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Carbon-dioxide emissions trading and hierarchical structure in worldwide finance and commodities markets

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  • Zeyu Zheng
  • Kazuko Yamasaki
  • Joel N. Tenenbaum
  • H. Eugene Stanley
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    Abstract

    In a highly interdependent economic world, the nature of relationships between financial entities is becoming an increasingly important area of study. Recently, many studies have shown the usefulness of minimal spanning trees (MST) in extracting interactions between financial entities. Here, we propose a modified MST network whose metric distance is defined in terms of cross-correlation coefficient absolute values, enabling the connections between anticorrelated entities to manifest properly. We investigate 69 daily time series, comprising three types of financial assets: 28 stock market indicators, 21 currency futures, and 20 commodity futures. We show that though the resulting MST network evolves over time, the financial assets of similar type tend to have connections which are stable over time. In addition, we find a characteristic time lag between the volatility time series of the stock market indicators and those of the EU CO2 emission allowance (EUA) and crude oil futures (WTI). This time lag is given by the peak of the cross-correlation function of the volatility time series EUA (or WTI) with that of the stock market indicators, and is markedly different (>20 days) from 0, showing that the volatility of stock market indicators today can predict the volatility of EU emissions allowances and of crude oil in the near future.

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    File URL: http://arxiv.org/pdf/1205.1861
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    Bibliographic Info

    Paper provided by arXiv.org in its series Papers with number 1205.1861.

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    Date of creation: May 2012
    Date of revision: Aug 2013
    Publication status: Published in Phys. Rev. E 87, 012814 (2013)
    Handle: RePEc:arx:papers:1205.1861

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    Web page: http://arxiv.org/

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    Cited by:
    1. Nobi, Ashadun & Maeng, Seong Eun & Ha, Gyeong Gyun & Lee, Jae Woo, 2014. "Effects of global financial crisis on network structure in a local stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 135-143.

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