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Efficiency and multifractality analysis of CSI 300 based on multifractal detrending moving average algorithm

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  • Zhou, Weijie
  • Dang, Yaoguo
  • Gu, Rongbao

Abstract

We apply the multifractal detrending moving average (MFDMA) to investigate and compare the efficiency and multifractality of 5-min high-frequency China Securities Index 300 (CSI 300). The results show that the CSI 300 market becomes closer to weak-form efficiency after the introduction of CSI 300 future. We find that the CSI 300 is featured by multifractality and there are less complexity and risk after the CSI 300 index future was introduced. With the shuffling, surrogating and removing extreme values procedures, we unveil that extreme events and fat-distribution are the main origin of multifractality. Besides, we discuss the knotting phenomena in multifractality, and find that the scaling range and the irregular fluctuations for large scales in the Fq(s) vs s plot can cause a knot.

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  • Zhou, Weijie & Dang, Yaoguo & Gu, Rongbao, 2013. "Efficiency and multifractality analysis of CSI 300 based on multifractal detrending moving average algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1429-1438.
  • Handle: RePEc:eee:phsmap:v:392:y:2013:i:6:p:1429-1438
    DOI: 10.1016/j.physa.2012.11.044
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    2. Gu, Rongbao & Xiong, Wei & Li, Xinjie, 2015. "Does the singular value decomposition entropy have predictive power for stock market? — Evidence from the Shenzhen stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 439(C), pages 103-113.
    3. Zhang, Chen & Ni, Zhiwei & Ni, Liping & Li, Jingming & Zhou, Longfei, 2016. "Asymmetric multifractal detrending moving average analysis in time series of PM2.5 concentration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 322-330.
    4. He, Xiaoli & Wang, Hongwu & Du, Ziping, 2014. "The complexity and fractal structures of CSI300 before and after the introduction of CSI300IF," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 76-85.
    5. Chen, Yuwen & Zheng, Tingting, 2017. "Asymmetric joint multifractal analysis in Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 10-19.
    6. Yang, Liansheng & Zhu, Yingming & Wang, Yudong & Wang, Yiqi, 2016. "Multifractal detrended cross-correlations between crude oil market and Chinese ten sector stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 255-265.
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    8. Zhou, Weijie & Wang, Zhengxin & Guo, Haiming, 2016. "Modelling volatility recurrence intervals in the Chinese commodity futures market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 514-525.
    9. Yang, Liansheng & Zhu, Yingming & Wang, Yudong, 2016. "Multifractal characterization of energy stocks in China: A multifractal detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 357-365.

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