IDEAS home Printed from https://ideas.repec.org/a/wsi/acsxxx/v16y2013i04n05ns0219525913500069.html
   My bibliography  Save this article

Enhancing The Resilience Of Networked Agents Through Risk Sharing

Author

Listed:
  • AKIRA NAMATAME

    (Department of Computer Science, National Defense Academy of Japan, 1-10-20 Hashirimizu, Yokosuka, Kanagawa 239-8686, Japan)

  • HOANG ANG Q. TRAN

    (Department of Computer Science, National Defense Academy of Japan, 1-10-20 Hashirimizu, Yokosuka, Kanagawa 239-8686, Japan)

Abstract

Since social-economic systems increase interdependency, a crucial question arises: Is an interconnected world a safer or a more dangerous place to live? Over the last few years, we have witnessed the dark side of increasing interdependencies. As such, there is a growing need to focus on how to mitigate networked risk and to enhance the system resilience to the impact of a large-scale shock. The traditional engineering approach has been to design systems that are less vulnerable to damage from hazard events. On the other hand, system resilience is the ability to recover from failure and provide the continuity of system function. The goal of the present paper is to investigate the gain from risk sharing. We propose a mechanism of risk sharing that may enhance the resilience of the networked systems. The proposed risk sharing protocols are based on coordinated incentives of agents to survive collectively by absorbing external shocks. The key issue we would like to analyze is how the gain from risk sharing depends on the capacity of each agent to absorb shock and on the interconnections patterns among agents with risk sharing rules. We demonstrate that risk sharing is beneficial from a systems point of view when the agents' capacities to shocks is high and detrimental when it is low. In particular, we evaluate the effectiveness of risk sharing in two domains. In the first domain, in which networked agents have the possibility of cascading failure, risk sharing is useful in mitigating systemic failure, especially if the agents are running at high load. In the second domain, we evaluate the ratio of safe agents who invest in risky portfolios or projects collectively. In this case, risk sharing is only beneficial if the agents' risk absorbing capacity is high.

Suggested Citation

  • Akira Namatame & Hoang Ang Q. Tran, 2013. "Enhancing The Resilience Of Networked Agents Through Risk Sharing," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 16(04n05), pages 1-22.
  • Handle: RePEc:wsi:acsxxx:v:16:y:2013:i:04n05:n:s0219525913500069
    DOI: 10.1142/S0219525913500069
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219525913500069
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S0219525913500069?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gai, Prasanna & Kapadia, Sujit, 2010. "Contagion in financial networks," Bank of England working papers 383, Bank of England.
    2. Giulio Cainelli & Sandro Montresor & Giuseppe Vittucci Marzetti, 2013. "Production and financial linkages in inter-firm networks: structural variety, risk-sharing and resilience," Economic Complexity and Evolution, in: Andreas Pyka & Esben Sloth Andersen (ed.), Long Term Economic Development, edition 127, pages 113-136, Springer.
    3. Gabriele Tedeschi & Amin Mazloumian & Mauro Gallegati & Dirk Helbing, 2012. "Bankruptcy Cascades in Interbank Markets," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-10, December.
    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. Gopal R. Patil & B. K. Bhavathrathan, 2016. "Effect Of Traffic Demand Variation On Road Network Resilience," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 19(01n02), pages 1-18, February.

    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. Brini, Alessio & Tedeschi, Gabriele & Tantari, Daniele, 2023. "Reinforcement learning policy recommendation for interbank network stability," Journal of Financial Stability, Elsevier, vol. 67(C).
    2. Andre R. Neveu, 2018. "A survey of network-based analysis and systemic risk measurement," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(2), pages 241-281, July.
    3. Teteryatnikova, Mariya, 2014. "Systemic risk in banking networks: Advantages of “tiered” banking systems," Journal of Economic Dynamics and Control, Elsevier, vol. 47(C), pages 186-210.
    4. Tao Xu & Jianmin He & Shouwei Li, 2016. "Multi-Channel Contagion In Dynamic Interbank Market Network," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 19(06n07), pages 1-25, September.
    5. Daniel Grigat & Fabio Caccioli, 2017. "Reverse stress testing interbank networks," Papers 1702.08744, arXiv.org, revised Mar 2017.
    6. Gabbi, Giampaolo & Iori, Giulia & Jafarey, Saqib & Porter, James, 2015. "Financial regulations and bank credit to the real economy," Journal of Economic Dynamics and Control, Elsevier, vol. 50(C), pages 117-143.
    7. De Caux, Robert & McGroarty, Frank & Brede, Markus, 2017. "The evolution of risk and bailout strategy in banking systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 109-118.
    8. 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.
    9. Champagne, Claudia, 2014. "The international syndicated loan market network: An “unholy trinity”?," Global Finance Journal, Elsevier, vol. 25(2), pages 148-168.
    10. Bargigli, Leonardo & Gallegati, Mauro, 2011. "Random digraphs with given expected degree sequences: A model for economic networks," Journal of Economic Behavior & Organization, Elsevier, vol. 78(3), pages 396-411, May.
    11. Feinstein, Zachary, 2020. "Capital regulation under price impacts and dynamic financial contagion," European Journal of Operational Research, Elsevier, vol. 281(2), pages 449-463.
    12. Fariba Karimi & Matthias Raddant, 2016. "Cascades in Real Interbank Markets," Computational Economics, Springer;Society for Computational Economics, vol. 47(1), pages 49-66, January.
    13. 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.
    14. Alessandro Ferracci & Giulio Cimini, 2021. "Systemic risk in interbank networks: disentangling balance sheets and network effects," Papers 2109.14360, arXiv.org, revised Sep 2022.
    15. Miao He & Yanhong Guo, 2022. "Systemic Risk Contributions of Financial Institutions during the Stock Market Crash in China," Sustainability, MDPI, vol. 14(9), pages 1-14, April.
    16. Kanno, Masayasu, 2020. "Interconnectedness and systemic risk in the US CDS market," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    17. Kuzubaş, Tolga Umut & Saltoğlu, Burak & Sever, Can, 2016. "Systemic risk and heterogeneous leverage in banking networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 358-375.
    18. Maryam Farboodi, 2014. "Intermediation and Voluntary Exposure to Counterparty Risk," 2014 Meeting Papers 365, Society for Economic Dynamics.
    19. Kobayashi, Teruyoshi & Takaguchi, Taro, 2018. "Identifying relationship lending in the interbank market: A network approach," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 20-36.
    20. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 958-969.

    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:wsi:acsxxx:v:16:y:2013:i:04n05:n:s0219525913500069. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/acs/acs.shtml .

    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.