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Comparative Performance of Volatility Models for Oil Price

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  • Afees A. Salisu

    (Department of Economics and Centre for Econometrics and Allied Research (CEAR), University of Ibadan, Ibadan, Nigeria.)

  • Ismail O. Fasanya

    (Department of Economics, Fountain University, Osogbo, Osun State, Nigeria)

Abstract

In this paper, we compare the performance of volatility models for oil price using daily returns of WTI. The innovations of this paper are in two folds: (i) we analyse the oil price across three sub samples namely period before, during and after the global financial crisis, (ii) we also analyse the comparative performance of both symmetric and asymmetric volatility models for the oil price. We find that oil price was most volatile during the global financial crises compared to other sub samples. Based on the appropriate model selection criteria, the asymmetric GARCH models appear superior to the symmetric ones in dealing with oil price volatility. This finding indicates evidence of leverage effects in the oil market and ignoring these effects in oil price modelling will lead to serious biases and misleading results.

Suggested Citation

  • Afees A. Salisu & Ismail O. Fasanya, 2012. "Comparative Performance of Volatility Models for Oil Price," International Journal of Energy Economics and Policy, Econjournals, vol. 2(3), pages 167-183.
  • Handle: RePEc:eco:journ2:2012-03-9
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    References listed on IDEAS

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    Cited by:

    1. Nnaemeka Vincent Emodi & Kyung-Jin Boo, 2015. "Sustainable Energy Development in Nigeria: Overcoming Energy Poverty," International Journal of Energy Economics and Policy, Econjournals, vol. 5(2), pages 580-597.
    2. Samet Günay, 2015. "Markov Regime Switching Generalized Autoregressive Conditional Heteroskedastic Model and Volatility Modeling for Oil Returns," International Journal of Energy Economics and Policy, Econjournals, vol. 5(4), pages 979-985.
    3. repec:eco:journ2:2018-01-18 is not listed on IDEAS
    4. Gatfaoui, Hayette, 2016. "Linking the gas and oil markets with the stock market: Investigating the U.S. relationship," Energy Economics, Elsevier, vol. 53(C), pages 5-16.
    5. Pokhilchuk, K.A. & Savel’ev, S.E., 2016. "On the choice of GARCH parameters for efficient modelling of real stock price dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 248-253.
    6. Laura Cueppers & Dieter Smeets, 2015. "How Do Oil Price Changes Affect German Stock Returns?," International Journal of Energy Economics and Policy, Econjournals, vol. 5(1), pages 321-334.
    7. Gil-Alana, Luis A. & Gupta, Rangan & Olubusoye, Olusanya E. & Yaya, OlaOluwa S., 2016. "Time series analysis of persistence in crude oil price volatility across bull and bear regimes," Energy, Elsevier, vol. 109(C), pages 29-37.

    More about this item

    Keywords

    Crude oil price; Volatility modelling; Global financial crisis;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G01 - Financial Economics - - General - - - Financial Crises
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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