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Graphical network models for international financial flows

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  • Paolo Giudici

    () (Department of Economics and Management, University of Pavia)

  • Alessandro Spelta

    () (Department of Economics and Management, University of Pavia)

Abstract

The late-2000s financial crisis has stressed the need of understanding the world financial system as a network of countries, where cross-border financial linkages play a fundamental role in the spread of systemic risks. Financial network models, that take into account the complex interrelationships between countries, seem to be an appropriate tool in this context. In this paper we propose to enrich the topological perspective of network models with a more structured statistical framework, that of graphical Gaussian models, which can be employed to accurately estimate the adjacency matrix, the main input for the estimation of the interconnections between different countries. We consider different types of graphical models: besides classical ones, we introduce Bayesian graphical models, that can take model uncertainty into account, and dynamic Bayesian graphical models, that provide a convenient framework to model temporal cross-border data, decomposing the model into autoregressive and contemporaneous networks. The paper shows how the application of the proposed models to the Bank of International Settlements locational banking statistics allows the identification of four distinct groups of countries, that can be considered central in systemic risk contagion.

Suggested Citation

  • Paolo Giudici & Alessandro Spelta, 2013. "Graphical network models for international financial flows," DEM Working Papers Series 052, University of Pavia, Department of Economics and Management.
  • Handle: RePEc:pav:demwpp:demwp0052
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    References listed on IDEAS

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    1. Soramäki, Kimmo & Bech, Morten L. & Arnold, Jeffrey & Glass, Robert J. & Beyeler, Walter E., 2007. "The topology of interbank payment flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 317-333.
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    Citations

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    Cited by:

    1. Rui Faustino, 2016. "Portuguese National Accounts: a network approach," Working Papers Department of Economics 2016/18, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    2. Pejman Abedifar & Paolo Giudici & Shatha Hashem, 2017. "Heterogeneous Market Structure and Systemic Risk: Evidence from Dual Banking Systems," DEM Working Papers Series 134, University of Pavia, Department of Economics and Management.
    3. Khai X. Chiong & Hyungsik Roger Moon, 2017. "Estimation of Graphical Models using the $L_{1,2}$ Norm," Papers 1709.10038, arXiv.org, revised Oct 2017.
    4. Paolo Giudici & Laura Parisi, 2016. "CoRisk: measuring systemic risk through default probability contagion," DEM Working Papers Series 116, University of Pavia, Department of Economics and Management.
    5. repec:eee:finsta:v:33:y:2017:i:c:p:96-119 is not listed on IDEAS
    6. Paolo Giudici & Shatha Hashem, 2015. "Systemic risk of Islamic Banks," DEM Working Papers Series 103, University of Pavia, Department of Economics and Management.
    7. Tanya Ara'ujo & Rui Faustino, 2016. "The Topology of Inter-industry Relations from the Portuguese National Accounts," Papers 1612.06291, arXiv.org.
    8. Paolo Giudici & Laura Parisi, 2015. "Modeling Systemic Risk with Correlated Stochastic Processes," DEM Working Papers Series 110, University of Pavia, Department of Economics and Management.
    9. Frank Emmert-Streib & Aliyu Musa & Kestutis Baltakys & Juho Kanniainen & Shailesh Tripathi & Olli Yli-Harja & Herbert Jodlbauer & Matthias Dehmer, 2017. "Computational Analysis of the structural properties of Economic and Financial Networks," Papers 1710.04455, arXiv.org.
    10. repec:spr:qualqt:v:51:y:2017:i:4:d:10.1007_s11135-016-0354-x is not listed on IDEAS
    11. Paolo Giudici & Peter Sarlin & Alessandro Spelta, 2016. "The multivariate nature of systemic risk: direct and common exposures," DEM Working Papers Series 118, University of Pavia, Department of Economics and Management.

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    Keywords

    Financial network models; Graphical models; Bayesian model selection;

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