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Computationally-intensive tools play an increasingly important role in financial decisions. Many financial problems—ranging from asset allocation to risk management and from op… Read more
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Immediately download your ebook while waiting for your print delivery. No promo code needed.
Computationally-intensive tools play an increasingly important role in financial decisions. Many financial problems—ranging from asset allocation to risk management and from option pricing to model calibration—can be efficiently handled using modern computational techniques. Numerical Methods and Optimization in Finance presents such computational techniques, with an emphasis on simulation and optimization, particularly so-called heuristics. This book treats quantitative analysis as an essentially computational discipline in which applications are put into software form and tested empirically.
This revised edition includes two new chapters, a self-contained tutorial on implementing and using heuristics, and an explanation of software used for testing portfolio-selection models. Postgraduate students, researchers in programs on quantitative and computational finance, and practitioners in banks and other financial companies can benefit from this second edition of Numerical Methods and Optimization in Finance.
Students (Master or PhD level) and researchers in programs on quantitative and computational finance, and also practitioners in banks and other financial companies
1. Introduction
I. Fundamentals
2. Numerical Analysis in a Nutshell3. Linear Equations and Least Squares Problems4. Finite Difference Methods5. Binomial TreesII. Simulation6. Generating Random Numbers7. Modeling Dependencies8. A Gentle Introduction to Financial Simulation9. Financial Simulation at Work: Some Case Studies
III. Optimization10. Optimization Problems in Finance11. Basic Methods12. Heuristic Methods in a Nutshell13.: Heuristic Methods: A Tutorial14. Portfolio Optimization15. Backtesting Investment Strategies16. Econometric Models17. Calibrating Option Pricing Models
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