IDEAS home Printed from https://ideas.repec.org/p/ctc/serie1/def036.html

A unfi ed view of systemic risk: detecting SIFIs and forecasting the fi nancial cycle via EWSs

Author

Listed:
  • Alessandro Spelta

    (Università Cattolica del Sacro Cuore
    Dipartimento di Economia e Finanza, Università Cattolica del Sacro Cuore)

Abstract

Following the defi nition of systemic risk by the Financial Stability Board, the International Monetary Fund and the Bank for International Settlements, this paper proposes a method able to simultaneously address the two dimensions in which this risk materializes: namely the cross-sectional and the time dimension. The method is based on the W-TOPHITS algorithm, that exploits the connectivity information of an evolving network, and decomposes its tensor representation as the outer product of three vectors: borrowing, lending and time scores. These vectors can be interpreted as indices of the systemic importance of borrowing and lending associated with each fi nancial institution and of the systemic importance associated with each period, coherently with the realization of the whole network in that period. The time score, being able to simultaneously consider the temporal distribution of the whole traded volume over time as well as the spatial distribution of the transactions between players in each period, turns out to be a useful Early Warning Signal of the fi nancial crisis. The W-TOPHITS is tested on the e-MID interbank market dataset and on the BIS consolidated banking statistics with the aim of discovering Systemically Important Financial Institutions and to show how the time score is able to signal a change in the bipartite network of borrowers and lenders that heralds the fall of the traded volume that occurred during the 2007/2009 nancial crisis.

Suggested Citation

  • Alessandro Spelta, 2016. "A unfi ed view of systemic risk: detecting SIFIs and forecasting the fi nancial cycle via EWSs," DISCE - Working Papers del Dipartimento di Economia e Finanza def036, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    • Handle: RePEc:ctc:serie1:def036
    as

    Download full text from publisher

    File URL: http://dipartimenti.unicatt.it/economia-finanza-def036.pdf
    File Function: First version, 2016
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andrew K. Rose & Mark M. Spiegel, 2010. "Cross‐Country Causes And Consequences Of The 2008 Crisis: International Linkages And American Exposure," Pacific Economic Review, Wiley Blackwell, vol. 15(3), pages 340-363, August.
    2. Rose, Andrew K. & Spiegel, Mark M., 2011. "Cross-country causes and consequences of the crisis: An update," European Economic Review, Elsevier, vol. 55(3), pages 309-324, April.
    3. Daniel D. Lee & H. Sebastian Seung, 1999. "Learning the parts of objects by non-negative matrix factorization," Nature, Nature, vol. 401(6755), pages 788-791, October.
    4. Ben S. Bernanke & Mark Gertler, 1995. "Inside the Black Box: The Credit Channel of Monetary Policy Transmission," Journal of Economic Perspectives, American Economic Association, vol. 9(4), pages 27-48, Fall.
    5. Stefano Battiston & Guido Caldarelli, 2013. "Systemic Risk in Financial Networks," Journal of Financial Management, Markets and Institutions, Società editrice il Mulino, issue 2, pages 129-154, December.
    6. Battiston, Stefano & Delli Gatti, Domenico & Gallegati, Mauro & Greenwald, Bruce & Stiglitz, Joseph E., 2012. "Liaisons dangereuses: Increasing connectivity, risk sharing, and systemic risk," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1121-1141.
    7. Nobuhiro Kiyotaki & John Moore, 1997. "Credit Chains," Working Papers 1997-2, Princeton University. Economics Department..
    8. 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.
    9. Nobuhiro Kiyotaki & John Moore, 1997. "Credit Chains," Edinburgh School of Economics Discussion Paper Series 118, Edinburgh School of Economics, University of Edinburgh.
    10. Tiziano Squartini & Iman van Lelyveld & Diego Garlaschelli, 2013. "Early-warning signals of topological collapse in interbank networks," Papers 1302.2063, arXiv.org, revised Nov 2013.
    11. Hoo-Kyu Rhu, 2011. "Macroprudential policy framework," BIS Papers chapters, in: Bank for International Settlements (ed.), Macroprudential regulation and policy, volume 60, pages 120-123, Bank for International Settlements.
    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. Andrea Albanese & Lorenzo Cappellari & Marco Ovidi, 2025. "Earning ability over the life cycle," DISCE - Working Papers del Dipartimento di Economia e Finanza def148, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    2. Irene Torrini & Claudio Lucifora & Antonio Russo, 2022. "The Long-Term Effects of Hospitalization on Health Care Expenditures: An Empirical Analysis for the Young-Old Population," DISCE - Working Papers del Dipartimento di Economia e Finanza def117, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    3. Tiziana Assenza & Domenico Delli Gatti & Jakob Grazzini & Giorgio Ricchiuti, 2016. "Heterogeneous Firms and International Trade: The Role of Productivity and Financial Fragility," CESifo Working Paper Series 5959, CESifo.

