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Is WTI crude oil market becoming weakly efficient over time?: New evidence from multiscale analysis based on detrended fluctuation analysis

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  1. 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).
  2. Sibanjan Mishra, 2019. "Testing Martingale Hypothesis Using Variance Ratio Tests: Evidence from High-frequency Data of NCDEX Soya Bean Futures," Global Business Review, International Management Institute, vol. 20(6), pages 1407-1422, December.
  3. Li, Jianfeng & Lu, Xinsheng & Zhou, Ying, 2016. "Cross-correlations between crude oil and exchange markets for selected oil rich economies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 131-143.
  4. 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.
  5. Yang, Chen & Lv, Fei & Fang, Libing & Shang, Xingxing, 2020. "The pricing efficiency of crude oil futures in the Shanghai International Exchange," Finance Research Letters, Elsevier, vol. 36(C).
  6. Hongtao Chen & Lianghua Chen, 2015. "Multifractal spectrum analysis of Brent crude oil futures prices volatility in intercontinental exchange," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 38(1/2/3), pages 93-108.
  7. Yuan, Ying & Zhuang, Xin-tian & Jin, Xiu & Huang, Wei-qiang, 2014. "Stable distribution and long-range correlation of Brent crude oil market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 173-179.
  8. Duan, Kun & Li, Zeming & Urquhart, Andrew & Ye, Jinqiang, 2021. "Dynamic efficiency and arbitrage potential in Bitcoin: A long-memory approach," International Review of Financial Analysis, Elsevier, vol. 75(C).
  9. Wang, Yudong & Wu, Chongfeng, 2012. "Energy prices and exchange rates of the U.S. dollar: Further evidence from linear and nonlinear causality analysis," Economic Modelling, Elsevier, vol. 29(6), pages 2289-2297.
  10. Wang, Yudong & Wu, Chongfeng, 2012. "Long memory in energy futures markets: Further evidence," Resources Policy, Elsevier, vol. 37(3), pages 261-272.
  11. Wang, Yudong & Wu, Chongfeng & Yang, Li, 2016. "Forecasting crude oil market volatility: A Markov switching multifractal volatility approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 1-9.
  12. Wang, Yudong & Wu, Chongfeng, 2013. "Are crude oil spot and futures prices cointegrated? Not always!," Economic Modelling, Elsevier, vol. 33(C), pages 641-650.
  13. Wei, Yu & Wang, Yudong & Huang, Dengshi, 2011. "A copula–multifractal volatility hedging model for CSI 300 index futures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4260-4272.
  14. Li Jingjing & Tang Ling & Li Ling, 2020. "The Co-Movements Between Crude Oil Price and Internet Concerns: Causality Analysis in the Frequency Domain," Journal of Systems Science and Information, De Gruyter, vol. 8(3), pages 224-239, June.
  15. Li, Shuping & Lu, Xinsheng & Li, Jianfeng, 2021. "Cross-correlations between the P2P interest rate, Shibor and treasury yields," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
  16. Ruan, Qingsong & Bao, Junjie & Zhang, Manqian & Fan, Limin, 2019. "The effects of exchange rate regime reform on RMB markets: A new perspective based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 122-134.
  17. Zhang, Shuchang & Guo, Yaoqi & Cheng, Hui & Zhang, Hongwei, 2021. "Cross-correlations between price and volume in China's crude oil futures market: A study based on multifractal approaches," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
  18. 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.
  19. Ruan, Qingsong & Huang, Ying & Jiang, Wei, 2016. "The exceedance and cross-correlations between the gold spot and futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 139-151.
  20. Zhuang, Xiaoyang & Wei, Yu & Ma, Feng, 2015. "Multifractality, efficiency analysis of Chinese stock market and its cross-correlation with WTI crude oil price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 101-113.
  21. 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.
  22. 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.
  23. Huang, Xuan & An, Haizhong & Gao, Xiangyun & Hao, Xiaoqing & Liu, Pengpeng, 2015. "Multiresolution transmission of the correlation modes between bivariate time series based on complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 493-506.
  24. 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.
