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Forecasting the Risk of Speculative Assets by Means of Copula Distributions


  • Benjamin Beckers
  • Helmut Herwartz
  • Moritz Seidel


The GARCH(1,1) model and its extensions have become a standard econometric tool for modeling volatility dynamics of financial returns and port-folio risk. In this paper, we propose an adjustment of GARCH implied conditional value-at-risk and expected shortfall forecasts that exploits the predictive content of uncorrelated, yet dependent model innovations. The adjustment is motivated by non-Gaussian characteristics of model residuals, and is implemented in a semiparametric fashion by means of conditional moments of simulated bivariate standardized copula distributions. We conduct in-sample forecasting comparisons for a set of 18 stock market indices. In total, four competing copula-GARCH models are contrasted against each other on the basis of their one-step ahead forecasting performance. With regard to forecast unbiasedness and precision, especially the Frank-GARCH models provide most conservative risk forecasts and out-perform all rival models.

Suggested Citation

  • Benjamin Beckers & Helmut Herwartz & Moritz Seidel, 2013. "Forecasting the Risk of Speculative Assets by Means of Copula Distributions," Discussion Papers of DIW Berlin 1282, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp1282

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    References listed on IDEAS

    1. Martin Andersson & Sierdjan Koster, 2011. "Sources of persistence in regional start-up rates--evidence from Sweden," Journal of Economic Geography, Oxford University Press, vol. 11(1), pages 179-201, January.
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    More about this item


    copula distributions; expected shortfall; GARCH; model selection; non-Gaussian innovations; risk forecasting; value-at-risk;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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