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A wavelet analysis of oil price volatility dynamic

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  • François Benhmad

    (LAMETA)

Abstract

In this the paper we investigate the oil price volatility, by studying the causal relationships between different volatilities captured at different time scales. We first decompose the oil price volatility at various scales of resolution or frequency ranges by using wavelet analysis. We then explore the causalities between absolute returns of oil prices at different time scales. As traditional Granger causality test, designed to detect linear causality, is ineffective in uncovering certain nonlinear causal relationships, we use the nonlinear causality test introduced by Péguin-Feissolle and Teräsvirta (1999) and Péguin-Feissolle, Strikholm and Teräsvirta (2008). Our results confirm the fact that the vertical dependence is a strong stylised fact of oil returns volatility. But, the main finding consists on the presence of a feed- back effect from high frequency traders to low frequency traders. In contrast to Gençay et al. (2010), we prove that high frequency shocks could have an impact outside their boundaries and reach the long term traders.

Suggested Citation

  • François Benhmad, 2011. "A wavelet analysis of oil price volatility dynamic," Economics Bulletin, AccessEcon, vol. 31(1), pages 792-806.
    • Handle: RePEc:ebl:ecbull:eb-10-00632
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    References listed on IDEAS

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    1. Benassy-Quere, Agnes & Mignon, Valerie & Penot, Alexis, 2007. "China and the relationship between the oil price and the dollar," Energy Policy, Elsevier, vol. 35(11), pages 5795-5805, November.
    2. Péguin-Feissolle, Anne & Strikholm, Birgit & Teräsvirta, Timo, 2007. "Testing the Granger noncausality hypothesis in stationary nonlinear models of unknown functional form," SSE/EFI Working Paper Series in Economics and Finance 672, Stockholm School of Economics, revised 18 Jan 2012.
    3. Ramazan Gencay & Nikola Gradojevic & Faruk Selcuk & Brandon Whitcher, 2010. "Asymmetry of information flow between volatilities across time scales," Quantitative Finance, Taylor & Francis Journals, vol. 10(8), pages 895-915.
    4. Virginie Coudert & Valérie Mignon & Alexis Penot, 2008. "Oil Price and the Dollar," Post-Print halshs-00353404, HAL.
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    Citations

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    Cited by:

    1. Benhmad, François, 2013. "Dynamic cyclical comovements between oil prices and US GDP: A wavelet perspective," Energy Policy, Elsevier, vol. 57(C), pages 141-151.
    2. Madaleno, Mara & Pinho, Carlos, 2014. "Wavelet dynamics for oil-stock world interactions," Energy Economics, Elsevier, vol. 45(C), pages 120-133.
    3. Junsheng Ha & Pei-Pei Tan & Kim-Leng Goh, 2018. "Linear and nonlinear causal relationship between energy consumption and economic growth in China: New evidence based on wavelet analysis," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-21, May.
    4. Benhmad, François, 2013. "Bull or bear markets: A wavelet dynamic correlation perspective," Economic Modelling, Elsevier, vol. 32(C), pages 576-591.
    5. Benhmad, François, 2012. "Modeling nonlinear Granger causality between the oil price and U.S. dollar: A wavelet based approach," Economic Modelling, Elsevier, vol. 29(4), pages 1505-1514.

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    More about this item

    Keywords

    Causality; Wavelet decomposition; oil price volatility;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G1 - Financial Economics - - General Financial Markets

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