  25. Wang, Yudong & Wu, Chongfeng, 2012. "What can we learn from the history of gasoline crack spreads?: Long memory, structural breaks and modeling implications," Economic Modelling, Elsevier, vol. 29(2), pages 349-360.
  26. 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.
  27. 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.
  28. Martina, Esteban & Rodriguez, Eduardo & Escarela-Perez, Rafael & Alvarez-Ramirez, Jose, 2011. "Multiscale entropy analysis of crude oil price dynamics," Energy Economics, Elsevier, vol. 33(5), pages 936-947, September.
  29. Guo, Yaoqi & Shi, Fengyuan & Yu, Zhuling & Yao, Shanshan & Zhang, Hongwei, 2022. "Asymmetric multifractality in China’s energy market based on improved asymmetric multifractal cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
  30. Lubnau, Thorben & Todorova, Neda, 2015. "Trading on mean-reversion in energy futures markets," Energy Economics, Elsevier, vol. 51(C), pages 312-319.
  31. Li, Daye & Nishimura, Yusaku & Men, Ming, 2016. "The long memory and the transaction cost in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 312-320.
  32. Shaista Arshad, 2017. "Analysing the Relationship between Oil Prices and Islamic Stock Markets," Economic Papers, The Economic Society of Australia, vol. 36(4), pages 429-443, December.
  33. Liu, Li & Chen, Ching-Cheng & Wan, Jieqiu, 2013. "Is world oil market “one great pool”?: An example from China's and international oil markets," Economic Modelling, Elsevier, vol. 35(C), pages 364-373.
  34. Wang, Yudong & Wu, Chongfeng & Wei, Yu, 2011. "Can GARCH-class models capture long memory in WTI crude oil markets?," Economic Modelling, Elsevier, vol. 28(3), pages 921-927, May.
  35. Khaled Mokni & Manel Youssef, 2020. "Empirical analysis of the cross‐interdependence between crude oil and agricultural commodity markets," Review of Financial Economics, John Wiley & Sons, vol. 38(4), pages 635-654, October.
  36. Li, Zhihui & Lu, Xinsheng, 2012. "Cross-correlations between agricultural commodity futures markets in the US and China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(15), pages 3930-3941.
  37. Wang, Yudong & Liu, Li & Ma, Feng & Wu, Chongfeng, 2016. "What the investors need to know about forecasting oil futures return volatility," Energy Economics, Elsevier, vol. 57(C), pages 128-139.
  38. Yuan, PengCheng & Lin, XuXun, 2017. "How long will the traffic flow time series keep efficacious to forecast the future?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 419-431.
  39. O-Chia Chuang & Chenxu Yang, 2022. "Identifying the Determinants of Crude Oil Market Volatility by the Multivariate GARCH-MIDAS Model," Energies, MDPI, vol. 15(8), pages 1-14, April.
  40. Faheem Aslam & Paulo Ferreira & Haider Ali, 2022. "Analysis of the Impact of COVID-19 Pandemic on the Intraday Efficiency of Agricultural Futures Markets," JRFM, MDPI, vol. 15(12), pages 1-18, December.
  41. Li, Daye & Nishimura, Yusaku & Men, Ming, 2016. "Why the long-term auto-correlation has not been eliminated by arbitragers: Evidences from NYMEX," Energy Economics, Elsevier, vol. 59(C), pages 167-178.
  42. Liu, Li & Wang, Yudong & Wu, Chongfeng & Wu, Wenfeng, 2016. "Disentangling the determinants of real oil prices," Energy Economics, Elsevier, vol. 56(C), pages 363-373.
  43. Zhuang, Xiaoyang & Wei, Yu & Zhang, Bangzheng, 2014. "Multifractal detrended cross-correlation analysis of carbon and crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 113-125.
  44. Liu, Li & Wan, Jieqiu, 2011. "A study of correlations between crude oil spot and futures markets: A rolling sample test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3754-3766.
  45. Sensoy, Ahmet & Hacihasanoglu, Erk, 2014. "Time-varying long range dependence in energy futures markets," Energy Economics, Elsevier, vol. 46(C), pages 318-327.
  46. 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.
