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Market structure explained by pairwise interactions

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  • Thomas Bury
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    Abstract

    Financial markets are a typical example of complex systems where interactions between constituents lead to many remarkable features. Here, we show that a pairwise maximum entropy model (or auto-logistic model) is able to describe switches between ordered (strongly correlated) and disordered market states. In this framework, the influence matrix may be thought as a dissimilarity measure and we explain how it can be used to study market structure. We make the link with the graph-theoretic description of stock markets reproducing the non-random and scale-free topology, shrinking length during crashes and meaningful clustering features as expected. The pairwise model provides an alternative method to study financial networks which may be useful for characterization of abnormal market states (crises and bubbles), in capital allocation or for the design of regulation rules.

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    File URL: http://arxiv.org/pdf/1210.8380
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    Paper provided by arXiv.org in its series Papers with number 1210.8380.

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    Date of creation: Oct 2012
    Date of revision: Jan 2014
    Handle: RePEc:arx:papers:1210.8380

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    Web page: http://arxiv.org/

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