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Testing the oil price efficiency using various measures of long-range dependence

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  • Tiwari, Aviral Kumar
  • Kumar, Satish
  • Pathak, Rajesh
  • Roubaud, David

Abstract

In this paper, we empirically examine the application of a host of techniques employed to measure price efficiency through long-range dependence using prices of monthly oil contracts. Using a series of methods, we analyse the volatility (daily absolute returns) of WTI and Brent oil prices for nine different contracts with maturity, ranging from 1 to 9 months, during the sample period of 1990-2017. We use bootstrapping to compute the confidence interval of the parameter of long-range dependence. Our results indicate that on an average, there is no long-range dependence in the volatility of oil price contracts at least at the 10-percent level of significance. Moreover, our results of rolling estimates suggest that the normality assumption does not affect the results considerably, and the results are robust to different rolling window sizes. While the results of the efficiency index suggest that the efficiency of oil returns vary with time, the futures contracts for Brent oil are found to be less efficient compared to WTI oil. The long-term futures contracts are more efficient than short-term contracts.

Suggested Citation

  • Tiwari, Aviral Kumar & Kumar, Satish & Pathak, Rajesh & Roubaud, David, 2019. "Testing the oil price efficiency using various measures of long-range dependence," Energy Economics, Elsevier, vol. 84(C).
  • Handle: RePEc:eee:eneeco:v:84:y:2019:i:c:s0140988319303421
    DOI: 10.1016/j.eneco.2019.104547
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    as
    1. Los, Cornelis A. & Yu, Bing, 2008. "Persistence characteristics of the Chinese stock markets," International Review of Financial Analysis, Elsevier, vol. 17(1), pages 64-82.
    2. Arouri, Mohamed El Hedi & Hammoudeh, Shawkat & Lahiani, Amine & Nguyen, Duc Khuong, 2013. "On the short- and long-run efficiency of energy and precious metal markets," Energy Economics, Elsevier, vol. 40(C), pages 832-844.
    3. Narayan, Paresh Kumar & Narayan, Seema & Zheng, Xinwei, 2010. "Gold and oil futures markets: Are markets efficient?," Applied Energy, Elsevier, vol. 87(10), pages 3299-3303, October.
    4. John Elder & Apostolos Serletis, 2008. "Long memory in energy futures prices," Review of Financial Economics, John Wiley & Sons, vol. 17(2), pages 146-155.
    5. Alvarez-Ramirez, Jose & Alvarez, Jesus & Solis, Ricardo, 2010. "Crude oil market efficiency and modeling: Insights from the multiscaling autocorrelation pattern," Energy Economics, Elsevier, vol. 32(5), pages 993-1000, September.
    6. Kristoufek, Ladislav & Vosvrda, Miloslav, 2013. "Measuring capital market efficiency: Global and local correlations structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(1), pages 184-193.
    7. Satish Kumar & Rajesh Pathak & Aviral Kumar Tiwari & Seong-Min Yoon, 2017. "Are exchange rates interdependent? Evidence using wavelet analysis," Applied Economics, Taylor & Francis Journals, vol. 49(33), pages 3231-3245, July.
    8. Serletis, Apostolos & Rosenberg, Aryeh Adam, 2007. "The Hurst exponent in energy futures prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 325-332.
    9. Zhang, Bing & Li, Xiao-Ming & He, Fei, 2014. "Testing the evolution of crude oil market efficiency: Data have the conn," Energy Policy, Elsevier, vol. 68(C), pages 39-52.
    10. Alvarez-Ramirez, Jose & Alvarez, Jesus & Rodriguez, Eduardo, 2008. "Short-term predictability of crude oil markets: A detrended fluctuation analysis approach," Energy Economics, Elsevier, vol. 30(5), pages 2645-2656, September.
    11. Fernandez Viviana, 2011. "Alternative Estimators of Long-Range Dependence," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(2), pages 1-37, March.
    12. Lorne N. Switzer & Mario El‐Khoury, 2007. "Extreme volatility, speculative efficiency, and the hedging effectiveness of the oil futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 27(1), pages 61-84, January.
    13. repec:clg:wpaper:2007-02 is not listed on IDEAS
    14. Amélie Charles & Olivier Darné, 2009. "Variance‐Ratio Tests Of Random Walk: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 23(3), pages 503-527, July.
    15. Tabak, Benjamin M. & Cajueiro, Daniel O., 2007. "Are the crude oil markets becoming weakly efficient over time? A test for time-varying long-range dependence in prices and volatility," Energy Economics, Elsevier, vol. 29(1), pages 28-36, January.
    16. Caraiani, Petre, 2012. "Money and output: New evidence based on wavelet coherence," Economics Letters, Elsevier, vol. 116(3), pages 547-550.
    17. Lee, Chien-Chiang & Lee, Jun-De, 2009. "Energy prices, multiple structural breaks, and efficient market hypothesis," Applied Energy, Elsevier, vol. 86(4), pages 466-479, April.
    18. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    19. Ghazani, Majid Mirzaee & Ebrahimi, Seyed Babak, 2019. "Testing the adaptive market hypothesis as an evolutionary perspective on market efficiency: Evidence from the crude oil prices," Finance Research Letters, Elsevier, vol. 30(C), pages 60-68.
    20. Sensoy, Ahmet & Hacihasanoglu, Erk, 2014. "Time-varying long range dependence in energy futures markets," Energy Economics, Elsevier, vol. 46(C), pages 318-327.
    21. Gu, Rongbao & Zhang, Bing, 2016. "Is efficiency of crude oil market affected by multifractality? Evidence from the WTI crude oil market," Energy Economics, Elsevier, vol. 53(C), pages 151-158.
    22. Zhang, Bing, 2013. "Are the crude oil markets becoming more efficient over time? New evidence from a generalized spectral test," Energy Economics, Elsevier, vol. 40(C), pages 875-881.
    23. Apostolos Serletis, 1992. "The Random Walk in Canadian Output," Canadian Journal of Economics, Canadian Economics Association, vol. 25(2), pages 392-406, May.
    24. Wang, Yudong & Wu, Chongfeng, 2012. "Long memory in energy futures markets: Further evidence," Resources Policy, Elsevier, vol. 37(3), pages 261-272.
    25. Connor Jeff & Rossiter Rosemary, 2005. "Wavelet Transforms and Commodity Prices," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(1), pages 1-22, March.
    26. Shambora, William E. & Rossiter, Rosemary, 2007. "Are there exploitable inefficiencies in the futures market for oil?," Energy Economics, Elsevier, vol. 29(1), pages 18-27, January.
    27. Juncal Cunado & Luis A. Gil‐Alana & Fernando Perez de Gracia, 2010. "Persistence in some energy futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 30(5), pages 490-507, May.
    28. Yudong Wang & Chongfeng Wu, 2013. "Efficiency of Crude Oil Futures Markets: New Evidence from Multifractal Detrending Moving Average Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 42(4), pages 393-414, December.
    29. Kian‐Ping Lim & Robert Brooks, 2011. "The Evolution Of Stock Market Efficiency Over Time: A Survey Of The Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 69-108, February.
    30. C. W. J. Granger & Roselyne Joyeux, 1980. "An Introduction To Long‐Memory Time Series Models And Fractional Differencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 15-29, January.
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    More about this item

    Keywords

    Long-range dependence; Oil price efficiency; Brent; WTI;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools

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