IDEAS home Printed from https://ideas.repec.org/a/spr/trosos/v16y2022i2d10.1007_s12626-022-00122-y.html
   My bibliography  Save this article

Multi-dimensional Self-Exciting NBD Process and Default Portfolios

Author

Listed:
  • Masato Hisakado

    (Nomura Holdings, Inc.)

  • Kodai Hattori

    (Hirosaki University)

  • Shintaro Mori

    (Hirosaki University)

Abstract

In this study, we apply a multidimensional self-exciting negative binomial distribution (SE-NBD) process to default portfolios with 13 sectors. The SE-NBD process is a Poisson process with a gamma-distributed intensity function. We extend the SE-NBD process to a multidimensional process. Using the multidimensional SE-NBD process (MD-SE-NBD), we can estimate interactions between these 13 sectors as a network. By applying impact analysis, we can classify upstream and downstream sectors. The upstream sectors are real-estate and financial institution (FI) sectors. From these upstream sectors, shock spreads to the downstream sectors. This is an amplifier of the shock. This is consistent with the analysis of bubble bursts. We compare these results to the multidimensional Hawkes process (MD-Hawkes) that has a zero-variance intensity function.

Suggested Citation

  • Masato Hisakado & Kodai Hattori & Shintaro Mori, 2022. "Multi-dimensional Self-Exciting NBD Process and Default Portfolios," The Review of Socionetwork Strategies, Springer, vol. 16(2), pages 493-512, October.
    • Handle: RePEc:spr:trosos:v:16:y:2022:i:2:d:10.1007_s12626-022-00122-y
    DOI: 10.1007/s12626-022-00122-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12626-022-00122-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12626-022-00122-y?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. P. Blanc & J. Donier & J.-P. Bouchaud, 2017. "Quadratic Hawkes processes for financial prices," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 171-188, February.
    2. Hisakado, Masato & Mori, Shintaro, 2020. "Phase transition in the Bayesian estimation of the default portfolio," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 544(C).
    3. Matthias Kirchner, 2017. "An estimation procedure for the Hawkes process," Quantitative Finance, Taylor & Francis Journals, vol. 17(4), pages 571-595, April.
    4. S. Mori & K. Kitsukawa & M. Hisakado, 2006. "Correlation Structures of Correlated Binomial Models and Implied Default Distribution," Papers physics/0609093, arXiv.org, revised Sep 2008.
    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. Takayuki Mizuno & Takaaki Ohnishi & Ryohei Hisano & Hiroshi Iyetomi & Tsutomu Watanabe, 2022. "Preface of Special Issue on Data Science Questing for a Better Society," The Review of Socionetwork Strategies, Springer, vol. 16(2), pages 333-335, October.
    2. Kotaro Sakuraba & Wataru Kurebayashi & Masato Hisakado & Shintaro Mori, 2024. "Self-exciting negative binomial distribution process and critical properties of intensity distribution," Evolutionary and Institutional Economics Review, Springer, vol. 21(2), pages 277-299, September.

    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. Kotaro Sakuraba & Wataru Kurebayashi & Masato Hisakado & Shintaro Mori, 2024. "Self-exciting negative binomial distribution process and critical properties of intensity distribution," Evolutionary and Institutional Economics Review, Springer, vol. 21(2), pages 277-299, September.
    2. Antoine Fosset & Jean-Philippe Bouchaud & Michael Benzaquen, 2020. "Endogenous Liquidity Crises," Post-Print hal-02567495, HAL.
    3. Omar El Euch & Jim Gatheral & Radov{s} Radoiv{c}i'c & Mathieu Rosenbaum, 2018. "The Zumbach effect under rough Heston," Papers 1809.02098, arXiv.org.
    4. Antoine Fosset & Jean-Philippe Bouchaud & Michael Benzaquen, 2020. "Non-parametric Estimation of Quadratic Hawkes Processes for Order Book Events," Papers 2005.05730, arXiv.org.
    5. Chenlong Li & Kaiyan Cui, 2024. "Multivariate Hawkes processes with spatial covariates for spatiotemporal event data analysis," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 76(4), pages 535-578, August.
    6. Jim Gatheral & Paul Jusselin & Mathieu Rosenbaum, 2020. "The quadratic rough Heston model and the joint S&P 500/VIX smile calibration problem," Papers 2001.01789, arXiv.org.
    7. Cao, Jingyi & Landriault, David & Li, Bin, 2020. "Optimal reinsurance-investment strategy for a dynamic contagion claim model," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 206-215.
    8. Marcus Cordi & Damien Challet & Serge Kassibrakis, 2021. "The market nanostructure origin of asset price time reversal asymmetry," Quantitative Finance, Taylor & Francis Journals, vol. 21(2), pages 295-304, February.
    9. Konark Jain & Jean-Franc{c}ois Muzy & Jonathan Kochems & Emmanuel Bacry, 2024. "No Tick-Size Too Small: A General Method for Modelling Small Tick Limit Order Books," Papers 2410.08744, arXiv.org, revised Nov 2024.
    10. Lee, Sangwook & Kim, Min Jae & Lee, Sun Young & Kim, Soo Yong & Ban, Joon Hwa, 2013. "The effect of the subprime crisis on the credit risk in global scale," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2060-2071.
    11. Konark Jain & Nick Firoozye & Jonathan Kochems & Philip Treleaven, 2024. "Limit Order Book Simulations: A Review," Papers 2402.17359, arXiv.org, revised Mar 2024.
    12. Turiel, Jeremy D. & Aste, Tomaso, 2022. "Heterogeneous criticality in high frequency finance: a phase transition in flash crashes," LSE Research Online Documents on Economics 113892, London School of Economics and Political Science, LSE Library.
    13. Maxime Morariu-Patrichi & Mikko Pakkanen, 2018. "State-dependent Hawkes processes and their application to limit order book modelling," CREATES Research Papers 2018-26, Department of Economics and Business Economics, Aarhus University.
    14. Maxime Morariu-Patrichi & Mikko S. Pakkanen, 2018. "State-dependent Hawkes processes and their application to limit order book modelling," Papers 1809.08060, arXiv.org, revised Sep 2021.
    15. Gr'egoire Szymanski & Wei Xu, 2025. "Mean-Field Limits for Nearly Unstable Hawkes Processes," Papers 2501.11648, arXiv.org.
    16. Ofelia Bonesini & Giorgia Callegaro & Martino Grasselli & Gilles Pag`es, 2023. "From elephant to goldfish (and back): memory in stochastic Volterra processes," Papers 2306.02708, arXiv.org, revised Jan 2025.
    17. Léo Parent, 2022. "The EWMA Heston model," Post-Print hal-04431111, HAL.
    18. Yang Lu, 2021. "The predictive distributions of thinning‐based count processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 42-67, March.
    19. Wen, Conghua & Zhai, Jia & Wang, Yinuo & Cao, Yi, 2024. "Implied volatility is (almost) past-dependent: Linear vs non-linear models," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    20. Kyungsub Lee, 2022. "Application of Hawkes volatility in the observation of filtered high-frequency price process in tick structures," Papers 2207.05939, arXiv.org, revised Sep 2024.

    More about this item

    Keywords

    Hawkes process; Hawkes graph;

    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:spr:trosos:v:16:y:2022:i:2:d:10.1007_s12626-022-00122-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.