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Measuring Economic Capital Using Loss Distributions

Received: 11 December 2013    Accepted:     Published: 30 January 2014
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Abstract

This paper investigates the complexity involved in the quantitative measurement of Economic Capital and proposes simulation methods as a practical solution for obtaining the loss distribution of a portfolio of obligors. The paper examines a one factor model to generate loss distribution which establishes the necessary ingredients to measure the credit risk quantities in a loan portfolio. The general elements of credit risk modeling are outlined and then a specific model that employs a Monte Carlo simulation is developed. An example is provided that calculates the risk quantities in a loan portfolio from which the Economic Capital in a credit risk portfolio is obtained.

Published in International Journal of Economics, Finance and Management Sciences (Volume 1, Issue 6)
DOI 10.11648/j.ijefm.20130106.29
Page(s) 406-412
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Economic Capital, Unexpected Loss, Obligor, Asset Value Correlation, Joint Probability of Default

References
[1] Bluhm, Ludger Overbeck., Wagner, Christoph., An Introduction to Credit Risk Modeling, Christian Chapman & Hall/CRC Financial Mathematics Series, pages 15-121,
[2] Hoogbruin, Peter-Paul., Journal of Global Association of Risk Professionals, September/October 2006 issue, pages 34-39.
[3] Haigh, John., Probability Models, Springer Undergraduate Mathematical Series, Springer, pages 1-86
[4] Barreto, Humberto., Howland, Frank M., Introductory Econometrics, Cambridge University Press, 2006, pages 215-235.
[5] David Vose, Risk Analysis A Quantitative Guide, John Wiley & Sons Ltd., 2003, page 59
[6] Berenson, Mark L., Levine, David M., Basic Business Statistics, Prentice-Hall International inc., Seventh Edition 1999, pages 291-330
[7] Winston, Wayne; Financial Models Using Simulation and Optimization II. Palisade Corporation NY. 2001, pages 9-20
[8] Addison-Wesley, Visual Basic an Object Oriented Approach, Pearson Education Ltd., 2001, pages 1-202
[9] Enrique Navarrete, Practical Calculation of Expected and Unexpected Losses on Operational Risk by Simulation Methods.
[10] Michael Kalkbrener (Deutsche Bank‘s Economic Capital Model LRC - Risk Analytics & Instruments, COMISEF Tutorial on Quantitative Finance, London, 18 October 2007.
[11] Martin, Hansen., Dr. Gary, van Vuuren., Mariarosa, Verde., Basel II Correlation Values., An Empirical Analysis of EL, UL and the IRB Model, Credit Market Research Financial Institutions Special Report, Fitch Rating 2008, Page 3.
[12] Bank for International Settlements, The New Basel Capital Accord, Consultative Document Basel Committee on Banking Supervision May 2001, Page 84.
Cite This Article
  • APA Style

    Osei Antwi, Alice Constance Mensah, Martin Owusu Amoamah, Dadzie Joseph. (2014). Measuring Economic Capital Using Loss Distributions. International Journal of Economics, Finance and Management Sciences, 1(6), 406-412. https://doi.org/10.11648/j.ijefm.20130106.29

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    ACS Style

    Osei Antwi; Alice Constance Mensah; Martin Owusu Amoamah; Dadzie Joseph. Measuring Economic Capital Using Loss Distributions. Int. J. Econ. Finance Manag. Sci. 2014, 1(6), 406-412. doi: 10.11648/j.ijefm.20130106.29

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    AMA Style

    Osei Antwi, Alice Constance Mensah, Martin Owusu Amoamah, Dadzie Joseph. Measuring Economic Capital Using Loss Distributions. Int J Econ Finance Manag Sci. 2014;1(6):406-412. doi: 10.11648/j.ijefm.20130106.29

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  • @article{10.11648/j.ijefm.20130106.29,
      author = {Osei Antwi and Alice Constance Mensah and Martin Owusu Amoamah and Dadzie Joseph},
      title = {Measuring Economic Capital Using Loss Distributions},
      journal = {International Journal of Economics, Finance and Management Sciences},
      volume = {1},
      number = {6},
      pages = {406-412},
      doi = {10.11648/j.ijefm.20130106.29},
      url = {https://doi.org/10.11648/j.ijefm.20130106.29},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijefm.20130106.29},
      abstract = {This paper investigates the complexity involved in the quantitative measurement of Economic Capital and proposes simulation methods as a practical solution for obtaining the loss distribution of a portfolio of obligors.  The paper examines a one factor model to generate loss distribution which establishes the necessary ingredients to measure the credit risk quantities in a loan portfolio. The general elements of credit risk modeling are outlined and then a specific model that employs a Monte Carlo simulation is developed. An example is provided that calculates the risk quantities in a loan portfolio from which the Economic Capital in a credit risk portfolio is obtained.},
     year = {2014}
    }
    

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    T1  - Measuring Economic Capital Using Loss Distributions
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    AU  - Alice Constance Mensah
    AU  - Martin Owusu Amoamah
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    AB  - This paper investigates the complexity involved in the quantitative measurement of Economic Capital and proposes simulation methods as a practical solution for obtaining the loss distribution of a portfolio of obligors.  The paper examines a one factor model to generate loss distribution which establishes the necessary ingredients to measure the credit risk quantities in a loan portfolio. The general elements of credit risk modeling are outlined and then a specific model that employs a Monte Carlo simulation is developed. An example is provided that calculates the risk quantities in a loan portfolio from which the Economic Capital in a credit risk portfolio is obtained.
    VL  - 1
    IS  - 6
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Author Information
  • Mathematics and Statistics Department, Accra Polytechnic, Accra-Ghana

  • Mathematics and Statistics Department, Accra Polytechnic, Accra-Ghana

  • Mathematics and Statistics Department, Accra Polytechnic, Accra-Ghana

  • Mathematics and Statistics Department, Accra Polytechnic, Accra-Ghana

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