Numerical Methods and Optimization in Finance

AvManfred Gilli,Dietmar Maringer

Häftad, Engelska, 2019

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Beskrivning

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.

Introduces numerical methods to readers with economics backgrounds
Emphasizes core simulation and optimization problems
Includes MATLAB and R code for all applications, with sample code in the text and freely available for download

Produktinformation

Utgivningsdatum:2019-08-16
Mått:216 x 276 x 33 mm
Vikt:1 700 g
Format:Häftad
Språk:Engelska
Antal sidor:638
Upplaga:2
Förlag:Elsevier Science
ISBN:9780128150658

Utforska kategorier

Mikroekonomi inom Ekonomi och Ledarskap
Optimering inom Naturvetenskap och teknik
Finansiering inom Ekonomi och Ledarskap

Mer om författaren

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.

Innehållsförteckning

1. IntroductionI. Fundamentals2. Numerical Analysis in a Nutshell3. Linear Equations and Least Squares Problems4. Finite Difference Methods5. Binomial TreesII. Simulation6. Generating Random Numbers7. Modeling Dependencies8. A Gentle Introduction to Financial Simulation9. Financial Simulation at Work: Some Case StudiesIII. 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