    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. Spelta, A. & Pecora, N. & Rovira Kaltwasser, P., 2019. "Identifying Systemically Important Banks: A temporal approach for macroprudential policies," Journal of Policy Modeling, Elsevier, vol. 41(1), pages 197-218.
    2. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    3. Song, Jae Wook & Ko, Bonggyun & Cho, Poongjin & Chang, Woojin, 2016. "Time-varying causal network of the Korean financial system based on firm-specific risk premiums," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 287-302.
    4. Nicolò Pecora & Pablo Rovira Kaltwasser & Alessandro Spelta, 2016. "Discovering SIFIs in Interbank Communities," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-17, December.
    5. Ashoka Mody & Maria Soledad Martinez Peria, 2004. "How foreign participation and market concentration impact bank spreads: evidence from Latin America," Proceedings, Federal Reserve Bank of Cleveland, pages 511-542.
    6. Germán G. Creamer & Tal Ben-Zvi, 2021. "Volatility and Risk in the Energy Market: A Trade Network Approach," Sustainability, MDPI, vol. 13(18), pages 1-17, September.
    7. Feldkircher, Martin, 2014. "The determinants of vulnerability to the global financial crisis 2008 to 2009: Credit growth and other sources of risk," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 19-49.
    8. Bruce N. Lehmann & David M. Modest, 1985. "The Empirical Foundations of the Arbitrage Pricing Theory I: The Empirical Tests," NBER Working Papers 1725, National Bureau of Economic Research, Inc.
    9. Vašíček, Bořek & Žigraiová, Diana & Hoeberichts, Marco & Vermeulen, Robert & Šmídková, Kateřina & de Haan, Jakob, 2017. "Leading indicators of financial stress: New evidence," Journal of Financial Stability, Elsevier, vol. 28(C), pages 240-257.
    10. Wang, Xichen & Yan, Ji (Karena) & Yan, Cheng & Gozgor, Giray, 2021. "Emerging stock market exuberance and international short-term flows," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    11. Kyunghun Kim & Ju Hyun Pyun & Jiyoun An, 2017. "Does Credit Market Integration Amplify the Transmission of Real Business Cycle During Financial Crisis?," 2017 Meeting Papers 1236, Society for Economic Dynamics.
    12. James J. McAndrews & William Roberds, 1999. "Payment intermediation and the origins of banking," Staff Reports 85, Federal Reserve Bank of New York.
    13. Livia Chitu, 2013. "Was Unofficial Dollarisation/Euroisation an Amplifier of the ‘Great Recession’ of 2007–2009 in Emerging Economies?," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 55(2), pages 233-265, June.
    14. Song, Jianhua & Zhang, Zhepei & So, Mike K.P., 2021. "On the predictive power of network statistics for financial risk indicators," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    15. Maria Dolores Gadea Rivas & Gabriel Perez-Quiros, 2012. "The failure to predict the Great Recession. The failure of academic economics? A view focusing on the role of credit," Working Papers 1240, Banco de España.
    16. Geert Bekaert & Michael Ehrmann & Marcel Fratzscher & Arnaud Mehl, 2014. "The Global Crisis and Equity Market Contagion," Journal of Finance, American Finance Association, vol. 69(6), pages 2597-2649, December.
    17. Levrero, Enrico Sergio & Deleidi, Matteo, 2017. "The money creation process: A theoretical and empirical analysis for the US," MPRA Paper 81970, University Library of Munich, Germany.
    18. Anthony Orlando, 2018. "Asset Markets, Credit Markets, and Inequality: Distributional Changes in Housing, 1970-2016," ERES eres2018_182, European Real Estate Society (ERES).
    19. Majumdar, Sumit K., 2016. "Debt and communications technology diffusion: Retrospective evidence," Research Policy, Elsevier, vol. 45(2), pages 458-474.
    20. Andreas Brunhart, 2025. "Country size and exposure to international economic shocks: new evidence from the Financial Crisis," International Economics and Economic Policy, Springer, vol. 22(3), pages 1-49, July.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ctc:serie1:def036. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Simone Moriconi The email address of this maintainer does not seem to be valid anymore. Please ask Simone Moriconi to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/dscatit.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.