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Investigating price clustering in the oil futures market

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  • Narayan, Paresh Kumar
  • Narayan, Seema
  • Popp, Stephan

Abstract

Price clustering can be a source of market inefficiency. It follows that searching for price clustering in markets have gone beyond share prices into real estate, interest rate, and exchange rate markets. In this paper, we extend this line of research to oil futures markets. In particular, we consider five different forms of oil futures contracts and test for evidence of price clustering. Our results reveal strong presence of price clustering in the oil futures market. This finding implies that price clustering can potentially be a source of oil market inefficiency, which can influence trading strategies.

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  • Narayan, Paresh Kumar & Narayan, Seema & Popp, Stephan, 2011. "Investigating price clustering in the oil futures market," Applied Energy, Elsevier, vol. 88(1), pages 397-402, January.
  • Handle: RePEc:eee:appene:v:88:y:2011:i:1:p:397-402
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    References listed on IDEAS

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    Cited by:

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    3. Zhang, Yue-Jun & Yao, Ting, 2016. "Interpreting the movement of oil prices: Driven by fundamentals or bubbles?," Economic Modelling, Elsevier, vol. 55(C), pages 226-240.
    4. Li, Xin & Li, Shenghong & Xu, Chong, 2020. "Price clustering in Bitcoin market—An extension," Finance Research Letters, Elsevier, vol. 32(C).
    5. Baruník, Jozef & Malinská, Barbora, 2016. "Forecasting the term structure of crude oil futures prices with neural networks," Applied Energy, Elsevier, vol. 164(C), pages 366-379.
    6. Dowling, Michael & Cummins, Mark & Lucey, Brian M., 2016. "Psychological barriers in oil futures markets," Energy Economics, Elsevier, vol. 53(C), pages 293-304.
    7. Jakobsson, Kristofer & Söderbergh, Bengt & Snowden, Simon & Li, Chuan-Zhong & Aleklett, Kjell, 2012. "Oil exploration and perceptions of scarcity: The fallacy of early success," Energy Economics, Elsevier, vol. 34(4), pages 1226-1233.
    8. Cummins, Mark & Dowling, Michael & Lucey, Brian M., 2015. "Behavioral influences in non-ferrous metals prices," Resources Policy, Elsevier, vol. 45(C), pages 9-22.
    9. Christos Alexakis & Mark Cummins & Michael Dowling & Vasileios Pappas, 2018. "A high-frequency analysis of price resolution and pricing barriers in equities on the adoption of a new currency," Applied Economics, Taylor & Francis Journals, vol. 50(36), pages 3949-3965, August.
    10. Sensoy, Ahmet & Hacihasanoglu, Erk, 2014. "Time-varying long range dependence in energy futures markets," Energy Economics, Elsevier, vol. 46(C), pages 318-327.
    11. Christos Alexakis & Mark Cummins & Michael Dowling & Vasileios Pappas, 2018. "A High-Frequency Analysis of Price Resolution and Pricing Barriers in Equities on the Adoption of a New Currency," Post-Print hal-01994666, HAL.
    12. Paresh Narayan & Russell Smyth, 2014. "Applied Econometrics and a Decade of Energy Economics Research," Monash Economics Working Papers 21-14, Monash University, Department of Economics.
    13. Urquhart, Andrew, 2017. "Price clustering in Bitcoin," Economics Letters, Elsevier, vol. 159(C), pages 145-148.
    14. An, Haizhong & Gao, Xiangyun & Fang, Wei & Ding, Yinghui & Zhong, Weiqiong, 2014. "Research on patterns in the fluctuation of the co-movement between crude oil futures and spot prices: A complex network approach," Applied Energy, Elsevier, vol. 136(C), pages 1067-1075.
    15. Wang, Minggang & Chen, Ying & Tian, Lixin & Jiang, Shumin & Tian, Zihao & Du, Ruijin, 2016. "Fluctuation behavior analysis of international crude oil and gasoline price based on complex network perspective," Applied Energy, Elsevier, vol. 175(C), pages 109-127.

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