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The Emperor has no Clothes: Limits to Risk Modelling

  • Jon Danielsson

    ()

This paper considers the properties of risk measures, primarily Value-at Risk (VaR), from both internal and external (regulatory) points of view. It is argued that since market data is endogenous to market behavior, statistical analysis made in times of stability does not provide much guidance in times of crisis. In an extensive survey across data classes and risk models, the empirical properties of current risk forecasting models are found to be lacking in robustness while being excessively volatile. For regulatory use, the VaR measure is lacking in the ability to fulfil its intended task, it gives misleading information about risk, and in some cases may actually increase both idiosyncratic and systemic risk. Finally, it is hypothesized that risk modelling is not an appropriate foundation for regulatory design, and alternative mechanisms are discussed.

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File URL: http://www.lse.ac.uk/fmg/documents/specialPapers/2000/sp126.pdf
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Paper provided by Financial Markets Group in its series FMG Special Papers with number sp126.

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Date of creation: Oct 2000
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Handle: RePEc:fmg:fmgsps:sp126
Contact details of provider: Web page: http://www.lse.ac.uk/fmg/

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  1. Morris, Stephen & Shin, Hyun Song, 1999. "Risk Management with Interdependent Choice," Oxford Review of Economic Policy, Oxford University Press, vol. 15(3), pages 52-62, Autumn.
  2. de Bandt, Olivier & Hartmann, Philipp, 2000. "Systemic Risk: A Survey," CEPR Discussion Papers 2634, C.E.P.R. Discussion Papers.
  3. Hartmann, Philipp & Straetmans, Stefan & de Vries, Casper, 2001. "Asset market linkages in crisis periods," Working Paper Series 0071, European Central Bank.
  4. Jean-Pierre Zigrand & Jon Danielsson, 2001. "What happens when you regulate risk?: evidence from a simple equilibrium model," LSE Research Online Documents on Economics 25069, London School of Economics and Political Science, LSE Library.
  5. Dong-Hyun Ahn & Jacob Boudoukh & Matthew Richardson & Robert F. Whitelaw, 1999. "Optimal Risk Management Using Options," Journal of Finance, American Finance Association, vol. 54(1), pages 359-375, 02.
  6. Philippe Artzner & Freddy Delbaen & Jean-Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228.
  7. Drost, F.C. & Nijman, T.E., 1990. "Temporal Aggregation Of Garch Processes," Papers 9066, Tilburg - Center for Economic Research.
  8. Con Keating & Hyun Song Shin & Charles Goodhart & Jon Danielsson, 2001. "An Academic Response to Basel II," FMG Special Papers sp130, Financial Markets Group.
  9. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
  10. Drost, F.C. & Nijman, T.E., 1993. "Temporal aggregation of GARCH processes," Other publications TiSEM 0642fb61-c7f4-4281-b484-4, Tilburg University, School of Economics and Management.
  11. Peter F. Christoffersen & Francis X. Diebold, 1998. "How Relevant is Volatility Forecasting for Financial Risk Management?," NBER Working Papers 6844, National Bureau of Economic Research, Inc.
  12. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
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