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Memory effect and multifractality of cross-correlations in financial markets

Author

Listed:
  • Qiu, Tian
  • Chen, Guang
  • Zhong, Li-Xin
  • Lei, Xiao-Wei

Abstract

We introduce an instantaneous and an average instantaneous cross-correlation function to detect the temporal cross-correlations between individual stocks based on the daily data of the United States and the Chinese stock markets. The memory effect of the instantaneous cross-correlations is investigated by applying the detrended fluctuation analysis (DFA), where the DFA exponents can be partly explained by the correlation function from the common sense. Long-range memory is observed for the average instantaneous cross-correlations, and persists up to a month magnitude of timescale for the United States stock market and half a month magnitude of timescale for the Chinese stock market. In addition, multifractal nature is investigated by a multifractal detrended fluctuation analysis.

Suggested Citation

  • Qiu, Tian & Chen, Guang & Zhong, Li-Xin & Lei, Xiao-Wei, 2011. "Memory effect and multifractality of cross-correlations in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(5), pages 828-836.
    • Handle: RePEc:eee:phsmap:v:390:y:2011:i:5:p:828-836
    DOI: 10.1016/j.physa.2010.11.011
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    Citations

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    Cited by:

    1. Zeng, Zhi-Jian & Xie, Chi & Yan, Xin-Guo & Hu, Jue & Mao, Zhou, 2016. "Are stock market networks non-fractal? Evidence from New York Stock Exchange," Finance Research Letters, Elsevier, vol. 17(C), pages 97-102.
    2. da Silva Filho, Antônio Carlos & Maganini, Natália Diniz & de Almeida, Eduardo Fonseca, 2018. "Multifractal analysis of Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 954-967.
    3. Yang, Honglin & Wan, Hong & Zha, Yong, 2013. "Autocorrelation type, timescale and statistical property in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(7), pages 1681-1693.

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