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Value at Risk: Implementing a Risk Measurement Standard

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  • Christopher Marshall
  • Michael Siegel
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    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 "

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    File URL: http://fic.wharton.upenn.edu/fic/papers/96/9647.pdf
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    Bibliographic Info

    Paper provided by Wharton School Center for Financial Institutions, University of Pennsylvania in its series Center for Financial Institutions Working Papers with number 96-47.

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    Date of creation: Jun 1996
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    Handle: RePEc:wop:pennin:96-47

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    1. Joseph P. Hughes & William W. Lang & Loretta J. Mester, 1998. "The dollars and sense of bank consolidation," Working Papers 98-10, Federal Reserve Bank of Philadelphia.
    2. Joseph P. Hughes & Loretta J. Mester & Choon-Geol Moon, 2000. "Are scale economies in banking elusive or illusive? Evidence obtained by incorporating capital structure and risk-taking into models of bank production," Working Papers 00-4, Federal Reserve Bank of Philadelphia.
    3. Joseph P. Hughes & William W. Lang & Loretta J. Mester & Choon-Geol Moon, 1996. "Efficient banking under interstate branching," Working Papers 96-9, Federal Reserve Bank of Philadelphia.
    4. Joseph P. Hughes & Loretta J. Mester, . "A Quality and Risk-Adjusted Cost Function for Banks: Evidence on the "Too-Big-To-Fail" Doctrine," Rodney L. White Center for Financial Research Working Papers 25-92, Wharton School Rodney L. White Center for Financial Research.
    5. Calomiris, Charles W & Kahn, Charles M, 1991. "The Role of Demandable Debt in Structuring Optimal Banking Arrangements," American Economic Review, American Economic Association, vol. 81(3), pages 497-513, June.
    6. Allen N. Berger & Loretta J. Mester, 1997. "Inside the Black Box: What Explains Differences in the Efficiencies of Financial Institutions?," Center for Financial Institutions Working Papers 97-04, Wharton School Center for Financial Institutions, University of Pennsylvania.
    7. Gary Gorton & Richard Rosen, 1994. "Corporate Control, Portfolio Choice, and the Decline of Banking," Center for Financial Institutions Working Papers 95-09, Wharton School Center for Financial Institutions, University of Pennsylvania.
    8. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-26, June.
    9. Joseph Hughes, 1999. "Incorporating risk into the analysis of production," Atlantic Economic Journal, International Atlantic Economic Society, vol. 27(1), pages 1-23, March.
    10. Keeley, Michael C, 1990. "Deposit Insurance, Risk, and Market Power in Banking," American Economic Review, American Economic Association, vol. 80(5), pages 1183-1200, December.
    11. Saunders, Anthony & Strock, Elizabeth & Travlos, Nickolaos G, 1990. " Ownership Structure, Deregulation, and Bank Risk Taking," Journal of Finance, American Finance Association, vol. 45(2), pages 643-54, June.
    12. Joseph P. Hughes & Loretta J. Mester & Moon Choo-Geol, 2000. "Are scale economies in banking elusive or illusive? evidence obtained by incorporating capital structure and risk-taking into models of bank production," Proceedings 700, Federal Reserve Bank of Chicago.
    13. Rebecca S. Demsetz & Marc R. Saidenberg & Philip E. Strahan, 1996. "Banks with something to lose: the disciplinary role of franchise value," Economic Policy Review, Federal Reserve Bank of New York, issue Oct, pages 1-14.
    14. Joseph P. Hughes & William Lang, 1997. "Recovering Technologies That Account for Generalized Managerial Preferences: An Application to Non-Risks-Neutral Banks," Departmental Working Papers 199521, Rutgers University, Department of Economics.
    15. Joseph P. Hughes & Loretta J. Mester & Choon-Geol Moon, 2000. "Are Scale Economies in Banking Elusive or Illusive?," Departmental Working Papers 200004, Rutgers University, Department of Economics.
    16. Humphrey, David B & Pulley, Lawrence B, 1997. "Banks' Responses to Deregulation: Profits, Technology, and Efficiency," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 73-93, February.
    17. Tufano, Peter, 1996. " Who Manages Risk? An Empirical Examination of Risk Management Practices in the Gold Mining Industry," Journal of Finance, American Finance Association, vol. 51(4), pages 1097-1137, September.
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    Cited by:
    1. Anthony Santomero, 1997. "Commercial Bank Risk Management: An Analysis of the Process," Journal of Financial Services Research, Springer, vol. 12(2), pages 83-115, October.
    2. 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.
    3. Matthew Pritsker, 1997. "Evaluating Value at Risk Methodologies: Accuracy versus Computational Time," Journal of Financial Services Research, Springer, vol. 12(2), pages 201-242, October.

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