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Forecasting the Risk of Speculative Assets by Means of Copula Distributions
Year Of Publication: 2013
Month Of Publication: January
Resource Link: Click here to open
Pages: 35
Download Count: 0
View Count: 1159
Comment Num: 0
Language: English
Source: working paper
Who Can Read: Free
Date: 3-27-2013
Publisher: Administrator
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.
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Herwartz, Helmut Sign in to follow this author
Beckers, Benjamin Sign in to follow this author
Seidel, Moritz Sign in to follow this author
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