Optimization methods play a central role in financial modeling. This textbook is devoted to explaining how state-of-the-art optimization theory, algorithms, and software can be used to efficiently solve problems in computational finance. It discusses some classical mean-variance portfolio optimization models as well as more modern developments such as models for optimal trade execution and dynamic portfolio allocation with transaction costs and taxes. Chapters discussing the theory and efficient solution methods for the main classes of optimization problems alternate with chapters discussing their use in the modeling and solution of central problems in mathematical finance. This book will be interesting and useful for students, academics, and practitioners with a background in mathematics, operations research, or financial engineering. The second edition includes new examples and exercises as well as a more detailed discussion of mean-variance optimization, multi-period models, and additional material to highlight the relevance to finance.
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This is a thorough treatment of optimization techniques that solve central challenges in finance. It gives a complete picture of model formulation, gathering relevant data, and computational implementation for each problem discussed. Theory and practical applications are woven together and enriched with worked examples, exercises, and case studies.
Gérard Cornuéjols is a Professor of Operations Research at the Tepper School of Business, Carnegie Mellon University, Pennsylvania. He is a member of the National Academy of Engineering and has received numerous prizes for his research contributions in integer programming and combinatorial optimization, including the Lanchester Prize, the Fulkerson Prize, the Dantzig Prize, and the von Neumann Theory Prize.
Javier Peña is a Professor of Operations Research at the Tepper School of Business, Carnegie Mellon University, Pennsylvania. His research explores the myriad of challenges associated with large-scale optimization models and he has published numerous articles on optimization, machine learning, financial engineering, and computational game theory. His research has been supported by grants from the National Science Foundation, including a prestigious CAREER award.
Reha Tütüncü is the Chief Risk Officer at SECOR Asset Management and an adjunct professor at Carnegie Mellon University, Pennsylvania. He has previously held senior positions at Goldman Sachs Asset Management and AQR Capital Management focusing on quantitative portfolio construction, equity portfolio management, and risk management.
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Gebunden. Condition: Sehr gut. Gebraucht - Sehr gut Leichte Lagerspuren -Optimization methods play a central role in financial modeling. This textbook is devoted to explaining how state-of-the-art optimization theory, algorithms, and software can be used to efficiently solve problems in computational finance. It discusses some classical mean-variance portfolio optimization models as well as more modern developments such as models for optimal trade execution and dynamic portfolio allocation with transaction costs and taxes. Chapters discussing the theory and efficient solution methods for the main classes of optimization problems alternate with chapters discussing their use in the modeling and solution of central problems in mathematical finance. This book will be interesting and useful for students, academics, and practitioners with a background in mathematics, operations research, or financial engineering. The second edition includes new examples and exercises as well as a more detailed discussion of mean-variance optimization, multi-period models, and additional material to highlight the relevance to finance. 350 pp. Englisch. Seller Inventory # INF1001423398
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Hardcover. Condition: new. Hardcover. Optimization methods play a central role in financial modeling. This textbook is devoted to explaining how state-of-the-art optimization theory, algorithms, and software can be used to efficiently solve problems in computational finance. It discusses some classical meanvariance portfolio optimization models as well as more modern developments such as models for optimal trade execution and dynamic portfolio allocation with transaction costs and taxes. Chapters discussing the theory and efficient solution methods for the main classes of optimization problems alternate with chapters discussing their use in the modeling and solution of central problems in mathematical finance. This book will be interesting and useful for students, academics, and practitioners with a background in mathematics, operations research, or financial engineering. The second edition includes new examples and exercises as well as a more detailed discussion of meanvariance optimization, multi-period models, and additional material to highlight the relevance to finance. This is a thorough treatment of optimization techniques that solve central challenges in finance. It gives a complete picture of model formulation, gathering relevant data, and computational implementation for each problem discussed. Theory and practical applications are woven together and enriched with worked examples, exercises, and case studies. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781107056749
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