  47. Chen, Hongtao & Wu, Chongfeng, 2011. "Forecasting volatility in Shanghai and Shenzhen markets based on multifractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(16), pages 2926-2935.
  48. Benjamin Rainer Auer, 2018. "Are standard asset pricing factors long-range dependent?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(1), pages 66-88, January.
  49. Li, Daye & Kou, Zhun & Sun, Qiankun, 2015. "The scale-dependent market trend: Empirical evidences using the lagged DFA method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 26-35.
  50. Ibarra-Valdez, C. & Alvarez, J. & Alvarez-Ramirez, J., 2016. "Randomness confidence bands of fractal scaling exponents for financial price returns," Chaos, Solitons & Fractals, Elsevier, vol. 83(C), pages 119-124.
  51. 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.
  52. Cerqueti, Roy & Fanelli, Viviana & Rotundo, Giulia, 2019. "Long run analysis of crude oil portfolios," Energy Economics, Elsevier, vol. 79(C), pages 183-205.
  53. Zhang, Xin & Zhu, Yingming & Yang, Liansheng, 2018. "Multifractal detrended cross-correlations between Chinese stock market and three stock markets in The Belt and Road Initiative," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 105-115.
  54. Xia, Jianan & Shang, Pengjian & Lu, Dan & Yin, Yi, 2016. "A comprehensive segmentation analysis of crude oil market based on time irreversibility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 104-114.
  55. Wang, Yudong & Wei, Yu & Wu, Chongfeng, 2011. "Analysis of the efficiency and multifractality of gold markets based on multifractal detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(5), pages 817-827.
  56. Liu, Li & Wang, Yudong & Wan, Jieqiu, 2010. "Analysis of efficiency for Shenzhen stock market: Evidence from the source of multifractality," International Review of Financial Analysis, Elsevier, vol. 19(4), pages 237-241, September.
  57. Khalfaoui, Rabeh, 2018. "Oil–gold time varying nexus: A time–frequency analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 86-104.
  58. Zheng, Shiyuan & Lan, Xiangang, 2016. "Multifractal analysis of spot rates in tanker markets and their comparisons with crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 547-559.
  59. Olga Y. Uritskaya & Vadim M. Uritsky, 2015. "Predictability of price movements in deregulated electricity markets," Papers 1505.08117, arXiv.org.
  60. Pan, Zhiyuan & Wang, Yudong & Wu, Chongfeng & Yin, Libo, 2017. "Oil price volatility and macroeconomic fundamentals: A regime switching GARCH-MIDAS model," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 130-142.
  61. 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.
  62. Wang, Yudong & Wei, Yu & Wu, Chongfeng, 2010. "Auto-correlated behavior of WTI crude oil volatilities: A multiscale perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5759-5768.
  63. García-Carranco, Sergio M. & Bory-Reyes, Juan & Balankin, Alexander S., 2016. "The crude oil price bubbling and universal scaling dynamics of price volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 60-68.
  64. Bariviera, Aurelio F. & Fabregat-Aibar, Laura & Sorrosal-Forradellas, Maria-Teresa, 2023. "Disentangling the impact of economic and health crises on financial markets," Research in International Business and Finance, Elsevier, vol. 65(C).
  65. Li, Wen & Yu, Cindy & Carriquiry, Alicia & Kliemann, Wolfgang, 2011. "The asymptotic behavior of the R/S statistic for fractional Brownian motion," Statistics & Probability Letters, Elsevier, vol. 81(1), pages 83-91, January.
  66. Ruan, Qingsong & Zhou, Mi & Yin, Linsen & Lv, Dayong, 2021. "Hedging effectiveness of Chinese Treasury bond futures: New evidence based on nonlinear analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
  67. 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.
  68. Pal, Mayukha & Madhusudana Rao, P. & Manimaran, P., 2014. "Multifractal detrended cross-correlation analysis on gold, crude oil and foreign exchange rate time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 452-460.
  69. Kang, Sang Hoon & Yoon, Seong-Min, 2013. "Modeling and forecasting the volatility of petroleum futures prices," Energy Economics, Elsevier, vol. 36(C), pages 354-362.
