IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v508y2018icp118-130.html
   My bibliography  Save this article

Network topology and systemic risk in Peer-to-Peer lending market

Author

Listed:
  • Li, Yuelei
  • Hao, Aiting
  • Zhang, Xiaotao
  • Xiong, Xiong

Abstract

Peer-to-Peer lending market is presented as a complex network and its topology characteristics, such as the ratio of brokers’ connections, degree, ratio of available node pairs, betweenness centrality, network density, network efficiency and edges’ loading ability have been investigated in this paper. The main contribution of this paper is that modeling and analyzing the systemic risk in P2P lending market in the view point of complex network based on these topology characteristics. And the empirical research has been carried out by using the real data from one of the largest online platforms in China (www.renrendai.com). Result shows that the relationship between lending–borrowing network topology and the default loans is significant, which implies that these factors have strong relations to systemic risk in the network.

Suggested Citation

  • Li, Yuelei & Hao, Aiting & Zhang, Xiaotao & Xiong, Xiong, 2018. "Network topology and systemic risk in Peer-to-Peer lending market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 118-130.
  • Handle: RePEc:eee:phsmap:v:508:y:2018:i:c:p:118-130
    DOI: 10.1016/j.physa.2018.05.083
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437118306319
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2018.05.083?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. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    2. Franklin Allen & Douglas Gale, 2000. "Financial Contagion," Journal of Political Economy, University of Chicago Press, vol. 108(1), pages 1-33, February.
    3. Tabak, Benjamin M. & Takami, Marcelo & Rocha, Jadson M.C. & Cajueiro, Daniel O. & Souza, Sergio R.S., 2014. "Directed clustering coefficient as a measure of systemic risk in complex banking networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 211-216.
    4. Devin G. Pope & Justin R. Sydnor, 2011. "What’s in a Picture?: Evidence of Discrimination from Prosper.com," Journal of Human Resources, University of Wisconsin Press, vol. 46(1), pages 53-92.
    5. Gonzalez, Laura & Loureiro, Yuliya Komarova, 2014. "When can a photo increase credit? The impact of lender and borrower profiles on online peer-to-peer loans," Journal of Behavioral and Experimental Finance, Elsevier, vol. 2(C), pages 44-58.
    6. Iori, Giulia & Jafarey, Saqib & Padilla, Francisco G., 2006. "Systemic risk on the interbank market," Journal of Economic Behavior & Organization, Elsevier, vol. 61(4), pages 525-542, December.
    7. Lenzu, Simone & Tedeschi, Gabriele, 2012. "Systemic risk on different interbank network topologies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(18), pages 4331-4341.
    8. Mingfeng Lin & Nagpurnanand R. Prabhala & Siva Viswanathan, 2013. "Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending," Management Science, INFORMS, vol. 59(1), pages 17-35, August.
    9. Khwaja, Asim Ijaz & Iyer, Rajkamal & Luttmer, Erzo F.P. & Shue, Kelly, 2009. "Screening in New Credit Markets: Can Individual Lenders Infer Borrower Creditworthiness in Peer-to-Peer Lending?," Scholarly Articles 4448882, Harvard Kennedy School of Government.
    10. Juanjuan Zhang & Peng Liu, 2012. "Rational Herding in Microloan Markets," Management Science, INFORMS, vol. 58(5), pages 892-912, May.
    11. Freixas, Xavier & Parigi, Bruno M & Rochet, Jean-Charles, 2000. "Systemic Risk, Interbank Relations, and Liquidity Provision by the Central Bank," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 32(3), pages 611-638, August.
    12. Seth M. Freedman & Ginger Zhe Jin, 2011. "Learning by Doing with Asymmetric Information: Evidence from Prosper.com," NBER Working Papers 16855, National Bureau of Economic Research, Inc.
    13. Nier, Erlend & Yang, Jing & Yorulmazer, Tanju & Alentorn, Amadeo, 2007. "Network models and financial stability," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 2033-2060, June.
    14. Michael Boss & Helmut Elsinger & Martin Summer & Stefan Thurner, 2004. "Network topology of the interbank market," Quantitative Finance, Taylor & Francis Journals, vol. 4(6), pages 677-684.
    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. Li Li & Haifen Lin & Yibo Lyu, 2022. "Technology cluster coupling and invulnerability of industrial innovation networks: the role of centralized structure and technological turbulence," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1209-1231, March.
    2. Νikolaos A. Kyriazis, 2021. "Investigating the nexus between European major and sectoral stock indices, gold and oil during the COVID-19 pandemic," SN Business & Economics, Springer, vol. 1(4), pages 1-12, April.
    3. Menéndez-Caravaca, Eloísa & Bueno, Salvador & Gallego, M. Dolores, 2021. "Exploring the link between free and open source software and the collaborative economy: A Delphi-based scenario for the year 2025," Technological Forecasting and Social Change, Elsevier, vol. 173(C).

