IDEAS home Printed from https://ideas.repec.org/a/spt/apfiba/v7y2017i3f7_3_6.html
   My bibliography  Save this article

Extreme Value Theory with an Application to Bank Failures through Contagion

Author

Listed:
  • Rashid Nikzad
  • David McDonald

Abstract

This study attempts to quantify the shocks to a banking network and analyze the transfer of shocks through the network. We consider two sources of shocks: external shocks due to market and macroeconomic factors which impact the entire banking system, and idiosyncratic shocks due to failure of a single bank. The external shocks we considered in this study are due to exchange rate shocks. An ARMA/GARCH model is used to extract i.i.d. residuals for this purpose. The effect of external shocks will be estimated by using two methods: (i) bootstrap simulation of the time series of shocks that occurred to the banking system in the past, and (ii) using the extreme value theory (EVT) to model the tail part of the shocks. In the next step, the probability of the failure of banks in the system is studied by using the Monte Carlo simulation. We also introduce the importance sampling technique in the EVT modeling to increase the probability of failure in the simulation. We calibrate the model such that the network resembles the Canadian banking system.JEL classification numbers: G2, C1Keywords: Monte Carlo Simulation; Extreme Value Theory; GARCH; Importance Sampling; Bank Contagion

Suggested Citation

  • Rashid Nikzad & David McDonald, 2017. "Extreme Value Theory with an Application to Bank Failures through Contagion," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(3), pages 1-6.
  • Handle: RePEc:spt:apfiba:v:7:y:2017:i:3:f:7_3_6
    as

    Download full text from publisher

    File URL: http://www.scienpress.com/Upload/JAFB%2fVol%207_3_6.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Christian Upper, 2007. "Using counterfactual simulations to assess the danger of contagion in interbank markets," BIS Working Papers 234, Bank for International Settlements.
    2. Gai, Prasanna & Kapadia, Sujit, 2010. "Contagion in financial networks," Bank of England working papers 383, Bank of England.
    3. Helmut Elsinger & Alfred Lehar & Martin Summer, 2006. "Risk Assessment for Banking Systems," Management Science, INFORMS, vol. 52(9), pages 1301-1314, September.
    4. Manfred Gilli & Evis këllezi, 2006. "An Application of Extreme Value Theory for Measuring Financial Risk," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 207-228, May.
    5. Gencay, Ramazan & Selcuk, Faruk, 2006. "Overnight borrowing, interest rates and extreme value theory," European Economic Review, Elsevier, vol. 50(3), pages 547-563, April.
    6. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    7. Larry Eisenberg & Thomas H. Noe, 2001. "Systemic Risk in Financial Systems," Management Science, INFORMS, vol. 47(2), pages 236-249, February.
    8. Hols, Martien C A B & de Vries, Casper G, 1991. "The Limiting Distribution of Extremal Exchange Rate Returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(3), pages 287-302, July-Sept.
    9. Céline Gauthier & Alfred Lehar & Moez Souissi, 2010. "Macroprudential Regulation and Systemic Capital Requirements," Staff Working Papers 10-4, Bank of Canada.
    10. Mark Illing & Ying Liu, 2003. "An Index of Financial Stress for Canada," Staff Working Papers 03-14, Bank of Canada.
    11. Eric Santor, 2003. "Banking Crises and Contagion: Empirical Evidence," Staff Working Papers 03-1, Bank of Canada.
    12. Fuchun Li, 2009. "Testing for Financial Contagion with Applications to the Canadian Banking System," Staff Working Papers 09-14, Bank of Canada.
    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. Alexander Jiron & Wayne Passmore & Aurite Werman, 2021. "An empirical foundation for calibrating the G-SIB surcharge," BIS Working Papers 935, Bank for International Settlements.

    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. Arnd Hübsch & Ursula Walther, 2017. "The impact of network inhomogeneities on contagion and system stability," Annals of Operations Research, Springer, vol. 254(1), pages 61-87, July.
    2. Markus K. Brunnermeier & Patrick Cheridito, 2019. "Measuring and Allocating Systemic Risk," Risks, MDPI, vol. 7(2), pages 1-19, April.
    3. Qianqian Gao & Hong Fan, 2020. "Macroprudential regulation for a dynamic Chinese banking system with a scale-free network," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(3), pages 579-611, July.
    4. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    5. Cetina, Jill & Paddrik, Mark & Rajan, Sriram, 2018. "Stressed to the core: Counterparty concentrations and systemic losses in CDS markets," Journal of Financial Stability, Elsevier, vol. 35(C), pages 38-52.
    6. Alessandro Ferracci & Giulio Cimini, 2021. "Systemic risk in interbank networks: disentangling balance sheets and network effects," Papers 2109.14360, arXiv.org, revised Sep 2022.
    7. Aldasoro, Iñaki & Hüser, Anne-Caroline & Kok, Christoffer, 2022. "Contagion accounting in stress-testing," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
    8. Fabio Caccioli & Paolo Barucca & Teruyoshi Kobayashi, 2018. "Network models of financial systemic risk: a review," Journal of Computational Social Science, Springer, vol. 1(1), pages 81-114, January.
    9. Marko Krznar, 2009. "Contagion Risk in the Croatian Banking System," Working Papers 20, The Croatian National Bank, Croatia.
    10. Ladley, Daniel, 2013. "Contagion and risk-sharing on the inter-bank market," Journal of Economic Dynamics and Control, Elsevier, vol. 37(7), pages 1384-1400.
    11. Hitoshi Hayakawa, 2020. "Liquidity in Financial Networks," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 253-301, January.
    12. 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.
    13. Torri, Gabriele & Radi, Davide & Dvořáčková, Hana, 2022. "Catastrophic and systemic risk in the non-life insurance sector: A micro-structural contagion approach," Finance Research Letters, Elsevier, vol. 47(PB).
    14. Prasanna Gai & Sujit Kapadia, 2011. "A Network Model of Super-Systemic Crises," Central Banking, Analysis, and Economic Policies Book Series, in: Rodrigo Alfaro (ed.),Financial Stability, Monetary Policy, and Central Banking, edition 1, volume 15, chapter 13, pages 411-432, Central Bank of Chile.
    15. Sergio R. Stancato de Souza, 2014. "Capital Requirements, Liquidity and Financial Stability: the case of Brazil," Working Papers Series 375, Central Bank of Brazil, Research Department.
    16. Giulio Cimini & Matteo Serri, 2016. "Entangling Credit and Funding Shocks in Interbank Markets," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-15, August.
    17. Giansante, Simone & Manfredi, Sabato & Markose, Sheri, 2023. "Fair immunization and network topology of complex financial ecosystems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 612(C).
    18. Teruyoshi Kobayashi, 2012. "Diversity among banks may increase systemic risk," Discussion Papers 1213, Graduate School of Economics, Kobe University.
    19. Marco Bardoscia & Stefano Battiston & Fabio Caccioli & Guido Caldarelli, 2015. "DebtRank: A Microscopic Foundation for Shock Propagation," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-13, June.
    20. Hamed Amini & Rama Cont & Andreea Minca, 2011. "Resilience to Contagion in Financial Networks," Papers 1112.5687, arXiv.org.

    More about this item

    Keywords

    monte carlo simulation; extreme value theory; garch; importance sampling; bank contagion;
    All these keywords.

    JEL classification:

    • G2 - Financial Economics - - Financial Institutions and Services

    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:spt:apfiba:v:7:y:2017:i:3:f:7_3_6. 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: Eleftherios Spyromitros-Xioufis (email available below). General contact details of provider: http://www.scienpress.com/ .

    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.