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Optimization Methods in Finance

$72.00 USD

Part of Mathematics, Finance and Risk

  • Date Published: January 2007
  • availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
  • format: Adobe eBook Reader
  • isbn: 9780511258183

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About the Authors
  • 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.

    • The book is based on a successful Master's course at Carnegie Mellon University and comes with worked examples, exercises and case studies
    • Cutting edge material - chapters on conic and robust optimization are unique for any optimization text
    • Ideal for applied mathematicians, operational researchers and others working in mathematical and computational finance
    • The chapters alternate between operational research and financial applications, which is a unique approach
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    Reviews & endorsements

    '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

    'This book would certainly appeal to someone with a mathematical background, perhaps in operations research, wishing to update and apply their knowledge to the financial world.' Mathematics TODAY

    'Until now, there has been no comprehensive optimization book aimed at quantitative analysts in the financial industry. The book by Cornuejols and Tutuncu fills this void … an excellent source for quantitative financial analysts and graduate students to learn about basic optimization theory, computational methods, and available software. At the same time, it can be used by academic researchers and students in optimization as an introduction to various interesting problems in financial applications.' International Review of Economics & Finance

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    Product details

    • Date Published: January 2007
    • format: Adobe eBook Reader
    • isbn: 9780511258183
    • contains: 43 b/w illus. 44 tables 177 exercises
    • availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
  • Table of Contents

    1. Introduction
    2. Linear programming: theory and algorithms
    3. LP models: asset/liability cash flow matching
    4. LP models: asset pricing and arbitrage
    5. Nonlinear programming: theory and algorithms
    6. NLP volatility estimation
    7. Quadratic programming: theory and algorithms
    8. QP models: portfolio optimization
    9. Conic optimization tools
    10. Conic optimization models in finance
    11. Integer programming: theory and algorithms
    12. IP models: constructing an index fund
    13. Dynamic programming methods
    14. DP models: option pricing
    15. DP models: structuring asset backed securities
    16. Stochastic programming: theory and algorithms
    17. SP models: value-at-risk
    18. SP models: asset/liability management
    19. Robust optimization: theory and tools
    20. Robust optimization models in finance
    Appendix A. Convexity
    Appendix B. Cones
    Appendix C. A probability primer
    Appendix D. The revised simplex method

  • Instructors have used or reviewed this title for the following courses

    • Advanced Business Modeling
    • Asset Allocation
    • Linear Programming
    • Mathematical Modeling
    • Numerical Methods in Finance
    • Optimization Methods with Finance Applications
    • Optimization Models & Methods for Financial Engineering
    • Quantitative Methods for Finance
    • Readings: Optimization
  • Authors

    Gerard Cornuejols, Carnegie Mellon University, Pennsylvania
    Gerard Cornuejols is an IBM University Professor of Operations Research at theTepper School of Business, Carnegie Mellon University.

    Reha Tütüncü, Quantitative Resources Group, Goldman Sachs Asset Management, New York
    Reha Tütüncü is a Vice President in the Quantitative Resources Group at Goldman Sachs Asset Management, New York.

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