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La Value-at-Risk: Modèles de la VaR, simulations en Visual Basic (Excel) et autres mesures récentes du risque de marché

Author

Listed:
  • Francois-Éric Racicot

    () (Département des sciences administratives, Université du Québec (Outaouais) et LRSP)

  • Raymond Théoret

    () (Département de stratégie des affaires, Université du Québec (Montréal))

Abstract

Since the end of the nineties, Basle Committee has required that banks compute periodically their VaR and maintain sufficient capital to pay the eventual losses projected by VaR. Unfortunately, there is not only one measure of VaR because volatility, which is a fundamental component of VaR, is latent. Therefore, banks must use many VaR models to compute the range of their prospective losses. These computations might be complex because the distribution of high frequency returns is not normal. This article analyses many VaR models and produces their programs in Visual Basic. It considers also other new measures of market risk and the use of copulas and Fourier Transform for the computation of VaR.

Suggested Citation

  • Francois-Éric Racicot & Raymond Théoret, 2006. "La Value-at-Risk: Modèles de la VaR, simulations en Visual Basic (Excel) et autres mesures récentes du risque de marché," RePAd Working Paper Series UQO-DSA-wp022006, Département des sciences administratives, UQO.
  • Handle: RePEc:pqs:wpaper:022006
    as

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    File URL: http://www.repad.org/ca/qc/uq/uqo/dsa/VaRRacicotTheoret.pdf
    File Function: First version, 2006
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    References listed on IDEAS

    as
    1. Fama, Eugene F & French, Kenneth R, 1992. " The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    2. Pierre Giot & Sébastien Laurent, 2003. "Value-at-risk for long and short trading positions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., pages 641-663.
    3. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    4. Simon Benninga, 2000. "Financial Modeling, 2nd Edition," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262024829, January.
    5. Pierre Giot & Sébastien Laurent, 2003. "Value-at-risk for long and short trading positions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., pages 641-663.
    6. Cooley, Philip L, 1977. "A Multidimensional Analysis of Institutional Investor Perception of Risk," Journal of Finance, American Finance Association, vol. 32(1), pages 67-78, March.
    7. Fung, William & Hsieh, David A, 1997. "Empirical Characteristics of Dynamic Trading Strategies: The Case of Hedge Funds," Review of Financial Studies, Society for Financial Studies, vol. 10(2), pages 275-302.
    8. Kraus, Alan & Litzenberger, Robert H, 1976. "Skewness Preference and the Valuation of Risk Assets," Journal of Finance, American Finance Association, vol. 31(4), pages 1085-1100, September.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Ingénierie financière; simulation de Monte Carlo; banques; copules; transformée de Fourier.;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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