Numerical Methods and Optimization in Finance

by Manfred Gilli, Dietmar Maringer, Enrico Schumann BA in Economics and Law. MSC in Economics. Ph.D. in Econometrics.

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
Note:	This product may take a few minutes to download.

About the Author

Manfred Gilli is Professor emeritus at the Geneva School of Economics and Management at the University of Geneva, Switzerland, where he has taught numerical methods in economics and finance. He is also a Faculty member of the Swiss Finance Institute, a member of the Advisory Board of Computational Statistics and Data Analysis, and a member of the editorial board of Computational Economics. He formerly served as president of the Society for Computational Economics.Dietmar Maringer is Professor of Computational Economics and Finance at the University of Basel, Switzerland, and a faculty member at the Geneva School of Economics and Management. His research interests include non-deterministic methods such as heuristic optimization and simulations, computational learning, and empirical methods, typically with applications in trading, risk, and financial management.Enrico Schumann holds a Ph.D. in econometrics, an MSC in economics, and a BA in economics and law. He has written on numerical methods and their application in finance, with a focus on asset allocation. His research interests include quantitative investment strategies and portfolio construction, computationally-intensive methods (in particular, optimization), and automated data processing and analysis.

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

What People are Saying About This

From the Publisher

Teaches ways to make applications into software and test them empirically

Editorial Reviews

"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

From the Publisher