Fluctuation scaling and covariance matrix of constituents' flows on a bipartite graph

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Abstract

We investigate an association between a power-law relationship of constituents' flows (mean versus standard deviation) and their covariance matrix on a directed bipartite network. We propose a Poisson mixture model and a method to infer states of the constituents' flows on such a bipartite network from empirical observation without a priori knowledge on the network structure. By using a proposed parameter estimation method with high frequency financial data we found that the scaling exponent and simultaneous cross-correlation matrix have a positive correspondence relationship. Consequently we conclude that the scaling exponent tends to be 1/2 in the case of desynchronous (specific dynamics is dominant), and to be 1 in the case of synchronous (common dynamics is dominant).

Journal

  • The European Physical Journal B

    The European Physical Journal B 76(4), 529-535, 2010-08

    SPRINGER

Codes

  • NII Article ID (NAID)
    120002576694
  • NII NACSIS-CAT ID (NCID)
    AA12316710
  • Text Lang
    ENG
  • Article Type
    journal article
  • ISSN
    1434-6028
  • Data Source
    IR 
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