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Testing the evolution of crude oil market efficiency: Data have the conn

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  • Zhang, Bing
  • Li, Xiao-Ming
  • He, Fei

Abstract

Utilising a time-varying GAR (1)-TGARCH (1,1) model with different frequency data, we investigate the weak-form efficiency of major global crude oil spot markets in Europe, the US, the UAE and China for the period from December 2001 to August 2013. Our empirical results with weekly data indicate that all four markets have reached efficiency with few brief inefficient periods during the past decade, whereas the daily crude oil returns series suggest intermittent and inconsistent efficiency. We argue that the weekly Friday series fit the data better than the average series in autocorrelation tests. The evidence suggests that all four markets exhibit asymmetries in return-volatility reactions to different information shocks and that they react more strongly to bad news than to good news. The 2008 financial crisis has significantly affected the efficiency of oil markets. Furthermore, a comovement phenomenon and volatility spillover effects exist among the oil markets. Policy recommendations consistent with our empirical results are proposed, which address three issues: implementing prudential regulations, establishing an Asian pricing centre and improving transparency in crude oil spot markets.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:enepol:v:68:y:2014:i:c:p:39-52
    DOI: 10.1016/j.enpol.2013.12.052
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    References listed on IDEAS

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    1. Charles, Amélie & Darné, Olivier, 2009. "The efficiency of the crude oil markets: Evidence from variance ratio tests," Energy Policy, Elsevier, vol. 37(11), pages 4267-4272, November.
    2. Campbell, John Y. & Hentschel, Ludger, 1992. "No news is good news *1: An asymmetric model of changing volatility in stock returns," Journal of Financial Economics, Elsevier, vol. 31(3), pages 281-318, June.
    3. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    4. Christiane Baumeister & Gert Peersman, 2013. "The Role Of Time‐Varying Price Elasticities In Accounting For Volatility Changes In The Crude Oil Market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(7), pages 1087-1109, November.
    5. Green, Steven L & Mork, Knut Anton, 1991. "Toward Efficiency in the Crude-Oil Market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(1), pages 45-66, Jan.-Marc.
    6. Gu, Rongbao & Chen, Hongtao & Wang, Yudong, 2010. "Multifractal analysis on international crude oil markets based on the multifractal detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(14), pages 2805-2815.
    7. Gulen, S. Gurcan, 1998. "Efficiency in the crude oil futures market," Journal of Energy Finance & Development, Elsevier, vol. 3(1), pages 13-21.
    8. Xiao-Ming Li, 2003. "Time-varying Informational Efficiency in China's A-Share and B-Share Markets," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 1(1), pages 33-56.
    9. Lean, Hooi Hooi & McAleer, Michael & Wong, Wing-Keung, 2010. "Market efficiency of oil spot and futures: A mean-variance and stochastic dominance approach," Energy Economics, Elsevier, vol. 32(5), pages 979-986, September.
    10. El Hedi Arouri, Mohamed & Huong Dinh, Thanh & Khuong Nguyen, Duc, 2010. "Time-varying predictability in crude-oil markets: the case of GCC countries," Energy Policy, Elsevier, vol. 38(8), pages 4371-4380, August.
    11. Harvey,Andrew C., 1991. "Forecasting, Structural Time Series Models and the Kalman Filter," Cambridge Books, Cambridge University Press, number 9780521405737, December.
    12. Jiang, Zhi-Qiang & Xie, Wen-Jie & Zhou, Wei-Xing, 2014. "Testing the weak-form efficiency of the WTI crude oil futures market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 235-244.
    13. Wang, Yudong & Wei, Yu & Wu, Chongfeng, 2011. "Detrended fluctuation analysis on spot and futures markets of West Texas Intermediate crude oil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(5), pages 864-875.
    14. Christiane Baumeister & Gert Peersman, 2013. "Time-Varying Effects of Oil Supply Shocks on the US Economy," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(4), pages 1-28, October.
    15. Ortiz-Cruz, Alejandro & Rodriguez, Eduardo & Ibarra-Valdez, Carlos & Alvarez-Ramirez, Jose, 2012. "Efficiency of crude oil markets: Evidences from informational entropy analysis," Energy Policy, Elsevier, vol. 41(C), pages 365-373.
    16. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    17. Wang, Yudong & Liu, Li, 2010. "Is WTI crude oil market becoming weakly efficient over time?: New evidence from multiscale analysis based on detrended fluctuation analysis," Energy Economics, Elsevier, vol. 32(5), pages 987-992, September.
    18. 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.
    19. Ozdemir, Zeynel Abidin & Gokmenoglu, Korhan & Ekinci, Cagdas, 2013. "Persistence in crude oil spot and futures prices," Energy, Elsevier, vol. 59(C), pages 29-37.
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    Cited by:

    1. 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).
    2. 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.
    3. Adewuyi, Adeolu O. & Wahab, Bashir A. & Adeboye, Olusegun S., 2020. "Stationarity of prices of precious and industrial metals using recent unit root methods: Implications for markets’ efficiency," Resources Policy, Elsevier, vol. 65(C).
    4. Liu, Xueyong & An, Haizhong & Li, Huajiao & Chen, Zhihua & Feng, Sida & Wen, Shaobo, 2017. "Features of spillover networks in international financial markets: Evidence from the G20 countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 265-278.
    5. Górska, Anna & Krawiec, Monika, 2017. "Analiza efektywności informacyjnej w formie słabej na rynkach „soft commodities” z wykorzystaniem wybranych testów statystycznych," Problems of World Agriculture / Problemy Rolnictwa Światowego, Warsaw University of Life Sciences, vol. 17(32, Part ), September.
    6. Alvarez-Ramirez, J. & Alvarez, J. & Rodríguez, E., 2015. "Asymmetric long-term autocorrelations in crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 330-341.
    7. Wang, Lijun & An, Haizhong & Liu, Xiaojia & Huang, Xuan, 2016. "Selecting dynamic moving average trading rules in the crude oil futures market using a genetic approach," Applied Energy, Elsevier, vol. 162(C), pages 1608-1618.

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