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Price–volume cross-correlation analysis of CSI300 index futures

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  • Wang, Dong-Hua
  • Suo, Yuan-Yuan
  • Yu, Xiao-Wen
  • Lei, Man

Abstract

We investigate the cross-correlation between price returns and trading volumes for the China Securities Index 300 (CSI300) index futures, which are the only stock index futures traded on the China Financial Futures Exchange (CFFEX). The basic statistics suggest that distributions of these two time series are not normal but exhibit fat tails. Based on the detrended cross-correlation analysis (DCCA), we obtain that returns and trading volumes are long-range cross-correlated. The existence of multifractality in the cross-correlation between returns and trading volumes has been proven with the multifractal detrended cross-correlation analysis (MFDCCA) algorithm. The multifractal analysis also confirms that returns and trading volumes have different degrees of multifractality. We further perform a cross-correlation statistic to verify whether the cross-correlation significantly exists between returns and trading volumes for CSI300 index futures. In addition, results of the test for lead-lag effect demonstrate that contemporaneous cross-correlation of return and trading volume series is stronger than cross-correlations of leaded or lagged series.

Suggested Citation

  • Wang, Dong-Hua & Suo, Yuan-Yuan & Yu, Xiao-Wen & Lei, Man, 2013. "Price–volume cross-correlation analysis of CSI300 index futures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(5), pages 1172-1179.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:5:p:1172-1179
    DOI: 10.1016/j.physa.2012.11.031
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    20. Liu, Li & Ma, Guofeng, 2014. "Cross-correlation between crude oil and refined product prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 284-293.
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    24. Xiaojie Xu & Yun Zhang, 2023. "Neural network predictions of the high-frequency CSI300 first distant futures trading volume," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(2), pages 191-207, June.

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