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Unveiling the connectivity structure of financial networks via high-frequency analysis

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  • Materassi, Donatello
  • Innocenti, Giacomo

Abstract

The paper deals with the problem of reconstructing the internal link structure of a network of agents subject to mutual dependencies. We show that standard multivariate approaches based on a correlation analysis are not well suited to detect mutual influences and dependencies, especially in the presence of delayed or propagative relations and when the sampling rate is sufficiently high to capture them. In particular, we develop and apply a metric based on the coherence function to take into account these dynamical phenomena. The effectiveness of the proposed approach is illustrated through numerical examples and through the analysis of a real complex networked system, i.e. a set of 100 high volume stocks of the New York Stock Exchange, observed during March 2008 and sampled at high frequency.

Suggested Citation

  • Materassi, Donatello & Innocenti, Giacomo, 2009. "Unveiling the connectivity structure of financial networks via high-frequency analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(18), pages 3866-3878.
  • Handle: RePEc:eee:phsmap:v:388:y:2009:i:18:p:3866-3878 DOI: 10.1016/j.physa.2009.06.003
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    References listed on IDEAS

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    1. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    2. Caines, P. E. & Keng, C. W. & Sethi, S. P., 1981. "Causality analysis and multivariate Autoregressive modelling with an application to supermarket sales analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 3(1), pages 267-298, November.
    3. Tóth, Bence & Kertész, János, 2007. "On the origin of the Epps effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 54-58.
    4. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    5. Naylor, Michael J. & Rose, Lawrence C. & Moyle, Brendan J., 2007. "Topology of foreign exchange markets using hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 199-208.
    6. Tóth, Bence & Kertész, János, 2009. "Accurate estimator of correlations between asynchronous signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1696-1705.
    7. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2007. "Agent-based Models of Financial Markets," Papers physics/0701140, arXiv.org.
    8. Bence Toth & Janos Kertesz, 2007. "On the origin of the Epps effect," Papers physics/0701110, arXiv.org, revised Feb 2007.
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    Cited by:

    1. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Sep 2017.

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