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Local Risk-Minimization for Change Point Models Open Access


Other title
honest time
enlargement of filtration
local risk-minimization
change point
Type of item
Degree grantor
University of Alberta
Author or creator
Supervisor and department
Choulli, Tahir
Examining committee member and department
Frei, Christoph (Mathematical Finance and Stochastic Analysis)
Choulli, Tahir (Mathematical Finance and Stochastic Analysis)
Mizera, Ivan (Statistics)
Berger, Arno (Dynamical Systems and Probability Theory)
Pass, Brentan
Department of Mathematical and Statistical Sciences
Mathematical Finance
Date accepted
Graduation date
Master of Science
Degree level
he main aim of this thesis lies in describing, as explicit as possible, the local-risk minimizing strategy for a change-point model. To this end, we analyze and investigate the mathematical structures of this model. The change-point model is a model that starts with a dynamic and switches to another dynamic immediately at some random time. This random time can represents the time of occurrence of an event that may affect the market and/or agents, such as the default of a firm, a catastrophic event, sudden adjustment of fiscal policies, etc. The most interesting feature of this random time lies in the fact that its behavior might not be seen through the public flow of information. This feature obliges us to enlarge the flow of information to include this random time. For this context, we develop the local-risk minimization and describe the optimal strategy using the public information. As applications of these results, we address the hedging problem for default sensitive contingent claims.
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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File title: Introduction
File title: Local Risk-Minimization for Change point models
File author: Long Jiang
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