    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. Elosegui, Pedro & Forte, Federico D. & Montes-Rojas, Gabriel, 2022. "Network structure and fragmentation of the Argentinean interbank markets," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 3(3).
    2. Adão, Luiz F.S. & Silveira, Douglas & Ely, Regis A. & Cajueiro, Daniel O., 2022. "The impacts of interest rates on banks’ loan portfolio risk-taking," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    3. Yun, Tae-Sub & Jeong, Deokjong & Park, Sunyoung, 2019. "“Too central to fail” systemic risk measure using PageRank algorithm," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 251-272.
    4. Green, Christopher & Bai, Ye & Murinde, Victor & Ngoka, Kethi & Maana, Isaya & Tiriongo, Samuel, 2016. "Overnight interbank markets and the determination of the interbank rate: A selective survey," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 149-161.
    5. Sam Langfield & Kimmo Soramäki, 2016. "Interbank Exposure Networks," Computational Economics, Springer;Society for Computational Economics, vol. 47(1), pages 3-17, January.
    6. Jiang, Shanshan & Fan, Hong, 2021. "Systemic risk in the interbank market with overlapping portfolios and cross-ownership of the subordinated debts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    7. Christoph Siebenbrunner, 2021. "Quantifying the importance of different contagion channels as sources of systemic risk," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(1), pages 103-131, January.
    8. Jiajia, Liu & Kun, Guo & Fangcheng, Tang & Yahan, Wang & Shouyang, Wang, 2023. "The effect of the disposal of non-performing loans on interbank liquidity risk in China: A cash flow network-based analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 105-119.
    9. 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.
    10. Spiros Bougheas & Alan Kirman, 2015. "Complex Financial Networks and Systemic Risk: A Review," Dynamic Modeling and Econometrics in Economics and Finance, in: Pasquale Commendatore & Saime Kayam & Ingrid Kubin (ed.), Complexity and Geographical Economics, edition 127, pages 115-139, Springer.
    11. Silva, Thiago Christiano & de Souza, Sergio Rubens Stancato & Tabak, Benjamin Miranda, 2016. "Network structure analysis of the Brazilian interbank market," Emerging Markets Review, Elsevier, vol. 26(C), pages 130-152.
    12. Brandi, Giuseppe & Di Clemente, Riccardo & Cimini, Giulio, 2018. "Epidemics of liquidity shortages in interbank markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 255-267.
    13. Li, Shouwei & Sui, Xin, 2016. "Contagion risk in endogenous financial networks," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 591-597.
    14. Domenico Delli Gatti & Mauro Gallegati & Bruce C. Greenwald & Alberto Russo & Joseph E. Stiglitz, 2008. "Financially Constrained Fluctuations in an Evolving Network Economy," NBER Working Papers 14112, National Bureau of Economic Research, Inc.
    15. Pawe{l} Smaga & Mateusz Wili'nski & Piotr Ochnicki & Piotr Arendarski & Tomasz Gubiec, 2016. "Can banks default overnight? Modeling endogenous contagion on O/N interbank market," Papers 1603.05142, arXiv.org.
    16. Christoph Siebenbrunner, 2017. "Clearing algorithms and network centrality," Papers 1706.00284, arXiv.org.
    17. Temizsoy, Asena & Iori, Giulia & Montes-Rojas, Gabriel, 2017. "Network centrality and funding rates in the e-MID interbank market," Journal of Financial Stability, Elsevier, vol. 33(C), pages 346-365.
    18. Affinito, Massimiliano & Franco Pozzolo, Alberto, 2017. "The interbank network across the global financial crisis: Evidence from Italy," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 90-107.
    19. Krause, Andreas & Giansante, Simone, 2012. "Interbank lending and the spread of bank failures: A network model of systemic risk," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 583-608.
    20. Paul Glasserman & Peyton Young, 2015. "Contagion in Financial Networks," Economics Series Working Papers 764, University of Oxford, Department of Economics.

    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:eee:phsmap:v:508:y:2018:i:c:p:118-130. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.