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Why VAR Fails: Long Memory and Extreme Events in Financial Markets

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  • Cornelis A. Los
Abstract
The Value-at-Risk (VAR) measure is based on only the second moment of a rates of return distribution. It is an insufficient risk performance measure, since it ignores both the higher moments of the pricing distributions, like skewness and kurtosis, and all the fractional moments resulting from the long - term dependencies (long memory) of dynamic market pricing. Not coincidentally, the VaR methodology also devotes insufficient attention to the truly extreme financial events, i.e., those events that are catastrophic and that are clustering because of this long memory. Since the usual stationarity and i.i.d. assumptions of classical asset returns theory are not satisfied in reality, more attention should be paid to the measurement of the degree of dependence to determine the true risks to which any investment portfolio is exposed: the return distributions are time-varying and skewness and kurtosis occur and change over time. Conventional mean-variance diversification does not apply when the tails of the return distributions ate too fat, i.e., when many more than normal extreme events occur. Regrettably, also, Extreme Value Theory is empirically not valid, because it is based on the uncorroborated i.i.d. assumption.

Suggested Citation

  • Cornelis A. Los, 2004. "Why VAR Fails: Long Memory and Extreme Events in Financial Markets," Finance 0412014, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpfi:0412014
    Note: Type of Document - pdf; pages: 26
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    References listed on IDEAS

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    Cited by:

    1. Cornelis A. Los, 2005. "The Degree of Stability of Price Diffusion," Finance 0508006, University Library of Munich, Germany.
    2. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.

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    More about this item

    Keywords

    Long memory; Value at Risk; Extreme Value Theory; Portfolio Management; Degrees of Persistence;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • G19 - Financial Economics - - General Financial Markets - - - Other
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage

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