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When aggregating financial risk on a portfolio level, the specification of the dependence structure between the risk factors plays an important role. Promising parametric models are often based on a so-called copula approach. Case studies of market crashes suggest the application of concepts allowing for extremal dependence. We present a transformed copula as a new model that both fits the data and allows for exact prediction in the tails. It turns out that the new model improves benchmark models like the t- or Clayton copula with respect to risk measures like VaR or Expected Shortfall. By performing different goodness-of-fit tests, the quality of the estimation is examined. Copyright 2005 Royal Economic Society

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From the IR-spectra of matrix isolated SiO species a D 2h -structure has been postulated for the dimer and a D 3h -structure for the trimer. High quality Raman-spectra-necessary for the complete characterization-were missing so far. Here we report the Raman-spectra especially of the totally symmetric vibrations for Si 2 O 2 and Si 3 O 3 and their 16 O/ 18 O isotopomers isolated in solid methane. We also detect the most intense A 1 -vibration of Si 4 O 4 and can assign it with its 16 O/ 18 O isotopic splitting. Ab initio calculations for all oligomers are presented in order to support the assignment of the spectra and to obtain geometric and energetic information about the oligomeric species which have been detected experimentally.