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Efficiency of crude oil markets: Evidences from informational entropy analysis

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  1. Cagli, Efe Caglar & Taskin, Dilvin & Evrim Mandaci, Pınar, 2019. "The short- and long-run efficiency of energy, precious metals, and base metals markets: Evidence from the exponential smooth transition autoregressive models," Energy Economics, Elsevier, vol. 84(C).
  2. Tiwari, Aviral Kumar & Umar, Zaghum & Alqahtani, Faisal, 2021. "Existence of long memory in crude oil and petroleum products: Generalised Hurst exponent approach," Research in International Business and Finance, Elsevier, vol. 57(C).
  3. Fernandes, Leonardo H.S. & Araújo, Fernando H.A., 2020. "Taxonomy of commodities assets via complexity-entropy causality plane," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
  4. Aurelio F. Bariviera & Luciano Zunino & M. Belen Guercio & Lisana B. Martinez & Osvaldo A. Rosso, 2015. "Efficiency and credit ratings: a permutation-information-theory analysis," Papers 1509.01839, arXiv.org.
  5. Bariviera, Aurelio F. & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2016. "Libor at crossroads: Stochastic switching detection using information theory quantifiers," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 172-182.
  6. 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).
  7. George P. Papaioannou & Christos Dikaiakos & Akylas C. Stratigakos & Panos C. Papageorgiou & Konstantinos F. Krommydas, 2019. "Testing the Efficiency of Electricity Markets Using a New Composite Measure Based on Nonlinear TS Tools," Energies, MDPI, vol. 12(4), pages 1-30, February.
  8. Kristoufek, Ladislav & Vosvrda, Miloslav, 2016. "Gold, currencies and market efficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 27-34.
  9. 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.
  10. Gil-Alana, Luis A. & Gupta, Rangan & Olubusoye, Olusanya E. & Yaya, OlaOluwa S., 2016. "Time series analysis of persistence in crude oil price volatility across bull and bear regimes," Energy, Elsevier, vol. 109(C), pages 29-37.
  11. Wang, Xiao-Qing & Su, Chi-Wei & Lobonţ, Oana-Ramona & Li, Hao & Nicoleta-Claudia, Moldovan, 2022. "Is China's carbon trading market efficient? Evidence from emissions trading scheme pilots," Energy, Elsevier, vol. 245(C).
  12. 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.
  13. Pu, Yingjian & Yang, Baochen, 2022. "The commodity futures' historical basis in trading strategy and portfolio investment," Energy Economics, Elsevier, vol. 105(C).
  14. 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.
  15. Sensoy, Ahmet & Hacihasanoglu, Erk, 2014. "Time-varying long range dependence in energy futures markets," Energy Economics, Elsevier, vol. 46(C), pages 318-327.
  16. Aurelio Fernandez Bariviera & M. Bel'en Guercio & Lisana B. Martinez, 2015. "Data manipulation detection via permutation information theory quantifiers," Papers 1501.04123, arXiv.org.
  17. Fan, Xinghua & Li, Shasha & Tian, Lixin, 2016. "Complexity of carbon market from multi-scale entropy analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 79-85.
  18. Cerqueti, Roy & Fanelli, Viviana & Rotundo, Giulia, 2019. "Long run analysis of crude oil portfolios," Energy Economics, Elsevier, vol. 79(C), pages 183-205.
  19. F. Benedetto & L. Mastroeni & P. Vellucci, 2021. "Modeling the flow of information between financial time-series by an entropy-based approach," Annals of Operations Research, Springer, vol. 299(1), pages 1235-1252, April.
  20. Benedetto, F. & Giunta, G. & Mastroeni, L., 2016. "On the predictability of energy commodity markets by an entropy-based computational method," Energy Economics, Elsevier, vol. 54(C), pages 302-312.
  21. Liu, Jian & Jiang, Ting & Ye, Ze, 2021. "Information efficiency research of China's carbon markets," Finance Research Letters, Elsevier, vol. 38(C).
