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Introduction The modelling of dependence between defaults is a key issue for the valuation and risk management of multi-name credit derivatives. The Gaussian copula model seems to have become an industry standard for pricing. It’s appeal is partly due to its ease of implementation via Monte Carlo simulation and the fact that the underlying dependence(More)
We compare some popular CDO pricing models, related to the bottom‐up approach. Dependence between default times is modelled through Gaussian, stochastic correlation, Student t, double t, Clayton and Marshall‐Olkin copulas. We detail the model properties and compare the semi‐analytic pricing approach with large portfolio approximation techniques. We study(More)
This contribution is an abridged version of the research paper “hedging default risks of CDOs in Markovian contagion models” (2008) to which we refer for further reading. We exhibit a replicating strategy of CDO tranches based upon dynamic trading of the corresponding credit default swap index. The aggregate loss follows a homogeneous Markov chain(More)
We have developed a new family of Archimedean copula processes for modeling the dynamic dependence between default times in a large portfolio of names and for pricing synthetic CDO tranches. After presenting their general properties, we show that there is a class of processes where default is not predictable. Then we study a new Clayton copula process in(More)
Disseminated intravascular coagulation is a complex hemostatic imbalance associated with many disease states. The potentially lethal systemic consequences of this disease mandate that the podiatric physician obtain a complete detailed history in addition to proceeding with appropriate consultations from other specialties. If haste is utilized and surgical(More)