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Bayesian Methods in Portfolio Credit Risk Management

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Bayesian Methods in
Portfolio Credit Risk Management
A dissertation submitted to the
SWISS FEDERAL INSTITUTE OF TECHNOLOGY
ZURICH
for the degree of
Doctor of Sciences
presented by
JONATHAN ERIK PURVIS WENDIN
MSc. Engineering Physics KTH
born 17 April 1978
citizen of Sweden
accepted on the recommendation of
Prof. Dr. Alexander J. McNeil, examiner
Prof. Dr. Peter L. Bühlmann, co-examiner
Prof. Dr. Philipp J. Schönbucher, co-examiner

This thesis addresses the challenge of dependence modelling in portfolio credit risk management, and provides a first application of Markov chain Monte Carlo (MCMC) methods for statistical inference in this field.

http://e-collection.library.ethz.ch/eserv/eth:28662/eth-28662-02.pdf

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