  70. Tao Yin & Yiming Wang, 2021. "Market Efficiency and Nonlinear Analysis of Soybean Futures," Sustainability, MDPI, vol. 13(2), pages 1-10, January.
  71. Zhuang, Xiaoyang & Wei, Dan, 2022. "Asymmetric multifractality, comparative efficiency analysis of green finance markets: A dynamic study by index-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
  72. Uritskaya, Olga Y. & Uritsky, Vadim M., 2015. "Predictability of price movements in deregulated electricity markets," Energy Economics, Elsevier, vol. 49(C), pages 72-81.
  73. Tokic, Damir, 2015. "The 2014 oil bust: Causes and consequences," Energy Policy, Elsevier, vol. 85(C), pages 162-169.
  74. 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.
  75. Chen, Hongtao & Liu, Li & Li, Xiaolei, 2018. "The predictive content of CBOE crude oil volatility index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 837-850.
  76. Liu, Li, 2014. "Cross-correlations between crude oil and agricultural commodity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 293-302.
  77. Zhang, Yahui & Liu, Li, 2018. "The lead-lag relationships between spot and futures prices of natural gas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 203-211.
  78. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Commodity futures and market efficiency," Energy Economics, Elsevier, vol. 42(C), pages 50-57.
  79. Lv, Xiaodong & Shan, Xian, 2013. "Modeling natural gas market volatility using GARCH with different distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5685-5699.
  80. Aurelio Fernández Bariviera & M. Belén Guercio & Lisana B. Martinez, 2014. "Informational Efficiency in Distressed Markets: The Case of European Corporate Bonds," The Economic and Social Review, Economic and Social Studies, vol. 45(3), pages 349-369.
  81. Ruan, Qingsong & Jiang, Wei & Ma, Guofeng, 2016. "Cross-correlations between price and volume in Chinese gold markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 10-22.
  82. Kim, Hongseok & Oh, Gabjin & Kim, Seunghwan, 2011. "Multifractal analysis of the Korean agricultural market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4286-4292.
  83. Kristoufek, Ladislav, 2019. "Are the crude oil markets really becoming more efficient over time? Some new evidence," Energy Economics, Elsevier, vol. 82(C), pages 253-263.
  84. Yuan, Ying & Zhuang, Xin-tian & Liu, Zhi-ying & Huang, Wei-qiang, 2014. "Analysis of the temporal properties of price shock sequences in crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 235-246.
  85. Lubnau, Thorben, 2014. "Spread trading strategies in the crude oil futures market," Discussion Papers 353, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
  86. Liang Hu & Yoon‐Jin Lee, 2024. "New evidence on crude oil market efficiency," Economic Inquiry, Western Economic Association International, vol. 62(2), pages 892-916, April.
  87. 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.
  88. Ruan, Qingsong & Cui, Hao & Fan, Liming, 2020. "China’s soybean crush spread: Nonlinear analysis based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
  89. Nima Nonejad, 2020. "A detailed look at crude oil price volatility prediction using macroeconomic variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1119-1141, November.
  90. 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).
  91. 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).
  92. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Mefteh-Wali, Salma & Owusu, Patrick, 2023. "Measuring price efficiency in petroleum markets: New insights using various long-range dependence techniques," Resources Policy, Elsevier, vol. 82(C).
  93. 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.
  94. Ji, Qiangbiao & Zhang, Xin & Zhu, Yingming, 2020. "Multifractal analysis of the impact of US–China trade friction on US and China soy futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
  95. Kwangwon Ahn & Hanwool Jang & Jinu Kim & Inug Ryu, 2024. "COVID-19 and REITs Crash: Predictability and Market Conditions," Computational Economics, Springer;Society for Computational Economics, vol. 63(3), pages 1159-1172, March.
  96. Sun, Qi & Xu, Weijun & Xiao, Weilin, 2013. "An empirical estimation for mean-reverting coal prices with long memory," Economic Modelling, Elsevier, vol. 33(C), pages 174-181.
  97. Liu, Li & Wan, Jieqiu, 2012. "A study of Shanghai fuel oil futures price volatility based on high frequency data: Long-range dependence, modeling and forecasting," Economic Modelling, Elsevier, vol. 29(6), pages 2245-2253.
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