Gaussian copula is by far the most popular copula used in the financial industry in default dependency modeling. However, it has a major drawback – it does not exhibit tail dependence, a very important property for copula. The essence of tail dependence is the interdependence when extreme events occur, say, defaults of corporate bonds. In this paper, we show that some tail dependence can be restored by introducing stochastic volatility on a Gaussian copula. Using perturbation methods we then derive an approximate copula – called perturbed Gaussian copula in this paper.
Fouque, J. and Zhou, X. (2008), "Perturbed Gaussian copula", Fouque, J., Fomby, T. and Solna, K. (Ed.) Econometrics and Risk Management (Advances in Econometrics, Vol. 22), Emerald Group Publishing Limited, Bingley, pp. 103-121. https://doi.org/10.1016/S0731-9053(08)22005-0Download as .RIS
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