IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1705.00691.html
   My bibliography  Save this paper

Particle systems with singular interaction through hitting times: application in systemic risk modeling

Author

Listed:
  • Sergey Nadtochiy
  • Mykhaylo Shkolnikov

Abstract

We propose an interacting particle system to model the evolution of a system of banks with mutual exposures. In this model, a bank defaults when its normalized asset value hits a lower threshold, and its default causes instantaneous losses to other banks, possibly triggering a cascade of defaults. The strength of this interaction is determined by the level of the so-called non-core exposure. We show that, when the size of the system becomes large, the cumulative loss process of a bank resulting from the defaults of other banks exhibits discontinuities. These discontinuities are naturally interpreted as systemic events, and we characterize them explicitly in terms of the level of non-core exposure and the fraction of banks that are "about to default". The main mathematical challenges of our work stem from the very singular nature of the interaction between the particles, which is inherited by the limiting system. A similar particle system is analyzed in [DIRT15a] and [DIRT15b], and we build on and extend their results. In particular, we characterize the large-population limit of the system and analyze the jump times, the regularity between jumps, and the local uniqueness of the limiting process.

Suggested Citation

  • Sergey Nadtochiy & Mykhaylo Shkolnikov, 2017. "Particle systems with singular interaction through hitting times: application in systemic risk modeling," Papers 1705.00691, arXiv.org.
  • Handle: RePEc:arx:papers:1705.00691
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1705.00691
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kay Giesecke & Konstantinos Spiliopoulos & Richard B. Sowers & Justin A. Sirignano, 2015. "Large Portfolio Asymptotics For Loss From Default," Mathematical Finance, Wiley Blackwell, vol. 25(1), pages 77-114, January.
    2. Gai, Prasanna & Kapadia, Sujit, 2010. "Contagion in financial networks," Bank of England working papers 383, Bank of England.
    3. J. Lorenz & S. Battiston & F. Schweitzer, 2009. "Systemic risk in a unifying framework for cascading processes on networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(4), pages 441-460, October.
    4. Horst, Ulrich, 2007. "Stochastic cascades, credit contagion, and large portfolio losses," Journal of Economic Behavior & Organization, Elsevier, vol. 63(1), pages 25-54, May.
    5. Ali Alichi & Mr. Cheol Hong & Mr. Sang Chul Ryoo, 2012. "Managing Non-Core Liabilities and Leverage of the Banking System: A Building Block for Macroprudential Policy Making in Korea," IMF Working Papers 2012/027, International Monetary Fund.
    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. Amir Dembo & Jean-Dominique Deuschel & Darrell Duffie, 2004. "Large portfolio losses," Finance and Stochastics, Springer, vol. 8(1), pages 3-16, January.
    8. Glasserman, Paul & Young, H. Peyton, 2015. "How likely is contagion in financial networks?," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 383-399.
    9. Kay Giesecke & Konstantinos Spiliopoulos & Richard B. Sowers & Justin A. Sirignano, 2011. "Large Portfolio Asymptotics for Loss From Default," Papers 1109.1272, arXiv.org, revised Feb 2015.
    10. Paolo Dai Pra & Wolfgang J. Runggaldier & Elena Sartori & Marco Tolotti, 2007. "Large portfolio losses: A dynamic contagion model," Papers 0704.1348, arXiv.org, revised Mar 2009.
    11. Paul Glasserman & Peyton Young, 2015. "Contagion in Financial Networks," Economics Series Working Papers 764, University of Oxford, Department of Economics.
    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 Lipton, 2020. "Old Problems, Classical Methods, New Solutions," Papers 2003.06903, arXiv.org.
    2. Tathagata Banerjee & Alex Bernstein & Zachary Feinstein, 2018. "Dynamic Clearing and Contagion in Financial Networks," Papers 1801.02091, arXiv.org, revised Nov 2022.
    3. Sergey Nadtochiy & Mykhaylo Shkolnikov, 2018. "Mean field systems on networks, with singular interaction through hitting times," Papers 1807.02015, arXiv.org, revised Sep 2019.
    4. Sean Ledger & Andreas Sojmark, 2018. "Uniqueness for contagious McKean--Vlasov systems in the weak feedback regime," Papers 1811.12356, arXiv.org, revised Oct 2019.
    5. Ben Hambly & Andreas Sojmark, 2018. "An SPDE Model for Systemic Risk with Endogenous Contagion," Papers 1801.10088, arXiv.org, revised Sep 2018.
    6. Aditya Maheshwari & Andrey Sarantsev, 2017. "Modeling Financial System with Interbank Flows, Borrowing, and Investing," Papers 1707.03542, arXiv.org, revised Oct 2018.
    7. Sean Ledger & Andreas Sojmark, 2018. "At the Mercy of the Common Noise: Blow-ups in a Conditional McKean--Vlasov Problem," Papers 1807.05126, arXiv.org, revised Mar 2024.
    8. Marcel Nutz & Yuchong Zhang, 2017. "A Mean Field Competition," Papers 1708.01308, arXiv.org.
    9. Alexander Lipton & Vadim Kaushansky & Christoph Reisinger, 2018. "Semi-analytical solution of a McKean-Vlasov equation with feedback through hitting a boundary," Papers 1808.05311, arXiv.org, revised Aug 2018.

