Practical Financial Optimization
Decision Making for Financial Engineers
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This book gives a comprehensive account of financial optimization models used to support decision-making for financial engineers. It starts with the classical static mean-variance analysis and portfolio immunization, moves on to scenario-based models, and builds towards multi-period dynamic portfolio optimization.As the story unfolds, the relationships between classes of models are revealed. Once the foundations are laid with several building blocks and the broad landscape of financial optimization is charted, the book moves on to analyze several real-world applications. In this way the reader...
This book gives a comprehensive account of financial optimization models used to support decision-making for financial engineers. It starts with the classical static mean-variance analysis and portfolio immunization, moves on to scenario-based models, and builds towards multi-period dynamic portfolio optimization.
As the story unfolds, the relationships between classes of models are revealed. Once the foundations are laid with several building blocks and the broad landscape of financial optimization is charted, the book moves on to analyze several real-world applications. In this way the reader acquires not only solid knowledge of the foundations of financial optimization, but also a taste for the large-scale models that can be grounded on these foundations. The math prerequisite is optimization with matrix algebra.
As the story unfolds, the relationships between classes of models are revealed. Once the foundations are laid with several building blocks and the broad landscape of financial optimization is charted, the book moves on to analyze several real-world applications. In this way the reader acquires not only solid knowledge of the foundations of financial optimization, but also a taste for the large-scale models that can be grounded on these foundations. The math prerequisite is optimization with matrix algebra.
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