Numerical Methods and Optimization in Finance

This book describes computational finance tools. It covers fundamental numerical analysis and computational techniques, such as option pricing, and gives special attention to simulation and optimization. Many chapters are organized as case studies around portfolio insurance and risk estimation problems.  In particular, several chapters explain optimization heuristics and how to use them for portfolio selection and in calibration of estimation and option pricing models. Such practical examples allow readers to learn the steps for solving specific problems and apply these steps to others. At the same time, the applications are relevant enough to make the book a useful reference. Matlab and R sample code is provided in the text and can be downloaded from the book's website.



  • Shows ways to build and implement tools that help test ideas
  • Focuses on the application of heuristics; standard methods receive limited attention
  • Presents as separate chapters problems from portfolio optimization, estimation of econometric models, and calibration of option pricing models
1100088417
Numerical Methods and Optimization in Finance

This book describes computational finance tools. It covers fundamental numerical analysis and computational techniques, such as option pricing, and gives special attention to simulation and optimization. Many chapters are organized as case studies around portfolio insurance and risk estimation problems.  In particular, several chapters explain optimization heuristics and how to use them for portfolio selection and in calibration of estimation and option pricing models. Such practical examples allow readers to learn the steps for solving specific problems and apply these steps to others. At the same time, the applications are relevant enough to make the book a useful reference. Matlab and R sample code is provided in the text and can be downloaded from the book's website.



  • Shows ways to build and implement tools that help test ideas
  • Focuses on the application of heuristics; standard methods receive limited attention
  • Presents as separate chapters problems from portfolio optimization, estimation of econometric models, and calibration of option pricing models
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Overview

This book describes computational finance tools. It covers fundamental numerical analysis and computational techniques, such as option pricing, and gives special attention to simulation and optimization. Many chapters are organized as case studies around portfolio insurance and risk estimation problems.  In particular, several chapters explain optimization heuristics and how to use them for portfolio selection and in calibration of estimation and option pricing models. Such practical examples allow readers to learn the steps for solving specific problems and apply these steps to others. At the same time, the applications are relevant enough to make the book a useful reference. Matlab and R sample code is provided in the text and can be downloaded from the book's website.



  • Shows ways to build and implement tools that help test ideas
  • Focuses on the application of heuristics; standard methods receive limited attention
  • Presents as separate chapters problems from portfolio optimization, estimation of econometric models, and calibration of option pricing models

Product Details

ISBN-13: 9780123756633
Publisher: Elsevier Science & Technology Books
Publication date: 06/30/2011
Sold by: Barnes & Noble
Format: eBook
Pages: 600
File size: 19 MB
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About the Author

VIP Value Investment Professionals, Switzerland

Table of Contents

1. Introduction I. Fundamentals 2. Numerical Analysis in a Nutshell 3. Linear Equations and Least-Squares Problems 4. Finite Difference Methods 5. Binomial Trees II Simulation 6. Generating Random Numbers 7. Modelling Dependencies 8. A Gentle Introduction to Financial Simulation 9. Financial Simulation at Work:  Some Case Studies III Optimization 10. Optimization Problems in Finance 11. Basic Methods 12. Heuristic Methods in a Nutshell 13. Portfolio Optimization 14. Econometric Models 15. Calibrating Option Pricing Models

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Teaches ways to make applications into software and test them empirically

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