  22. 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.
  23. Wang, Jingjing & Wang, Xiaoyang, 2021. "COVID-19 and financial market efficiency: Evidence from an entropy-based analysis," Finance Research Letters, Elsevier, vol. 42(C).
  24. Argyroudis, George S. & Siokis, Fotios M., 2019. "Spillover effects of Great Recession on Hong-Kong’s Real Estate Market: An analysis based on Causality Plane and Tsallis Curves of Complexity–Entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 576-586.
  25. Zunino, Luciano & Bariviera, Aurelio F. & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2016. "Monitoring the informational efficiency of European corporate bond markets with dynamical permutation min-entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 1-9.
  26. Tokic, Damir, 2015. "The 2014 oil bust: Causes and consequences," Energy Policy, Elsevier, vol. 85(C), pages 162-169.
  27. 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.
  28. Teng, Yue & Shang, Pengjian, 2017. "Transfer entropy coefficient: Quantifying level of information flow between financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 60-70.
  29. Memon, Bilal Ahmed & Yao, Hongxing & Naveed, Hafiz Muhammad, 2022. "Examining the efficiency and herding behavior of commodity markets using multifractal detrended fluctuation analysis. Empirical evidence from energy, agriculture, and metal markets," Resources Policy, Elsevier, vol. 77(C).
  30. Leng, Na & Li, Jiang-Cheng, 2020. "Forecasting the crude oil prices based on Econophysics and Bayesian approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
  31. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Commodity futures and market efficiency," Energy Economics, Elsevier, vol. 42(C), pages 50-57.
  32. Aurelio Fernandez Bariviera & María Belén Guercio & Lisana B. Martinez & Osvaldo A. Rosso, 2015. "The (in)visible hand in the Libor market: an information theory approach," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(8), pages 1-9, August.
  33. Peng Chen & Andrew Vivian & Cheng Ye, 2022. "Forecasting carbon futures price: a hybrid method incorporating fuzzy entropy and extreme learning machine," Annals of Operations Research, Springer, vol. 313(1), pages 559-601, June.
  34. Kunal Saha & Vinodh Madhavan & G. R. Chandrashekhar, 2022. "Effect of COVID-19 on ETF and index efficiency: evidence from an entropy-based analysis," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(2), pages 347-359, April.
  35. Yin, Jiuli & Zhu, Yan & Fan, Xinghua, 2021. "Correlation analysis of China’s carbon market and coal market based on multi-scale entropy," Resources Policy, Elsevier, vol. 72(C).
  36. 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).
  37. Esra ALP & Ünal SEVEN, 2019. "Türkiye Konut Piyasasında Etkinlik Analizi," Istanbul Business Research, Istanbul University Business School, vol. 48(1), pages 84-112, May.
  38. 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.
  39. Siokis, Fotios M., 2018. "Credit market Jitters in the course of the financial crisis: A permutation entropy approach in measuring informational efficiency in financial assets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 266-275.
  40. Okorie, David Iheke & Lin, Boqiang, 2021. "Adaptive market hypothesis: The story of the stock markets and COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
  41. Espinosa-Paredes, G. & Rodriguez, E. & Alvarez-Ramirez, J., 2022. "A singular value decomposition entropy approach to assess the impact of Covid-19 on the informational efficiency of the WTI crude oil market," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
  42. Roy Cerqueti & Viviana Fanelli, 2021. "Long memory and crude oil’s price predictability," Annals of Operations Research, Springer, vol. 299(1), pages 895-906, April.
  43. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa & Stosic, Tatijana, 2016. "Correlations of multiscale entropy in the FX market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 52-61.
  44. Aurelio F. Bariviera & Luciano Zunino & Osvaldo A. Rosso, 2018. "An analysis of high-frequency cryptocurrencies prices dynamics using permutation-information-theory quantifiers," Papers 1808.01926, arXiv.org.
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