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Leverage vs. Feedback: Which Effect Drives the Oil Market?

Author

Listed:
  • Sofiane Aboura

    () (CEREG - Centre de Recherche sur la gestion et la Finance - DRM UMR 7088 - Université Paris Dauphine-PSL - PSL - Université Paris sciences et lettres, DRM - Dauphine Recherches en Management - Université Paris Dauphine-PSL - PSL - Université Paris sciences et lettres - CNRS - Centre National de la Recherche Scientifique)

  • Julien Chevallier

    () (EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

Abstract

This article brings new insights on the role played by (implied) volatility on the WTI crude oil spot price. An increase in the volatility subsequent to an increase in the oil price (i.e. inverse leverage effect) remains the dominant effect as it might reflect the fear of oil consumers to face rising oil prices. However, this effect is amplified by an increase in the oil price subsequent to an increase in the volatility (i.e. inverse feedback effect) with a two-day delayed effect. This lead-lag relation between the oil price and its volatility is determinant for any type of trading strategy based on futures and options on the OVX implied volatility index, and thus is of interest to traders, risk- and fund-managers.

Suggested Citation

  • Sofiane Aboura & Julien Chevallier, 2012. "Leverage vs. Feedback: Which Effect Drives the Oil Market?," Working Papers halshs-00720156, HAL.
  • Handle: RePEc:hal:wpaper:halshs-00720156
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00720156
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    References listed on IDEAS

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    Cited by:

    1. Gong, Xu & Lin, Boqiang, 2018. "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, vol. 74(C), pages 370-386.
    2. Aboura, Sofiane & Chevallier, Julien, 2016. "Spikes and crashes in the oil market," Research in International Business and Finance, Elsevier, vol. 36(C), pages 615-623.
    3. Florian Ielpo & Benoît Sévi, 2014. "Forecasting the density of oil futures," Working Papers 2014-601, Department of Research, Ipag Business School.
    4. Julien, Chevallier & Sévi, Benoît, 2013. "A Fear Index to Predict Oil Futures Returns," Energy: Resources and Markets 156489, Fondazione Eni Enrico Mattei (FEEM).
    5. Qadan, Mahmoud & Idilbi-Bayaa, Yasmeen, 2020. "Risk appetite and oil prices," Energy Economics, Elsevier, vol. 85(C).
    6. Jeng-Bau Lin & Chin-Chia Liang & Wei Tsai, 2019. "Nonlinear Relationships between Oil Prices and Implied Volatilities: Providing More Valuable Information," Sustainability, MDPI, Open Access Journal, vol. 11(14), pages 1-1, July.
    7. Ji, Qiang & Fan, Ying, 2016. "Modelling the joint dynamics of oil prices and investor fear gauge," Research in International Business and Finance, Elsevier, vol. 37(C), pages 242-251.
    8. Sheung Yin Kevin Mo & Anqi Liu & Steve Y. Yang, 2016. "News sentiment to market impact and its feedback effect," Environment Systems and Decisions, Springer, vol. 36(2), pages 158-166, June.
    9. Deeney, Peter & Cummins, Mark & Dowling, Michael & Bermingham, Adam, 2015. "Sentiment in oil markets," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 179-185.
    10. Liu, Bing-Yue & Ji, Qiang & Fan, Ying, 2017. "Dynamic return-volatility dependence and risk measure of CoVaR in the oil market: A time-varying mixed copula model," Energy Economics, Elsevier, vol. 68(C), pages 53-65.
    11. Campos, I. & Cortazar, G. & Reyes, T., 2017. "Modeling and predicting oil VIX: Internet search volume versus traditional mariables," Energy Economics, Elsevier, vol. 66(C), pages 194-204.
    12. Jeng-Bau Lin & Wei Tsai, 2019. "The Relations of Oil Price Change with Fear Gauges in Global Political and Economic Environment," Energies, MDPI, Open Access Journal, vol. 12(15), pages 1-1, August.
    13. repec:dau:papers:123456789/11714 is not listed on IDEAS
    14. Fousekis, Panos, 2020. "Sign and size asymmetry in the stock returns-implied volatility relationship," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    15. repec:ipg:wpaper:2014-545 is not listed on IDEAS
    16. Brice V. Dupoyet & Corey A. Shank, 2018. "Oil prices implied volatility or direction: Which matters more to financial markets?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(3), pages 275-295, August.
    17. Agbeyegbe, Terence D., 2015. "An inverted U-shaped crude oil price return-implied volatility relationship," Review of Financial Economics, Elsevier, vol. 27(C), pages 28-45.
    18. Ji, Qiang & Liu, Bing-Yue & Nehler, Henrik & Uddin, Gazi Salah, 2018. "Uncertainties and extreme risk spillover in the energy markets: A time-varying copula-based CoVaR approach," Energy Economics, Elsevier, vol. 76(C), pages 115-126.
    19. Luo, Xingguo & Qin, Shihua, 2017. "Oil price uncertainty and Chinese stock returns: New evidence from the oil volatility index," Finance Research Letters, Elsevier, vol. 20(C), pages 29-34.
    20. Nguyen, Duc Khuong & Sousa, Ricardo M. & Uddin, Gazi Salah, 2015. "Testing for asymmetric causality between U.S. equity returns and commodity futures returns," Finance Research Letters, Elsevier, vol. 12(C), pages 38-47.

    More about this item

    Keywords

    Leverage Effect; Implied Volatility; WTI; Crude Oil Price; Feedback Effect;

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • G1 - Financial Economics - - General Financial Markets
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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