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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.

Corporate finance --- Operational research. Game theory --- -Mathematical optimization --- Finance --- Mathematical optimization --- lineaire algebra --- lineaire programmering --- mathematische modellen, toegepast op economie --- stochastische processen --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Mathematical models --- Mathematical optimization. --- Finances --- Optimisation mathématique --- Mathematical models. --- Modèles mathématiques --- Finance - Mathematical models --- Mathematical Sciences --- General and Others

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Integer programming --- Combinatorial optimization --- Combinatorial optimization -- Congresses. --- Electronic books. -- local. --- Integer programming -- Congresses. --- Operations Research --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Mathematics. --- Computer programming. --- Algorithms. --- Computer science --- Probabilities. --- Discrete mathematics. --- Combinatorics. --- Discrete Mathematics. --- Probability Theory and Stochastic Processes. --- Programming Techniques. --- Algorithm Analysis and Problem Complexity. --- Discrete Mathematics in Computer Science. --- Combinatorics --- Algebra --- Mathematical analysis --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Probability --- Statistical inference --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk --- Algorism --- Arithmetic --- Computers --- Electronic computer programming --- Electronic digital computers --- Programming (Electronic computers) --- Coding theory --- Math --- Science --- Foundations --- Programming --- Programming (Mathematics) --- Distribution (Probability theory. --- Computer science. --- Computer software. --- Computational complexity. --- Complexity, Computational --- Machine theory --- Software, Computer --- Computer systems --- Informatics --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Computer science—Mathematics. --- Discrete mathematical structures --- Mathematical structures, Discrete --- Structures, Discrete mathematical --- Numerical analysis --- Integer programming - Congresses --- Combinatorial optimization - Congresses

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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.

Finance --- Mathematical optimization. --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Mathematical models.