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Performance of monthly multivariate filtered historical simulation value-at-risk

Author

Listed:
  • Chrétien, Stéphane
  • Coggins, Frank
  • Trudel, Yves

Abstract

This study examines the performance of 16 value-at-risk (VaR) models in the context of institutional portfolio management. The paper focuses on multivariate versus univariate approaches of asset modelling, estimated with monthly or daily data, and filtered historical simulation (FHS) versus Monte Carlo simulation (MCS) techniques. Tests on VaR violations show that the best-performing models are generally the univariate FHS and MCS models with daily asymmetric GARCH specification. A comparative analysis reveals that the asymmetric impact of positive versus negative shocks in the conditional volatility is the most important feature of the models.

Suggested Citation

  • Chrétien, Stéphane & Coggins, Frank & Trudel, Yves, 2010. "Performance of monthly multivariate filtered historical simulation value-at-risk," Journal of Risk Management in Financial Institutions, Henry Stewart Publications, vol. 3(3), pages 259-277, June.
    • Handle: RePEc:aza:rmfi00:y:2010:v:3:i:3:p:259-277
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    More about this item

    Keywords

    conditional VaR models; VaR models by filtered historical simulations; GARCH models; G11; G23;
    All these keywords.

    JEL classification:

    • G2 - Financial Economics - - Financial Institutions and Services
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit

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