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Cross-correlations between agricultural commodity futures markets in the US and China

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  • Li, Zhihui
  • Lu, Xinsheng
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    Abstract

    This paper examines the cross-correlation properties of agricultural futures markets between the US and China using a cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). The results show that the cross-correlations between the two geographically distant markets for four pairs of important agricultural commodities futures are significantly multifractal. By introducing the concept of a “crossover”, we find that the multifractality of cross-correlations between the two markets is not long lasting. The cross-correlations in the short term are more strongly multifractal, but they are weakly so in the long term. Moreover, cross-correlations of small fluctuations are persistent and those of large fluctuations are anti-persistent in the short term while cross-correlations of all kinds of fluctuations for soy bean and soy meal futures are persistent and for corn and wheat futures are anti-persistent in the long term. We also find that cross-correlation exponents are less than the averaged generalized Hurst exponent when q<0 and more than the averaged generalized Hurst exponent when q>0 in the short term, while in the long term they are almost the same.

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    Bibliographic Info

    Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

    Volume (Year): 391 (2012)
    Issue (Month): 15 ()
    Pages: 3930-3941

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    Handle: RePEc:eee:phsmap:v:391:y:2012:i:15:p:3930-3941

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    Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

    Related research

    Keywords: Cross-correlation; Agricultural commodity futures; MF-DCCA; Crossover;

    References

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    Cited by:
    1. Wei, Yu & Chen, Wang & Lin, Yu, 2013. "Measuring daily Value-at-Risk of SSEC index: A new approach based on multifractal analysis and extreme value theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2163-2174.
    2. 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.
    3. Wang, Gang-Jin & Xie, Chi, 2013. "Cross-correlations between Renminbi and four major currencies in the Renminbi currency basket," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1418-1428.
    4. Lu, Xinsheng & Tian, Jie & Zhou, Ying & Li, Zhihui, 2013. "Multifractal detrended fluctuation analysis of the Chinese stock index futures market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1452-1458.
    5. Liu, Li & Wang, Yudong, 2014. "Cross-correlations between spot and futures markets of nonferrous metals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 20-30.
    6. Wang, Gang-Jin & Xie, Chi & Chen, Shou & Yang, Jiao-Jiao & Yang, Ming-Yan, 2013. "Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3715-3730.
    7. Ma, Feng & Wei, Yu & Huang, Dengshi & Zhao, Lin, 2013. "Cross-correlations between West Texas Intermediate crude oil and the stock markets of the BRIC," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5356-5368.
    8. Ma, Feng & Wei, Yu & Huang, Dengshi, 2013. "Multifractal detrended cross-correlation analysis between the Chinese stock market and surrounding stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(7), pages 1659-1670.
    9. Xinsheng Lu & Jie Tian & Ying Zhou & Zhihui Li, 2012. "Multifractal Detrended Fluctuation Analysis of the Chinese Stock Index Futures Market," Working Papers 2012-08, Auckland University of Technology, Department of Economics.

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