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Value at Risk: Implementing a Risk Measurement Standard

Author

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  • Christopher Marshall
  • Michael Siegel

Abstract

In the wake of recent failures of risk management, there has been a widespread call for improved quantification of the financial risks facing firms. At the forefront of this clamor has been Value at Risk. Previous research has identified differences in models, or Model Risk, as an important impediment to developing a Value at Risk standard. By contrast, this paper considers the divergence in a model's implementation in software and how it too, affects the establishment of a risk measurement standard. Different leading risk management systems' vendors were given identical portfolios of instruments of varying complexity, and were asked to assess the value at risk according to one common model, J.P. Morgan's RiskMetrics™. We analyzed the VaR results on a case by case basis, and in terms of prior expectations from the structure of financial instruments in the portfolio, as well as prior vendor expectations about the relative complexity of different asset classes. It follows that this research indicates the extent to which one particular model of risk can be effectively specified in advance, independent of the model's detailed implementation and use in practice. Key words: Risk Management, Financial Services, Model Management. This paper was presented at the Financial Institutions Center's October 1996 conference on "

Suggested Citation

  • Christopher Marshall & Michael Siegel, 1996. "Value at Risk: Implementing a Risk Measurement Standard," Center for Financial Institutions Working Papers 96-47, Wharton School Center for Financial Institutions, University of Pennsylvania.
  • Handle: RePEc:wop:pennin:96-47
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    File URL: http://fic.wharton.upenn.edu/fic/papers/96/9647.pdf
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    References listed on IDEAS

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    Cited by:

    1. Matthew Pritsker, 1996. "Evaluating Value-at-Risk Methodologies: Accuracy versus Computational Time," Center for Financial Institutions Working Papers 96-48, Wharton School Center for Financial Institutions, University of Pennsylvania.
    2. Matthew Pritsker, 1997. "Evaluating Value at Risk Methodologies: Accuracy versus Computational Time," Journal of Financial Services Research, Springer;Western Finance Association, vol. 12(2), pages 201-242, October.
    3. Anthony M. Santomero, 1997. "Commercial Bank Risk Management: An Analysis of the Process," Center for Financial Institutions Working Papers 95-11, Wharton School Center for Financial Institutions, University of Pennsylvania.
    4. Anthony Santomero, 1997. "Commercial Bank Risk Management: An Analysis of the Process," Journal of Financial Services Research, Springer;Western Finance Association, vol. 12(2), pages 83-115, October.

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