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Asymmetric multiscale behavior in PM2.5 time series: Based on asymmetric MS-DFA

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  • Zhang, Chen
  • Ni, Zhiwei
  • Ni, Liping

Abstract

Particulate matter with an aerodynamic diameter of 2.5 mm or less (PM2.5) is one of the most serious air pollution, considered most harmful for people by World Health Organisation. In this paper, we utilized the asymmetric multiscale detrended fluctuation analysis (A-MSDFA) method to explore the existence of asymmetric correlation properties for PM2.5 daily average concentration in two USA cities (Fresno and Los Angeles) and two Chinese cities (Hong Kong and Shanghai), and to assess the properties of these asymmetric correlations. The results show the existences of asymmetric correlations, and the degree of asymmetric for two USA cities is stronger than that of two Chinese cities. Further, most of the local exponent β(n) are smaller than 0.5, which indicates the existence of anti-persistent long-range correlation for PM2.5 time series in four cities. In addition, we reanalyze the asymmetric correlation by the A-MSDFA method with secant rolling windows of different sizes, which can investigate dynamic changes in the multiscale correlation for PM2.5 time series with changing window size. Whatever window sizes, the correlations are asymmetric and display smaller asymmetries at small scales and larger asymmetries at large scales. Moreover, the asymmetries become increasingly weaker with the increase of window sizes.

Suggested Citation

  • Zhang, Chen & Ni, Zhiwei & Ni, Liping, 2016. "Asymmetric multiscale behavior in PM2.5 time series: Based on asymmetric MS-DFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 355-365.
    • Handle: RePEc:eee:phsmap:v:461:y:2016:i:c:p:355-365
    DOI: 10.1016/j.physa.2016.05.018
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    References listed on IDEAS

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    1. Yin, Yi & Shang, Pengjian, 2013. "Modified DFA and DCCA approach for quantifying the multiscale correlation structure of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6442-6457.
    2. Alvarez-Ramirez, Jose & Rodriguez, Eduardo & Carlos Echeverria, Juan, 2009. "A DFA approach for assessing asymmetric correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(12), pages 2263-2270.
    3. Liang Ding & Hiroyoki Miyake & Hao Zou, 2011. "Asymmetric correlations in equity returns: a fundamental-based explanation," Applied Financial Economics, Taylor & Francis Journals, vol. 21(6), pages 389-399.
    4. Zhang, W.F. & Zhao, Q., 2015. "Asymmetric long-term persistence analysis in sea surface temperature anomaly," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 314-318.
    5. Zhang, Chen & Ni, Zhiwei & Ni, Liping, 2015. "Multifractal detrended cross-correlation analysis between PM2.5 and meteorological factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 114-123.
    6. Cao, Guangxi & Cao, Jie & Xu, Longbing, 2013. "Asymmetric multifractal scaling behavior in the Chinese stock market: Based on asymmetric MF-DFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 797-807.
    7. Fan, Qingju, 2016. "Asymmetric multiscale detrended fluctuation analysis of California electricity spot price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 252-260.
    8. Rivera-Castro, Miguel A. & Miranda, José G.V. & Cajueiro, Daniel O. & Andrade, Roberto F.S., 2012. "Detecting switching points using asymmetric detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 170-179.
    9. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    10. Ang, Andrew & Chen, Joseph, 2002. "Asymmetric correlations of equity portfolios," Journal of Financial Economics, Elsevier, vol. 63(3), pages 443-494, March.
    11. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
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    1. Meraz, M. & Alvarez-Ramirez, J. & Echeverria, J.C., 2017. "Asymmetric correlations in the ozone concentration dynamics of the Mexico City Metropolitan Area," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 377-386.

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