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Date de soutenance |
21/06/2012 |
Sujet |
Sciences de l'économie, de la gestion et de la société |
Fonds |
Ecole Polytechnique |
Mots-clés |
Dépendance extrême – Transport Optimal – Copules – Couplages de processus stochastiques – Dépendance entre vecteurs aléatoires |
Titre en anglais |
Three essays on modeling the dependence between financial assets |
Résumé en anglais |
This thesis addresses two aspects of the dependence between
financial assets. The first part is about the dependence between random
vectors. The first chapter consists in a comparison of several
algorithms that compute the optimal transport map for the quadratic cost
between two (possibly continuous) probabilities over R^n. These
algorithms compute couplings, called maximum correlation couplings,
which have a property of extreme dependence that naturally appears in
the definition of multivariate risk measures. The second chapter defines
a notion of extreme dependence between random vectors based on the
covariogram; the extreme couplings are characterized as maximum
correlation couplings, up to a linear transform of one of the
multivariate margins. A numerical method to compute these couplings is
provided, and applications to the stress testing of multivariate
dependence for portfolio allocation and the pricing of European options
on several underlyings are detailed. The last part describes the spatial
dependence between two Markovian diffusions, coupled with a state
dependent correlation function. An integrated Kolmogorov forward PDE is
established that relates the family of spatial copulas of the diffusion
and the correlation function. Then the problem of attainable spatial
dependence between two Brownian motions is addressed, and we show that
some classical copulas are not admissible to describe the stationary
dependence between Brownian motions. |
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