IDEAS home Printed from https://ideas.repec.org/p/osf/arabix/qmcdz.html
   My bibliography  Save this paper

Incremental Risk Charge Methodology

Author

Listed:
  • Xiao, Tim

Abstract

The incremental risk charge (IRC) is a new regulatory requirement from the Basel Committee in response to the recent financial crisis. Notably few models for IRC have been developed in the literature. This paper proposes a methodology consisting of two Monte Carlo simulations. The first Monte Carlo simulation simulates default, migration, and concentration in an integrated way. Combining with full re-valuation, the loss distribution at the first liquidity horizon for a subportfolio can be generated. The second Monte Carlo simulation is the random draws based on the constant level of risk assumption. It convolutes the copies of the single loss distribution to produce one year loss distribution. The aggregation of different subportfolios with different liquidity horizons is addressed. Moreover, the methodology for equity is also included, even though it is optional in IRC.

Suggested Citation

  • Xiao, Tim, 2018. "Incremental Risk Charge Methodology," arabixiv.org qmcdz, Center for Open Science.
    • Handle: RePEc:osf:arabix:qmcdz
    DOI: 10.31219/osf.io/qmcdz
    as

    Download full text from publisher

    File URL: https://osf.io/download/5dbf03efaf84c3000bea86fb/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/qmcdz?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Xiao, Tim, 2018. "Incremental Risk Charge Methodology," SocArXiv y43dx, Center for Open Science.
    2. Dirk Tasche, 2004. "The single risk factor approach to capital charges in case of correlated loss given default rates," Papers cond-mat/0402390, arXiv.org, revised Feb 2004.
    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. Xiao, Tim, 2018. "Incremental Risk Charge Methodology," SocArXiv y43dx, Center for Open Science.
    2. Matheus Pimentel Rodrigues & Andre Cury Maialy, 2019. "Measuring Default Risk For A Portfolio Of Equities," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(01), pages 1-21, 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. Rösch, Daniel & Scheule, Harald, 2009. "The Empirical Relation between Credit Quality, Recovery and Correlation," Hannover Economic Papers (HEP) dp-418, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    2. Barbagli, Matteo & Vrins, Frédéric, 2023. "Accounting for PD-LGD dependency: A tractable extension to the Basel ASRF framework," Economic Modelling, Elsevier, vol. 125(C).
    3. Janette Larney & Gerrit Lodewicus Grobler & James Samuel Allison, 2022. "Introducing Two Parsimonious Standard Power Mixture Models for Bimodal Proportional Data with Application to Loss Given Default," Mathematics, MDPI, vol. 10(23), pages 1-19, November.
    4. Greg M. Gupton, 2005. "Advancing Loss Given Default Prediction Models: How the Quiet Have Quickened," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 34(2), pages 185-230, July.
    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. Daniel Rosch & Harald Scheule, 2008. "Credit Losses in Economic Downturns - Empirical Evidence for Hong Kong Mortgage Loans," Working Papers 152008, Hong Kong Institute for Monetary Research.
    7. Jiri Witzany, 2013. "Estimating Default and Recovery Rate Correlations," Working Papers IES 2013/03, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Apr 2013.
    8. Franco Varetto, 2017. "La correlazione tra PD ed LGD nell’analisi del rischio di credito/The correlation between probability of default and loss given default in the credit risk analysis," IRCrES Working Paper 201714, CNR-IRCrES Research Institute on Sustainable Economic Growth - Moncalieri (TO) ITALY - former Institute for Economic Research on Firms and Growth - Torino (TO) ITALY.
    9. António Santos, 2020. "The relation between PD and LGD: an application to a corporate loan portfolio," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    10. Thomas Hartmann-Wendels & Christopher Paulus Imanto, 2023. "Is the regulatory downturn LGD adequate? Performance analysis and alternative methods," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 74(3), pages 736-747, March.
    11. Li, Hui, 2010. "Downturn LGD: A Spot Recovery Approach," MPRA Paper 20010, University Library of Munich, Germany.
    12. repec:ptu:bdpart:r202009 is not listed on IDEAS
    13. Li, Hui, 2010. "Downturn LGD: A Spot Recovery Approach," MPRA Paper 71986, University Library of Munich, Germany, revised 30 Apr 2013.
    14. Gürtler, Marc & Heithecker, Dirk, 2005. "Systematic credit cycle risk of financial collaterals: Modelling and evidence," Working Papers FW15V2, Technische Universität Braunschweig, Institute of Finance.
    15. Richard J Martin, 2011. "A CDS Option Miscellany," Papers 1201.0111, arXiv.org, revised May 2019.
    16. Annalisa Di Clemente, 2013. "Considering the dependence between the credit loss severity and the probability of default in the estimate of portfolio credit risk: an experimental analysis," STUDI ECONOMICI, FrancoAngeli Editore, vol. 2013(109), pages 5-24.
    17. Rafael Weißbach & Carsten Lieres und Wilkau, 2010. "Economic capital for nonperforming loans," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 24(1), pages 67-85, March.
    18. repec:czx:journl:v:21:y:2014:i:33:id:210 is not listed on IDEAS
    19. Aneta Ptak-Chmielewska & Paweł Kopciuszewski, 2023. "Application of the Bayesian approach in loss given default modelling," Bank i Kredyt, Narodowy Bank Polski, vol. 54(6), pages 625-650.
    20. Matheus Pimentel Rodrigues & Andre Cury Maialy, 2019. "Measuring Default Risk For A Portfolio Of Equities," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(01), pages 1-21, February.
    21. Kim, Joocheol & Kim, KiHyung, 2006. "Loss Given Default Modelling under the Asymptotic Single Risk Factor Assumption," MPRA Paper 860, University Library of Munich, Germany.
    22. Weißbach, Rafael & von Lieres und Wilkau, Carsten, 2006. "On partial defaults in portfolio credit risk: Comparing economic and regulatory view," Technical Reports 2006,02, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

    More about this item

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

    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:osf:arabix:qmcdz. 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: OSF (email available below). General contact details of provider: https://arabixiv.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.