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Optimization Methods in Finance (Mathematics, Finance and Risk)
 
 
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Optimization Methods in Finance (Mathematics, Finance and Risk) (Hardcover)

by Gerard Cornuejols (Author), Reha Tutuncu (Author)
Key Phrases: robust feasible set, robust optimization models, conic optimization, Stocks Bonds, Ayk Ask, Composite Index (more...)
4.3 out of 5 stars  (3 customer reviews)

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Editorial Reviews

Review
"This book will be useful as a textbook for students in financial engineering at the MS level.... The book will also be of interest to researchers and graduate students in optimization who are interested in applications of optimization to financial problems."
Brian Borchers, Journal of Online Mathematics and its Applications

Product Description
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.

See all Editorial Reviews

Product Details

  • Hardcover: 358 pages
  • Publisher: Cambridge University Press (January 8, 2007)
  • Language: English
  • ISBN-10: 0521861705
  • ISBN-13: 978-0521861700
  • Product Dimensions: 9.8 x 7.1 x 0.9 inches
  • Shipping Weight: 1.7 pounds (View shipping rates and policies)
  • Average Customer Review: