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Does crude oil price play an important role in explaining stock return behavior?

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  • Chang, Kuang-Liang
  • Yu, Shih-Ti

Abstract

Employing the MS-ARJI-GJR-GARCH-X model, in which the parameters for the jump process, the asymmetric GARCH effect and the impacts of oil price shocks are regime-dependent, this paper analyzes the impact of crude oil price shock on stock return dynamics. Empirical results reveal three interesting findings. First, incorporating the asymmetric GARCH effect and the oil price shock can substantially improve fitting ability. Second, the GARCH and jump components show very different behaviors during turbulent and stable periods. Third, the effects of current and past oil price shocks differ. The conditional mean, mean of jump size and variance of jump size immediately respond to a current oil price shock. A one-period lagged oil price shock, no matter whether positive or negative, can affect the transition probability that the stock market will remain conditional in the next period. Moreover, the effects of lagged positive and negative shocks on transition probabilities are very different.

Suggested Citation

  • Chang, Kuang-Liang & Yu, Shih-Ti, 2013. "Does crude oil price play an important role in explaining stock return behavior?," Energy Economics, Elsevier, vol. 39(C), pages 159-168.
  • Handle: RePEc:eee:eneeco:v:39:y:2013:i:c:p:159-168
    DOI: 10.1016/j.eneco.2013.05.008
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Kang, Wensheng & Ratti, Ronald A. & Yoon, Kyung Hwan, 2015. "Time-varying effect of oil market shocks on the stock market," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 150-163.
    2. repec:eee:tefoso:v:126:y:2018:i:c:p:271-283 is not listed on IDEAS
    3. Kayalar, Derya Ezgi & Küçüközmen, C. Coşkun & Selcuk-Kestel, A. Sevtap, 2017. "The impact of crude oil prices on financial market indicators: copula approach," Energy Economics, Elsevier, vol. 61(C), pages 162-173.
    4. Naser, Hanan & Alaali, Fatema, 2015. "Can Oil Prices Help Predict US Stock Market Returns: An Evidence Using a DMA Approach," MPRA Paper 65295, University Library of Munich, Germany, revised 25 Jun 2015.
    5. Reboredo, Juan C. & Ugolini, Andrea, 2016. "Quantile dependence of oil price movements and stock returns," Energy Economics, Elsevier, vol. 54(C), pages 33-49.
    6. Walid Mensi & Shawkat Hammoude & Seong-Min Yoon, 2014. "Structural Breaks, Dynamic Correlations, Volatility Transmission, and Hedging Strategies for International Petroleum Prices and U.S. Dollar Exchange Rate," Working Papers 884, Economic Research Forum, revised Dec 2014.
    7. Dhaoui, Abderrazak & Audi, Mohamed & Ouled Ahmed Ben Ali, Raja, 2015. "Revising empirical linkages between direction of Canadian stock price index movement and Oil supply and demand shocks: Artificial neural network and support vector machines approaches," MPRA Paper 66029, University Library of Munich, Germany.
    8. repec:eee:ecmode:v:66:y:2017:i:c:p:258-271 is not listed on IDEAS
    9. Jammazi, Rania & Reboredo, Juan C., 2016. "Dependence and risk management in oil and stock markets. A wavelet-copula analysis," Energy, Elsevier, vol. 107(C), pages 866-888.
    10. repec:eee:eneeco:v:68:y:2017:i:c:p:1-18 is not listed on IDEAS
    11. Peng, Cheng & Zhu, Huiming & Jia, Xianghua & You, Wanhai, 2017. "Stock price synchronicity to oil shocks across quantiles: Evidence from Chinese oil firms," Economic Modelling, Elsevier, vol. 61(C), pages 248-259.
    12. Dhaoui, Abderrazak & Saidi, Youssef, 2015. "Oil supply and demand shocks and stock price: Evidence for some OECD countries," MPRA Paper 63556, University Library of Munich, Germany.

    More about this item

    Keywords

    Oil price shock; Stock return; Jump process; Regime switching;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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