IDEAS home Printed from https://ideas.repec.org/p/imf/imfwpa/2016-184.html
   My bibliography  Save this paper

Spatial Dependence and Data-Driven Networks of International Banks

Author

Listed:
  • Ben Craig
  • Martín Saldías

Abstract

This paper computes data-driven correlation networks based on the stock returns of international banks and conducts a comprehensive analysis of their topological properties. We first apply spatial-dependence methods to filter the effects of strong common factors and a thresholding procedure to select the significant bilateral correlations. The analysis of topological characteristics of the resulting correlation networks shows many common features that have been documented in the recent literature but were obtained with private information on banks' exposures, including rich and hierarchical structures, based on but not limited to geographical proximity, small world features, regional homophily, and a core-periphery structure.

Suggested Citation

  • Ben Craig & Martín Saldías, 2016. "Spatial Dependence and Data-Driven Networks of International Banks," IMF Working Papers 2016/184, International Monetary Fund.
    • Handle: RePEc:imf:imfwpa:2016/184
    as

    Download full text from publisher

    File URL: http://www.imf.org/external/pubs/cat/longres.aspx?sk=44271
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Bailey, Natalia & Pesaran, M. Hashem & Smith, L. Vanessa, 2019. "A multiple testing approach to the regularisation of large sample correlation matrices," Journal of Econometrics, Elsevier, vol. 208(2), pages 507-534.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. Canova, Fabio & Ciccarelli, Matteo, 2013. "Panel Vector Autoregressive Models: A Survey," CEPR Discussion Papers 9380, C.E.P.R. Discussion Papers.
    4. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306.
    5. Lelyveld, Iman van & Liedorp, Franka, 2004. "Interbank Contagion in the Dutch Banking Sector," MPRA Paper 651, University Library of Munich, Germany, revised 11 Jul 2005.
    6. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    7. 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.
    8. Alexander Chudik & M. Hashem Pesaran & Elisa Tosetti, 2011. "Weak and strong cross‐section dependence and estimation of large panels," Econometrics Journal, Royal Economic Society, vol. 14(1), pages 45-90, February.
    9. Minoiu, Camelia & Reyes, Javier A., 2013. "A network analysis of global banking: 1978–2010," Journal of Financial Stability, Elsevier, vol. 9(2), pages 168-184.
    10. Craig, Ben & von Peter, Goetz, 2014. "Interbank tiering and money center banks," Journal of Financial Intermediation, Elsevier, vol. 23(3), pages 322-347.
    11. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2014. "Forecasting systemic impact in financial networks," International Journal of Forecasting, Elsevier, vol. 30(3), pages 781-794.
    12. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Torri, Gabriele & Giacometti, Rosella & Paterlini, Sandra, 2018. "Robust and sparse banking network estimation," European Journal of Operational Research, Elsevier, vol. 270(1), pages 51-65.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Matteo Barigozzi & Christian Brownlees, 2019. "NETS: Network estimation for time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 347-364, April.
    2. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.
    3. Jonathan E. Ogbuabor & God’stime O. Eigbiremolen & Gladys C. Aneke & Manasseh O. Charles, 2018. "Measuring the dynamics of APEC output connectedness," Asian-Pacific Economic Literature, Asia Pacific School of Economics and Government, The Australian National University, vol. 32(1), pages 29-44, May.
    4. van de Leur, Michiel C.W. & Lucas, André & Seeger, Norman J., 2017. "Network, market, and book-based systemic risk rankings," Journal of Banking & Finance, Elsevier, vol. 78(C), pages 84-90.
    5. Danau, Daniel, 2020. "Prudence and preference for flexibility gain," European Journal of Operational Research, Elsevier, vol. 287(2), pages 776-785.
    6. Cai, Jian & Eidam, Frederik & Saunders, Anthony & Steffen, Sascha, 2018. "Syndication, interconnectedness, and systemic risk," Journal of Financial Stability, Elsevier, vol. 34(C), pages 105-120.
    7. Tuomas Antero Peltonen & Michela Rancan & Peter Sarlin, 2019. "Interconnectedness of the banking sector as a vulnerability to crises," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(2), pages 963-990, April.
    8. Gang-Jin Wang & Chi Xie & Kaijian He & H. Eugene Stanley, 2017. "Extreme risk spillover network: application to financial institutions," Quantitative Finance, Taylor & Francis Journals, vol. 17(9), pages 1417-1433, September.
    9. Tan T. M. Le & Franck Martin & Duc K. Nguyen, 2018. "Dynamic connectedness of global currencies: a conditional Granger-causality approach," Economics Working Paper Archive (University of Rennes 1 & University of Caen) 2018-04, Center for Research in Economics and Management (CREM), University of Rennes 1, University of Caen and CNRS.
    10. Gustavo Peralta, 2015. "Network-based Measures as Leading Indicators of Market Instability: The case of the Spanish Stock," CNMV Working Papers CNMV Working Papers no 59, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
    11. Výrost, Tomas & Lyócsa, Štefan & Baumöhl, Eduard, 2019. "Network-based asset allocation strategies," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 516-536.
    12. Buse, Rebekka & Schienle, Melanie, 2019. "Measuring connectedness of euro area sovereign risk," International Journal of Forecasting, Elsevier, vol. 35(1), pages 25-44.
    13. Ogbuabor, Jonathan E. & Anthony-Orji, Onyinye I. & Manasseh, Charles O. & Orji, Anthony, 2020. "Measuring the dynamics of COMESA output connectedness with the global economy," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    14. Everett Grant & Julieta Yung, 2017. "The Double-Edged Sword of Global Integration: Robustness, Fragility & Contagion in the International Firm Network," Globalization Institute Working Papers 313, Federal Reserve Bank of Dallas.
    15. Arreola Hernandez, Jose & Kang, Sang Hoon & Shahzad, Syed Jawad Hussain & Yoon, Seong-Min, 2020. "Spillovers and diversification potential of bank equity returns from developed and emerging America," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    16. Jonathan E. Ogbuabor & Anthony Orji & Gladys C. Aneke & Oyun Erdene-Urnukh, 2016. "Measuring the Real and Financial Connectedness of Selected African Economies with the Global Economy," South African Journal of Economics, Economic Society of South Africa, vol. 84(3), pages 364-399, September.
    17. Billio, Monica & Caporin, Massimiliano & Panzica, Roberto Calogero & Pelizzon, Loriana, 2017. "The impact of network connectivity on factor exposures, asset pricing and portfolio diversification," SAFE Working Paper Series 166, Leibniz Institute for Financial Research SAFE.
    18. Mishra, Abinash & Srivastava, Pranjal & Chakrabarti, Anindya S., 2020. "'Too central to fail' firms in bi-layered financial networks: Evidence of linkages from the US corporate bond and stock markets," IIMA Working Papers WP 2020-06-02, Indian Institute of Management Ahmedabad, Research and Publication Department.
    19. Francis X. Diebold & Kamil Yilmaz, 2016. "Trans-Atlantic Equity Volatility Connectedness: U.S. and European Financial Institutions, 2004–2014," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 14(1), pages 81-127.
    20. Peralta, Gustavo & Zareei, Abalfazl, 2016. "A network approach to portfolio selection," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 157-180.

    More about this item

    Keywords

    Banking; Spatial models; International banking; Vector autoregression; Stock markets; WP; correlation matrix; hierarchical structure; graph theory;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:imf:imfwpa:2016/184. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Akshay Modi). General contact details of provider: http://edirc.repec.org/data/imfffus.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.