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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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- Series:
**Mathematics, finance, and risk** - Author:
**Gerard Cornuejols, Reha Tutuncu,** - Year:
**2007** - Publisher:
**Cambridge University Press** - Language:
**English** - ISBN:
**0511261284,9780521861700,0521861705,9780511261282**

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**1 605 964** - Format:
**pdf**

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This volume presents a collection of contributions dedicated to applied problems in the financial and energy sectors that have been formulated and solved in a stochastic optimization framework. The invited authors represent a group of scientists and pract...

Biologically inspired optimization methods constitute a rapidly expanding field of research, with new applications appearing on an almost daily basis, as optimization problems of ever-increasing complexity appear in science and technology. This book provi...

One of the major goals of geophysical inversion is to find earth models that explain the geophysical observations. Thus the branch of mathematics known as optimization has found significant use in many geophysical applications.Both local and global optimi...

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Features optimization problems that in practice involve random model parameters Provides applications from the fields of robust optimal control / design in case of stochastic uncertainty Includes numerous references to stochastic optimization, stochasti...

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