IDEAS home Printed from https://ideas.repec.org/a/ush/jaessh/v4y2009i4(10)_winter2009p81.html
   My bibliography  Save this article

A Practical Approach To Model Banking Risks Using Loss Distribution Approach (Lda) In Basel Ii Framework

Author

Listed:
  • Raquel BARREIRA
  • Tristan PRYER
  • Qi TANG

Abstract

In Basel II Capital Accord, the Advanced Measurement Approaches (AMA) is stated as one of the pillar stone methods for calculating corporate risk reserves. One of the common yet cumbersome methods is the one known as loss distribution approach (cf. [Chernobai A S, Rachev S T and Fabozzi F J, (2007)]. In this article, we present an easy to implement scheme through electronic means and discuss some of the mathematical problems we encountered in the process together with proposed solution methods and further sought on the issues.

Suggested Citation

  • Raquel BARREIRA & Tristan PRYER & Qi TANG, 2009. "A Practical Approach To Model Banking Risks Using Loss Distribution Approach (Lda) In Basel Ii Framework," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 4(4(10)_Win), pages 483-493.
    • Handle: RePEc:ush:jaessh:v:4:y:2009:i:4(10)_winter2009:p:81
    as

    Download full text from publisher

    File URL: http://www.jaes.reprograph.ro/articles/winter2009/BarreiraR_PryerT_TangQ.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pavel Cizek & Wolfgang Karl Härdle & Rafal Weron, 2005. "Statistical Tools for Finance and Insurance," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0501.
    2. Rosenberg, Joshua V. & Schuermann, Til, 2006. "A general approach to integrated risk management with skewed, fat-tailed risks," Journal of Financial Economics, Elsevier, vol. 79(3), pages 569-614, March.
    Full references (including those not matched with items on IDEAS)

    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. Cui, Yiran & del Baño Rollin, Sebastian & Germano, Guido, 2017. "Full and fast calibration of the Heston stochastic volatility model," European Journal of Operational Research, Elsevier, vol. 263(2), pages 625-638.
    2. Härdle, Wolfgang Karl & Burnecki, Krzysztof & Weron, Rafał, 2004. "Simulation of risk processes," Papers 2004,01, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    3. Rafał Weron, 2009. "Heavy-tails and regime-switching in electricity prices," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 69(3), pages 457-473, July.
    4. Marcel Wollschlager & Rudi Schafer, 2015. "Impact of non-stationarity on estimating and modeling empirical copulas of daily stock returns," Papers 1506.08054, arXiv.org.
    5. Michal Benko & Wolfgang Härdle & Alois Kneip, 2006. "Common Functional Principal Components," SFB 649 Discussion Papers SFB649DP2006-010, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. Helmut Elsinger & Alfred Lehar & Martin Summer, 2006. "Risk Assessment for Banking Systems," Management Science, INFORMS, vol. 52(9), pages 1301-1314, September.
    7. Dassios, Angelos & Qu, Yan & Zhao, Hongbiao, 2018. "Exact simulation for a class of tempered stable," LSE Research Online Documents on Economics 86981, London School of Economics and Political Science, LSE Library.
    8. Greg Hannsgen, 2011. "Infinite-variance, Alpha-stable Shocks in Monetary SVAR: Final Working Paper Version," Economics Working Paper Archive wp_682, Levy Economics Institute.
    9. Breuer, Thomas & Jandacka, Martin & Rheinberger, Klaus & Summer, Martin, 2010. "Does adding up of economic capital for market- and credit risk amount to conservative risk assessment?," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 703-712, April.
    10. Jianping Li & Lu Wei & Cheng-Few Lee & Xiaoqian Zhu & Dengsheng Wu, 2018. "Financial statements based bank risk aggregation," Review of Quantitative Finance and Accounting, Springer, vol. 50(3), pages 673-694, April.
    11. Shim Jeungbo & Lee Seung-Hwan, 2017. "Dependency between Risks and the Insurer’s Economic Capital: A Copula-based GARCH Model," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 11(1), pages 1-29, January.
    12. Paola Palmitesta & Corrado Provasi, 2005. "Aggregation of Dependent Risks Using the Koehler–Symanowski Copula Function," Computational Economics, Springer;Society for Computational Economics, vol. 25(1), pages 189-205, February.
    13. Yu, Lining & Voit, Eberhard O., 2006. "Construction of bivariate S-distributions with copulas," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1822-1839, December.
    14. Eudald Romo & Luis Ortiz-Gracia, 2021. "SWIFT calibration of the Heston model," Papers 2103.01570, arXiv.org.
    15. Michal Benko & Alois Kneip, 2005. "Common functional component modelling," SFB 649 Discussion Papers SFB649DP2005-016, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. Mark Carey & René M. Stulz, 2007. "The Risks of Financial Institutions," NBER Books, National Bureau of Economic Research, Inc, number care06-1, March.
    17. Ogwang, Tomson, 2013. "Is the wealth of the world’s billionaires Paretian?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 757-762.
    18. repec:onb:oenbwp:y::i:150:b:1 is not listed on IDEAS
    19. Hanene MEJDOUB & Mounira BEN ARAB, 2017. "A Multivariate Analysis for Risk Capital Estimation in Insurance Industry: Vine Copulas," Asian Development Policy Review, Asian Economic and Social Society, vol. 5(2), pages 100-119, June.
    20. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    21. Penikas, Henry & Simakova, Varvara, 2009. "Interest Rate Risk Management Based on Copula-GARCH Models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 13(1), pages 3-36.

    More about this item

    Keywords

    loss distribution approach; corporate risk; Basel II principles;
    All these keywords.

    JEL classification:

    • C - Mathematical and Quantitative Methods
    • P - Political Economy and Comparative Economic Systems

    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:ush:jaessh:v:4:y:2009:i:4(10)_winter2009:p:81. 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: Laura Stefanescu (email available below). General contact details of provider: https://edirc.repec.org/data/fmuspro.html .

    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.