|Authors:||Siburg, Karl Friedrich|
Weiß, Gregor N. F.
|Title:||Forecasting Portfolio-Value-at-Risk with Nonparametric Lower Tail Dependence Estimates|
|Abstract:||We propose to forecast the Value-at-Risk of bivariate portfolios using copulas which are calibrated on the basis of nonparametric sample estimates of the coefficient of lower tail dependence. We compare our proposed method to a conventional copula-GARCH model where the parameter of a Clayton copula is estimated via Canonical Maximum-Likelihood. The superiority of our proposed model is exemplified by analyzing a data sample of nine different financial portfolios. A comparison of the out-of-sample forecasting accuracy of both models confirms that our model yields economically significantly better Value-at-Risk forecasts than the competing parametric calibration strategy.|
|Subject Headings:||Canonical Maximum-Likelihood|
|Appears in Collections:||Preprints der Fakultät für Mathematik|
Files in This Item:
|mathematicalPreprint-2013-04.pdf||1.03 MB||Adobe PDF||View/Open|
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