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Numerical Methods and Optimization in Finance

  • Livre Relié
  • 584 Nombre de pages
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This book describes computational finance tools. It covers fundamental numerical analysis and computational techniques, such as op... Lire la suite
CHF 118.00
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Description

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 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

Auteur

University of Geneva, Switzerland



Texte du rabat

This textbook teaches readers steps for solving specific problems in finance and applying them to other problems. After a short introduction about numerical analysis, the authors devote two sections to pricing financial models and simulation to prepare readers for the book s core subject, optimization. Assuming that a model is only as good as its results, they provide a comprehensive overview and treatment of heuristic optimization techniques, only briefly touching upon standard methods. Arguing against judging models by the elegance of their math or whether it fits nicely into a theoretical framework, they advocate a pragmatic approach: implementing models to gain intuition about them. They provide sample code in the text, primarily MatLab and R and offer code for download at the book s website. This practical textbook can serve equally well as a self-contained desk reference.



Résumé
Describes computational finance tools. This title covers fundamental numerical analysis and computational techniques, such as option pricing, and gives special attention to simulation and optimization. It shows ways to build and implement tools that help test ideas. It focuses on the application of heuristics.

Contenu
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 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

Informations sur le produit

Titre: Numerical Methods and Optimization in Finance
Auteur:
Code EAN: 9780123756626
ISBN: 978-0-12-375662-6
Format: Livre Relié
Editeur: Academic Pr Inc
Genre: Généralités et lexiques
nombre de pages: 584
Poids: 926g
Taille: H234mm x B159mm x T28mm
Année: 2011