IDEAS home Printed from https://ideas.repec.org/a/cii/cepiie/2014-q4-140-6.html
   My bibliography  Save this article

Structural breaks and the time-varying levels of weak-form efficiency in crude oil markets: Evidence from the Hurst exponent and Shannon entropy methods

Author

Listed:
  • Walid Mensi
  • Makram Beljid
  • Shunsuke Managi

Abstract

This paper examines the time-varying levels of weak-form efficiency and the presence of structural breaks for two worldwide crude oil benchmarks over the period spanning from January 2, 1990, through September 18, 2012. We use two different econophysics approaches for comparison purposes. The Hurst exponent is provided by the scaled range R/S analysis to measure the degree of long-range dependency exhibited by the West Texas Intermediate (WTI) and European Brent crude oil indices. The Shannon entropy approach, which is based on a symbolic time series analysis (STSA), allows a ranking of market-level efficiency. The empirical results show that the European Brent index is less inefficient than the WTI index for both methods. Moreover, we find that the Hurst exponent displays better performance than the Shannon entropy method. The Hurst exponent is also more effective than the Shannon entropy in detecting financial crashes and crises as well as extreme events, such as wars and terrorist attacks. These findings have several implications for commodity portfolio hedgers and risk managers.

Suggested Citation

  • Walid Mensi & Makram Beljid & Shunsuke Managi, 2014. "Structural breaks and the time-varying levels of weak-form efficiency in crude oil markets: Evidence from the Hurst exponent and Shannon entropy methods," International Economics, CEPII research center, issue 140, pages 89-106.
    • Handle: RePEc:cii:cepiie:2014-q4-140-6
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S2110701714000493
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mensi, Walid & Tiwari, Aviral Kumar & Yoon, Seong-Min, 2017. "Global financial crisis and weak-form efficiency of Islamic sectoral stock markets: An MF-DFA analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 135-146.
    2. Anis Hoayek & Hassan Hamie & Hans Auer, 2020. "Modeling the Price Stability and Predictability of Post Liberalized Gas Markets Using the Theory of Information," Post-Print emse-03604655, HAL.
    3. Matthieu Garcin, 2023. "Complexity measure, kernel density estimation, bandwidth selection, and the efficient market hypothesis," Papers 2305.13123, arXiv.org.
    4. Clement Moyo & Izunna Anyikwa & Andrew Phiri, 2023. "The Impact of Covid-19 on Oil Market Returns: Has Market Efficiency Being Violated?," International Journal of Energy Economics and Policy, Econjournals, vol. 13(1), pages 118-127, January.
    5. Jebabli, Ikram & Roubaud, David, 2018. "Time-varying efficiency in food and energy markets: Evidence and implications," Economic Modelling, Elsevier, vol. 70(C), pages 97-114.
    6. Xavier Brouty & Matthieu Garcin, 2022. "A statistical test of market efficiency based on information theory," Working Papers hal-03760478, HAL.
    7. Miguel Henry & George Judge, 2019. "Permutation Entropy and Information Recovery in Nonlinear Dynamic Economic Time Series," Econometrics, MDPI, vol. 7(1), pages 1-16, March.
    8. Arshad, Shaista & Rizvi, Syed Aun R. & Haroon, Omair & Mehmood, Fahad & Gong, Qiang, 2021. "Are oil prices efficient?," Economic Modelling, Elsevier, vol. 96(C), pages 362-370.
    9. Cesario Mateus & Bao Trung Hoang, 2021. "Frontier Markets, Liberalization and Informational Efficiency: Evidence from Vietnam," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(4), pages 499-526, December.
    10. Ren, Minghui & Zhao, Guangsi & Zhou, Guoqing & Qiu, Xianhao & Xue, Qinghua & Chen, Meiting, 2018. "Using strain dynamics for fracture warning of shaft lining," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 406-413.
    11. Wang, Xiaoyang, 2022. "Efficient markets are more connected: An entropy-based analysis of the energy, industrial metal and financial markets," Energy Economics, Elsevier, vol. 111(C).
    12. Aharon, David Y. & Azman Aziz, Mukhriz Izraf & Kallir, Ido, 2023. "Oil price shocks and inflation: A cross-national examination in the ASEAN5+3 countries," Resources Policy, Elsevier, vol. 82(C).
    13. Mensi, Walid & Tiwari, Aviral Kumar & Al-Yahyaee, Khamis Hamed, 2019. "An analysis of the weak form efficiency, multifractality and long memory of global, regional and European stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 72(C), pages 168-177.
    14. Mensi, Walid & Hamdi, Atef & Shahzad, Syed Jawad Hussain & Shafiullah, Muhammad & Al-Yahyaee, Khamis Hamed, 2018. "Modeling cross-correlations and efficiency of Islamic and conventional banks from Saudi Arabia: Evidence from MF-DFA and MF-DXA approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 576-589.
    15. Alaba, Oluwayemisi O. & Ojo, Oluwadare O. & Yaya, OlaOluwa S & Abu, Nurudeen & Ajobo, Saheed A., 2021. "Comparative Analysis of Market Efficiency and Volatility of Energy Prices Before and During COVID-19 Pandemic Periods," MPRA Paper 109825, University Library of Munich, Germany.
    16. Elie Bouri & Imad Kachacha & Donald Lien & David Roubaud, 2017. "Short- and long-run causality across the implied volatility of crude oil and agricultural commodities," Economics Bulletin, AccessEcon, vol. 37(2).
    17. Anis Hoayek & Hassan Hamie & Hans Auer, 2020. "Modeling the Price Stability and Predictability of Post Liberalized Gas Markets Using the Theory of Information," Energies, MDPI, vol. 13(11), pages 1-20, June.
    18. Xavier Brouty & Matthieu Garcin, 2022. "A statistical test of market efficiency based on information theory," Papers 2208.11976, arXiv.org.
    19. Matthieu Garcin, 2023. "Complexity measure, kernel density estimation, bandwidth selection, and the efficient market hypothesis," Working Papers hal-04102815, HAL.
    20. de Area Leão Pereira, Eder Johnson & da Silva, Marcus Fernandes & Pereira, H.B.B., 2017. "Econophysics: Past and present," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 251-261.

    More about this item

    Keywords

    Oil market efficiency; Structural breaks; Hurst exponent; Shannon entropy; Rolling approach;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cii:cepiie:2014-q4-140-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/cepiifr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.