Numerical Methods and Optimization in Finance
Autor Manfred Gilli, Dietmar Maringer, Enrico Schumannen Limba Engleză Hardback – 24 aug 2011
- 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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Specificații
ISBN-13: 9780123756626
ISBN-10: 0123756626
Pagini: 600
Ilustrații: Illustrations
Dimensiuni: 152 x 229 x 28 mm
Greutate: 0.93 kg
Editura: ELSEVIER SCIENCE
ISBN-10: 0123756626
Pagini: 600
Ilustrații: Illustrations
Dimensiuni: 152 x 229 x 28 mm
Greutate: 0.93 kg
Editura: ELSEVIER SCIENCE
Public țintă
Graduate students studying quantitative or computational finance, as well as finance professionals, especially in banking and insuranceCuprins
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
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
Recenzii
"This book aims at providing guidance which is practical and useful for practitioners in finance with emphasis on computational techniques which are manageable by modern day desktop personal computers’ processing power when building, testing, comparing and using mathematical and econometric models of finance in the pursuit of analysis of actual financial market data in day to day activities of financial analysts, be they students of courses in finance programs or analysts in financial institutions." --Zentralblatt MATH 2012-1236-91001
"With as much rigor as can be mastered by anyone in the still-developing field of computational finance and a sense of humor, the authors unravel its mysteries. The presentations are clear and the models are practical --- these are the two ingredients that make for a valuable book in this field. The book is both practical in scope and rigorous on its theoretical foundations. It is a must for anyone who needs to apply quantitative methods for financial planning --- and who doesn’t need to in our days?" --Stavros A. Zenios, University of Cyprus and the Wharton Financial Institutions Center
"Numerical Methods and Optimization in Finance is an excellent introduction to computational science. The combination of methodology, software, and examples allows the reader to quickly grasp and apply serious computational ideas." --Kenneth L. Judd, Hoover Institution, Stanford University
"With as much rigor as can be mastered by anyone in the still-developing field of computational finance and a sense of humor, the authors unravel its mysteries. The presentations are clear and the models are practical --- these are the two ingredients that make for a valuable book in this field. The book is both practical in scope and rigorous on its theoretical foundations. It is a must for anyone who needs to apply quantitative methods for financial planning --- and who doesn’t need to in our days?" --Stavros A. Zenios, University of Cyprus and the Wharton Financial Institutions Center
"Numerical Methods and Optimization in Finance is an excellent introduction to computational science. The combination of methodology, software, and examples allows the reader to quickly grasp and apply serious computational ideas." --Kenneth L. Judd, Hoover Institution, Stanford University