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Forecasting the Risk of Speculative Assets by Means of Copula Distributions

Benjamin Beckers (), Helmut Herwartz and Moritz Seidel

No 1282, Discussion Papers of DIW Berlin from DIW Berlin, German Institute for Economic Research

Abstract: 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.

Keywords: copula distributions; expected shortfall; GARCH; model selection; non-Gaussian innovations; risk forecasting; value-at-risk (search for similar items in EconPapers)
JEL-codes: C22 C51 C52 C53 G32 (search for similar items in EconPapers)
Pages: 35 p.
Date: 2013
New Economics Papers: this item is included in nep-for and nep-rmg
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