil price movement. The study suggests that the policymakers must avail themselves necessary forecasting tools to gauge the immediate and differed spillovers between the stock and the oil markets, and that the current bank consolidation policy should be made more effective to enhance monitoring.

Suggested Citation

  • Olayeni O. Richard* & Olofin O. Philip*, 2015. "Spillover from oil market to stock market in Nigeria: Evidence from granger causality in risk," Journal of Developing Areas, Tennessee State University, College of Business, vol. 49(3), pages 81-101, July-Sepe.
  • Handle: RePEc:jda:journl:vol.49:year:2015:issue3:pp:81-101
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    Citations

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    Cited by:

    1. Olayeni, Olaolu Richard & Tiwari, Aviral Kumar & Wohar, Mark E., 2020. "Global economic activity, crude oil price and production, stock market behaviour and the Nigeria-US exchange rate," Energy Economics, Elsevier, vol. 92(C).
    2. Osaretin Kayode Omoregie & Sodik Adejonwo Olofin, 2020. "Corporate Performance in Nigeria: The Effect of Oil Price and Exchange Rate Fluctuations," International Journal of Economics and Financial Issues, Econjournals, vol. 10(1), pages 170-179.
    3. Maciej Mróz, 2022. "The Impact of Energy Commodity Prices on Selected Clean Energy Metal Prices," Energies, MDPI, vol. 15(9), pages 1-15, April.

    More about this item

    Keywords

    Risk spillover; CAViaR approach; Value-at-risk (VaR); Granger causality; Nigeria;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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