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Emergence of time-horizon invariant correlation structure in financial returns by subtraction of the market mode


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  • Christian Borghesi
  • Matteo Marsili
  • Salvatore Miccich\`e
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    We investigate the emergence of a structure in the correlation matrix of assets' returns as the time-horizon over which returns are computed increases from the minutes to the daily scale. We analyze data from different stock markets (New York, Paris, London, Milano) and with different methods. Result crucially depends on whether the data is restricted to the ``internal'' dynamics of the market, where the ``center of mass'' motion (the market mode) is removed or not. If the market mode is not removed, we find that the structure emerges, as the time-horizon increases, from splitting a single large cluster. In NYSE we find that when the market mode is removed, the structure of correlation at the daily scale is already well defined at the 5 minutes time-horizon, and this structure accounts for 80 % of the classification of stocks in economic sectors. Similar results, though less sharp, are found for the other markets. We also find that the structure of correlations in the overnight returns is markedly different from that of intraday activity.

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    Bibliographic Info

    Paper provided by in its series Papers with number physics/0702106.

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    Date of creation: Feb 2007
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    Publication status: Published in Phys. Rev. E, 76, 026104 (2005)
    Handle: RePEc:arx:papers:physics/0702106

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    Cited by:
    1. Leonidas Sandoval Junior, 2011. "A Map of the Brazilian Stock Market," Papers 1107.4146,, revised Mar 2013.
    2. Cheong, Siew Ann & Fornia, Robert Paulo & Lee, Gladys Hui Ting & Kok, Jun Liang & Yim, Woei Shyr & Xu, Danny Yuan & Zhang, Yiting, 2011. "The Japanese economy in crises: A time series segmentation study," Economics Discussion Papers 2011-24, Kiel Institute for the World Economy.
    3. Sandoval, Leonidas, 2014. "To lag or not to lag? How to compare indices of stock markets that operate on different times," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 403(C), pages 227-243.
    4. Marsili, Matteo & Raffaelli, Giacomo & Ponsot, Benedicte, 2009. "Dynamic instability in generic model of multi-assets markets," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 33(5), pages 1170-1181, May.
    5. Sandoval, Leonidas, 2012. "Pruning a minimum spanning tree," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 391(8), pages 2678-2711.
    6. Sandoval, Leonidas & Franca, Italo De Paula, 2012. "Correlation of financial markets in times of crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 391(1), pages 187-208.
    7. Ahmet Sensoy & Benjamin M. Tabak, 2014. "Dynamic spanning trees in stock market networks: The case of Asia-Pacific," Working Papers Series, Central Bank of Brazil, Research Department 351, Central Bank of Brazil, Research Department.


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