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Bank networks from text: interrelations, centrality and determinants

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  • Samuel R�nnqvist
  • Peter Sarlin

Abstract

In the wake of the still ongoing global financial crisis, bank interdependencies have come into focus in trying to assess linkages among banks and systemic risk. To date, such analysis has largely been based on numerical data. By contrast, this study attempts to gain further insight into bank interconnections by tapping into financial discourse. We present a text-to-network process, which has its basis in co-occurrences of bank names and can be analysed quantitatively and visualized. To quantify bank importance, we propose an information centrality measure to rank and assess trends of bank centrality in discussion. For qualitative assessment of bank networks, we put forward a visual, interactive interface for better illustrating network structures. We illustrate the text-based approach on European Large and Complex Banking Groups during the ongoing financial crisis by quantifying bank interrelations and centrality from discussion in 3M news articles, spanning 2007Q1 to 2014Q3.

Suggested Citation

  • Samuel R�nnqvist & Peter Sarlin, 2015. "Bank networks from text: interrelations, centrality and determinants," Quantitative Finance, Taylor & Francis Journals, vol. 15(10), pages 1619-1635, October.
  • Handle: RePEc:taf:quantf:v:15:y:2015:i:10:p:1619-1635
    DOI: 10.1080/14697688.2015.1071076
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    References listed on IDEAS

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    1. Mr. Luc Laeven & Mr. Fabian Valencia, 2010. "Resolution of Banking Crises: The Good, the Bad, and the Ugly," IMF Working Papers 2010/146, International Monetary Fund.
    2. Claudio Borio & Mathias Drehmann, 2011. "Toward an Operational Framework for Financial Stability: “Fuzzy” Measurement and Its Consequences," Central Banking, Analysis, and Economic Policies Book Series, in: Rodrigo Alfaro (ed.),Financial Stability, Monetary Policy, and Central Banking, edition 1, volume 15, chapter 4, pages 063-123, Central Bank of Chile.
    3. Eugenio Cerutti & Stijn Claessens & Patrick McGuire, 2012. "Systemic Risks in Global Banking: What Available Data Can Tell Us and What More Data Are Needed?," NBER Chapters, in: Risk Topography: Systemic Risk and Macro Modeling, pages 235-260, National Bureau of Economic Research, Inc.
    4. Peter Sarlin, 2014. "Macroprudential oversight, risk communication and visualization," Papers 1404.4550, arXiv.org, revised Jun 2014.
    5. Eugenio Cerutti & Stijn Claessens & Patrick McGuire, 2012. "Systemic risk in global banking: what can available data tell us and what more data are needed?," BIS Working Papers 376, Bank for International Settlements.
    6. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2015. "Financial Network Systemic Risk Contributions," Review of Finance, European Finance Association, vol. 19(2), pages 685-738.
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    Citations

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    Cited by:

    1. Fang, Libing & Sun, Boyang & Li, Huijing & Yu, Honghai, 2018. "Systemic risk network of Chinese financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 190-206.
    2. Thomas Forss & Peter Sarlin, 2017. "News-sentiment networks as a risk indicator," Papers 1706.05812, arXiv.org, revised May 2018.
    3. Zhibin Niu & Junqi Wu & Dawei Cheng & Jiawan Zhang, 2021. "Regshock: Interactive Visual Analytics of Systemic Risk in Financial Networks," Papers 2104.11863, arXiv.org.
    4. Samuel Ronnqvist & Peter Sarlin, 2015. "Detect & Describe: Deep learning of bank stress in the news," Papers 1507.07870, arXiv.org.
    5. Zhibin Niu & Runlin Li & Junqi Wu & Dawei Cheng & Jiawan Zhang, 2020. "iConViz: Interactive Visual Exploration of the Default Contagion Risk of Networked-Guarantee Loans," Papers 2006.09542, arXiv.org, revised Aug 2020.
    6. Li, Jingyu & Li, Jianping & Zhu, Xiaoqian, 2020. "Risk dependence between energy corporations: A text-based measurement approach," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 33-46.
    7. Liu, Wei & Ma, Qianting & Liu, Xiaoxing, 2022. "Research on the dynamic evolution and its influencing factors of stock correlation network in the Chinese new energy market," Finance Research Letters, Elsevier, vol. 45(C).
    8. Christopher Gerling, 2023. "Company2Vec -- German Company Embeddings based on Corporate Websites," Papers 2307.09332, arXiv.org.
    9. Samuel Ronnqvist & Peter Sarlin, 2016. "Bank distress in the news: Describing events through deep learning," Papers 1603.05670, arXiv.org, revised Dec 2016.
    10. Fang, Ming & Taylor, Stephen & Uddin, Ajim, 2022. "The network structure of overnight index swap rates," Finance Research Letters, Elsevier, vol. 46(PB).

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