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Oil Market Efficiency, Quantity of Information, and Oil Market Turbulence

Author

Listed:
  • Marc Gronwald
  • Sania Wadud
  • Kingsley Dogah

Abstract

This paper analyses the informational efficiency of the WTI crude oil markets using a recently proposed quantitative measure for market inefficiency. The procedure measures the extent to which observed oil price behaviour deviates from the Random Walk benchmark which represents an efficient market. The key findings are, first, that crude oil market inefficiency varies over time. Second, abrupt increases in inefficiency occur during extreme episodes such as the price downturns witnessed in 2008, 2014, and early 2020, as well as the begin of the Ukraine war in 2022. Third, the paper puts forward the interpretation of oil market inefficiency as oil market turbulence. This occurs when the quantity of information the market has to process is exceptionally high. Fourth, the paper demonstrates that oil market turbulence (or the drivers behind it) have negative macroeconomic consequences.

Suggested Citation

  • Marc Gronwald & Sania Wadud & Kingsley Dogah, 2024. "Oil Market Efficiency, Quantity of Information, and Oil Market Turbulence," CESifo Working Paper Series 10995, CESifo.
  • Handle: RePEc:ces:ceswps:_10995
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    References listed on IDEAS

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    1. Søren Johansen & Morten Ørregaard Nielsen, 2012. "Likelihood Inference for a Fractionally Cointegrated Vector Autoregressive Model," Econometrica, Econometric Society, vol. 80(6), pages 2667-2732, November.
    2. Shimotsu, Katsumi, 2010. "Exact Local Whittle Estimation Of Fractional Integration With Unknown Mean And Time Trend," Econometric Theory, Cambridge University Press, vol. 26(2), pages 501-540, April.
    3. Marc Gronwald, 2008. "Large Oil Shocks and the US Economy: Infrequent Incidents with Large Effects," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 151-172.
    4. De Bondt, Werner F M & Thaler, Richard, 1985. "Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    5. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    6. Kandel, Eugene & Pearson, Neil D, 1995. "Differential Interpretation of Public Signals and Trade in Speculative Markets," Journal of Political Economy, University of Chicago Press, vol. 103(4), pages 831-872, August.
    7. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
    8. French, Kenneth R. & Roll, Richard, 1986. "Stock return variances : The arrival of information and the reaction of traders," Journal of Financial Economics, Elsevier, vol. 17(1), pages 5-26, September.
    9. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    10. Ma, Xiaohan & Samaniego, Roberto, 2020. "The macroeconomic impact of oil earnings uncertainty: New evidence from analyst forecasts," Energy Economics, Elsevier, vol. 90(C).
    11. Abadir, Karim M. & Distaso, Walter & Giraitis, Liudas, 2007. "Nonstationarity-extended local Whittle estimation," Journal of Econometrics, Elsevier, vol. 141(2), pages 1353-1384, December.
    12. Kristoufek, Ladislav, 2019. "Are the crude oil markets really becoming more efficient over time? Some new evidence," Energy Economics, Elsevier, vol. 82(C), pages 253-263.
    13. Duan, Kun & Li, Zeming & Urquhart, Andrew & Ye, Jinqiang, 2021. "Dynamic efficiency and arbitrage potential in Bitcoin: A long-memory approach," International Review of Financial Analysis, Elsevier, vol. 75(C).
    14. Lutz Kilian, 2008. "Exogenous Oil Supply Shocks: How Big Are They and How Much Do They Matter for the U.S. Economy?," The Review of Economics and Statistics, MIT Press, vol. 90(2), pages 216-240, May.
    15. Christiane Baumeister & Lutz Kilian, 2016. "Understanding the Decline in the Price of Oil since June 2014," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 3(1), pages 131-158.
    16. Matteo, T. Di & Aste, T. & Dacorogna, Michel M., 2005. "Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 827-851, April.
    17. Johansen, SØren, 2008. "A Representation Theory For A Class Of Vector Autoregressive Models For Fractional Processes," Econometric Theory, Cambridge University Press, vol. 24(3), pages 651-676, June.
    18. Mitchell, Mark L & Mulherin, J Harold, 1994. "The Impact of Public Information on the Stock Market," Journal of Finance, American Finance Association, vol. 49(3), pages 923-950, July.
    19. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    20. Vlastakis, Nikolaos & Markellos, Raphael N., 2012. "Information demand and stock market volatility," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1808-1821.
    21. V Dimitrova & M Fernández-Martínez & M A Sánchez-Granero & J E Trinidad Segovia, 2019. "Some comments on Bitcoin market (in)efficiency," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-14, July.
    22. Brad M. Barber & Terrance Odean, 2001. "Boys will be Boys: Gender, Overconfidence, and Common Stock Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(1), pages 261-292.
    23. Shimotsu, Katsumi & Phillips, Peter C.B., 2006. "Local Whittle estimation of fractional integration and some of its variants," Journal of Econometrics, Elsevier, vol. 130(2), pages 209-233, February.
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    More about this item

    Keywords

    crude oil markets; efficient market hypothesis; quantity of information; fractional integration;
    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
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • Q31 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Demand and Supply; Prices

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