Optimization models play an increasingly important role in
financial decisions. This is the first textbook devoted to
explaining how recent advances in optimization models, methods and
software can be applied to solve problems in computational finance
more efficiently and accurately. Chapters discussing the theory and
efficient solution methods for all major classes of optimization
problems alternate with chapters illustrating their use in modeling
problems of mathematical finance. The reader is guided through
topics such as volatility estimation, portfolio optimization
problems and constructing an index fund, using techniques such as
nonlinear optimization models, quadratic programming formulations
and integer programming models respectively. The book is based on
Master's courses in financial engineering and comes with worked
examples, exercises and case studies. It will be welcomed by
applied mathematicians, operational researchers and others who work
in mathematical and computational finance and who are seeking a
text for self-learning or for use with courses.
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