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OPEC News Announcement Effect on Volatility in the Crude Oil Market: A Reconsideration

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  • Rangan Gupta

    (Department of Economics, University of Pretoria, South Africa)

  • Chi Keung Marco Lau

    (Newcastle Business School, Northumbria University, UK)

  • Seong-Min Yoon

    (Department of Economics, Pusan National University, Republic of Korea)

Abstract

This paper uses a nonparametric quantile-based methodology to analyse the predictive ability of OPEC meeting dates and production announcements on (Brent Crude and West Texas Intermediate) oil a measure of futures market volatility that is robust to jumps. We found a nonlinear relationship between oil futures volatility and OPEC-based predictors; hence, linear Granger-causality tests are misspecified and the linear model results of nonpredictability are unreliable. Results of the quantile-causality test show that OPEC variables' impact on oil futures markets is restricted to Brent Crude futures, with no effect observed for the WTI market. Specifically, OPEC production announcements and meeting dates predict only lower quantiles of the conditional distribution of Brent futures market volatility – a much weaker result compared to when volatility models used in the literature are not robust to jump and outliers.

Suggested Citation

  • Rangan Gupta & Chi Keung Marco Lau & Seong-Min Yoon, 2019. "OPEC News Announcement Effect on Volatility in the Crude Oil Market: A Reconsideration," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(4), pages 1-23, December.
  • Handle: RePEc:aag:wpaper:v:23:y:2019:i:4:p:1-23
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    2. Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian & Yoon, Seong-Min, 2021. "OPEC news and jumps in the oil market," Energy Economics, Elsevier, vol. 96(C).

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    More about this item

    Keywords

    : Oil markets; Volatility; OPEC announcements.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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