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Crude oil price and implied volatility

Author

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  • Panos Fousekis

Abstract

Purpose - The purpose of this study is to investigate empirically the pattern of co-movement between prices and implied volatility in the future markets for crude oil. Design/methodology/approach - The tool of non-parametric quantile regression is applied to daily price returns and implied volatility changes from 2007 to 2018. Findings - For the total sample period, the link between price returns and forward-looking volatility expectations is contemporaneous, negative and asymmetric, and it exhibits an (approximately) inverted U-shaped pattern suggesting that: the pricing of implied volatility is heavier for large (in absolute value terms) changes relative to small ones and it is lighter for large positive changes relative to large negative ones. The pattern of co-movement, therefore, appears to be in line with the theoretical postulates of fear, exuberance and loss aversion. The main characteristics of the relationship are present in some (but not in all) sub-periods, which are also considered in this study. Originality/value - Less than a handful of works have assessed the link between implied volatility and prices for commodity ETFs. This is the first one relying on flexible non-parametric quantile regressions.

Suggested Citation

  • Panos Fousekis, 2019. "Crude oil price and implied volatility," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 36(2), pages 168-182, May.
    • Handle: RePEc:eme:sefpps:sef-04-2018-0117
    DOI: 10.1108/SEF-04-2018-0117
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    Citations

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    Cited by:

    1. Dimitrios Panagiotou, 2021. "Re-examining the leverage effect and gold’s safe haven properties with the utilization of the implied volatility of gold: a non-parametric quantile regression approach," SN Business & Economics, Springer, vol. 1(7), pages 1-18, July.
    2. Fassas, Athanasios P. & Siriopoulos, Costas, 2021. "Implied volatility indices – A review," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 303-329.
    3. Yang, Kun & Wei, Yu & Li, Shouwei & Liu, Liang & Wang, Lei, 2021. "Global financial uncertainties and China’s crude oil futures market: Evidence from interday and intraday price dynamics," Energy Economics, Elsevier, vol. 96(C).

    More about this item

    Keywords

    Volatility; Non-parametric quantile regression; Oil prices; G10; C12;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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