Numerical Methods and Optimization in Finance / Edition 2

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

Overview

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.

Product Details

ISBN-13:	9780128150658
Publisher:	Elsevier Science
Publication date:	08/16/2019
Edition description:	2nd ed.
Pages:	638
Product dimensions:	8.50(w) x 10.88(h) x (d)

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. Fundamentals2. Numerical Analysis in a Nutshell3. Linear Equations and Least Squares Problems4. Finite Difference Methods5. Binomial Trees

II. 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

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