    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. Zachary Feinstein & Andreas Sojmark, 2019. "A Dynamic Default Contagion Model: From Eisenberg-Noe to the Mean Field," Papers 1912.08695, arXiv.org.
    2. Paulo Ferreira & Éder J.A.L. Pereira & Hernane B.B. Pereira, 2020. "From Big Data to Econophysics and Its Use to Explain Complex Phenomena," JRFM, MDPI, vol. 13(7), pages 1-10, July.
    3. Li, Fei & Kang, Hao & Xu, Jingfeng, 2022. "Financial stability and network complexity: A random matrix approach," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 177-185.
    4. Agostino Capponi & Xu Sun & David D. Yao, 2020. "A Dynamic Network Model of Interbank Lending—Systemic Risk and Liquidity Provisioning," Mathematics of Operations Research, INFORMS, vol. 45(3), pages 1127-1152, August.
    5. Wei, Li & Yuan, Zhongyi, 2016. "The loss given default of a low-default portfolio with weak contagion," Insurance: Mathematics and Economics, Elsevier, vol. 66(C), pages 113-123.
    6. Tang, Qihe & Tong, Zhiwei & Xun, Li, 2022. "Insurance risk analysis of financial networks vulnerable to a shock," European Journal of Operational Research, Elsevier, vol. 301(2), pages 756-771.
    7. Shi, Qing & Sun, Xiaoqi & Jiang, Yile, 2022. "Concentrated commonalities and systemic risk in China's banking system: A contagion network approach," International Review of Financial Analysis, Elsevier, vol. 83(C).
    8. Navarro, Noemí & Tran, Dan H., 2018. "Shock Diffusion in Regular Networks: The Role of Transitive Cycles," MPRA Paper 86267, University Library of Munich, Germany.
    9. Mardi Dungey & Moses Kangogo & Vladimir Volkov, 2022. "Dynamic effects of network exposure on equity markets," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 569-629, December.
    10. Ioannis Anagnostou & Sumit Sourabh & Drona Kandhai, 2018. "Incorporating Contagion in Portfolio Credit Risk Models Using Network Theory," Complexity, Hindawi, vol. 2018, pages 1-15, January.
    11. Tang, Qihe & Tang, Zhaofeng & Yang, Yang, 2019. "Sharp asymptotics for large portfolio losses under extreme risks," European Journal of Operational Research, Elsevier, vol. 276(2), pages 710-722.
    12. Paolo Bartesaghi & Michele Benzi & Gian Paolo Clemente & Rosanna Grassi & Ernesto Estrada, 2019. "Risk-dependent centrality in economic and financial networks," Papers 1907.07908, arXiv.org, revised Apr 2020.
    13. Tabak, Benjamin Miranda & Silva, Thiago Christiano & Fiche, Marcelo Estrela & Braz, Tércio, 2021. "Citation likelihood analysis of the interbank financial networks literature: A machine learning and bibliometric approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    14. Gao, Fuqing & Zhu, Lingjiong, 2018. "Some asymptotic results for nonlinear Hawkes processes," Stochastic Processes and their Applications, Elsevier, vol. 128(12), pages 4051-4077.
    15. Paul Glasserman & H. Peyton Young, 2016. "Contagion in Financial Networks," Journal of Economic Literature, American Economic Association, vol. 54(3), pages 779-831, September.
    16. Tang, Qihe & Tong, Zhiwei & Yang, Yang, 2021. "Large portfolio losses in a turbulent market," European Journal of Operational Research, Elsevier, vol. 292(2), pages 755-769.
    17. Kangogo, Moses & Volkov, Vladimir, 2021. "Dynamic effects of network exposure on equity markets," Working Papers 2021-03, University of Tasmania, Tasmanian School of Business and Economics.
    18. Diem, Christian & Pichler, Anton & Thurner, Stefan, 2020. "What is the minimal systemic risk in financial exposure networks?," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    19. Nils Detering & Thilo Meyer-Brandis & Konstantinos Panagiotou & Daniel Ritter, 2018. "Financial Contagion in a Generalized Stochastic Block Model," Papers 1803.08169, arXiv.org, revised Dec 2019.
    20. Gabrielle Demange, 2018. "Contagion in Financial Networks: A Threat Index," Management Science, INFORMS, vol. 64(2), pages 955-970, February.

    More about this item

    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:arx:papers:1705.00691. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.