Simulation and Optimization in Finance + Website
Modeling with MATLAB, @Risk, or VBA
Published on 22. October 2010
Book
Hardback
896 pages
978-0-470-37189-3 (ISBN)
Description
An introduction to the theory and practice of financial simulation and optimization
In recent years, there has been a notable increase in the use of simulation and optimization methods in the financial industry. Applications include portfolio allocation, risk management, pricing, and capital budgeting under uncertainty.
This accessible guide provides an introduction to the simulation and optimization techniques most widely used in finance, while at the same time offering background on the financial concepts in these applications. In addition, it clarifies difficult concepts in traditional models of uncertainty in finance, and teaches you how to build models with software. It does this by reviewing current simulation and optimization methodology-along with available software-and proceeds with portfolio risk management, modeling of random processes, pricing of financial derivatives, and real options applications.
* Contains a unique combination of finance theory and rigorous mathematical modeling emphasizing a hands-on approach through implementation with software
* Highlights not only classical applications, but also more recent developments, such as pricing of mortgage-backed securities
* Includes models and code in both spreadsheet-based software (@RISK, Solver, Evolver, VBA) and mathematical modeling software (MATLAB)
Filled with in-depth insights and practical advice, Simulation and Optimization Modeling in Finance offers essential guidance on some of the most important topics in financial management.
In recent years, there has been a notable increase in the use of simulation and optimization methods in the financial industry. Applications include portfolio allocation, risk management, pricing, and capital budgeting under uncertainty.
This accessible guide provides an introduction to the simulation and optimization techniques most widely used in finance, while at the same time offering background on the financial concepts in these applications. In addition, it clarifies difficult concepts in traditional models of uncertainty in finance, and teaches you how to build models with software. It does this by reviewing current simulation and optimization methodology-along with available software-and proceeds with portfolio risk management, modeling of random processes, pricing of financial derivatives, and real options applications.
* Contains a unique combination of finance theory and rigorous mathematical modeling emphasizing a hands-on approach through implementation with software
* Highlights not only classical applications, but also more recent developments, such as pricing of mortgage-backed securities
* Includes models and code in both spreadsheet-based software (@RISK, Solver, Evolver, VBA) and mathematical modeling software (MATLAB)
Filled with in-depth insights and practical advice, Simulation and Optimization Modeling in Finance offers essential guidance on some of the most important topics in financial management.
More details
Series
Edition
1. Auflage
Language
English
Place of publication
Chichester
United Kingdom
Publishing group
John Wiley and Sons Ltd
Target group
Professional and scholarly
Illustrations
Illustrations
Dimensions
Height: 23.3 cm
Width: 16.3 cm
Thickness: 4.1 cm
Weight
1120 gr
ISBN-13
978-0-470-37189-3 (9780470371893)
Schweitzer Classification
Persons
DESSISLAVA A. PACHAMANOVA, PhD, is an Associate Professor of Operations Research at Babson College where she holds the Zwerling Term Chair. She has published a number of articles in operations research, finance, and engineering journals, and co-authored the Wiley title Robust Portfolio Optimization and Management. Pachamanova's academic research is supplemented by consulting and previous work in the financial industry, including projects with quantitative strategy groups at WestLB and Goldman Sachs. She holds an AB in mathematics from Princeton University and a PhD in operations research from the Sloan School of Management at MIT.
Frank J. Fabozzi, PhD, CFA, CPA, is Professor in the Practice of Finance and Becton Fellow at theYale School of Management and Editor of the Journal of Portfolio Management. He is an Affiliated Professor at the University of Karlsruhe's Institute of Statistics, Econometrics, and Mathematical Finance and is on the Advisory Council for the Department of Operations Research and Financial Engineering at Princeton University. He earned a doctorate in economics from the City University of New York.
Frank J. Fabozzi, PhD, CFA, CPA, is Professor in the Practice of Finance and Becton Fellow at theYale School of Management and Editor of the Journal of Portfolio Management. He is an Affiliated Professor at the University of Karlsruhe's Institute of Statistics, Econometrics, and Mathematical Finance and is on the Advisory Council for the Department of Operations Research and Financial Engineering at Princeton University. He earned a doctorate in economics from the City University of New York.
Content
Preface.
Chapter 1: Introduction.
PART ONE: Fundamental Concepts.
Chapter 2: Important Finance Concepts.
Chapter 3: Random Variables, Probability Distributions, and Important Statistical Concepts.
Chapter 4: Simulation Modeling and Software.
Chapter 5: Optimization Modeling.
Chapter 6: Optimization under Uncertainty.
PART TWO: Portfolio Optimization and Risk Measures.
Chapter 7: Asset Diversification and Efficient Frontiers.
Chapter 8: Advances in the Theory of Risk Measures.
Chapter 9: Equity Portfolio Management in Practice.
Chapter 10: Fixed Income Portfolio Management in Practice.
PART THREE: Asset Pricing Models.
Chapter 11: Regression and Factor Models.
Chapter 12: Modeling Asset Price Dynamics.
PART FOUR: Derivative Pricing and Use.
Chapter 13: Introduction to Derivatives.
Chapter 14: Pricing Derivatives by Simulation.
Chapter 15: Structuring and Pricing Residential Mortgage-Backed Securities.
Chapter 16: Using Derivatives in Portfolio Management.
PART FIVE: Capital Budgeting Decisions.
Chapter 17: Capital budgeting under uncertainty.
Chapter 18: Real options.
REFERENCES.
INDEX.
Chapter 1: Introduction.
PART ONE: Fundamental Concepts.
Chapter 2: Important Finance Concepts.
Chapter 3: Random Variables, Probability Distributions, and Important Statistical Concepts.
Chapter 4: Simulation Modeling and Software.
Chapter 5: Optimization Modeling.
Chapter 6: Optimization under Uncertainty.
PART TWO: Portfolio Optimization and Risk Measures.
Chapter 7: Asset Diversification and Efficient Frontiers.
Chapter 8: Advances in the Theory of Risk Measures.
Chapter 9: Equity Portfolio Management in Practice.
Chapter 10: Fixed Income Portfolio Management in Practice.
PART THREE: Asset Pricing Models.
Chapter 11: Regression and Factor Models.
Chapter 12: Modeling Asset Price Dynamics.
PART FOUR: Derivative Pricing and Use.
Chapter 13: Introduction to Derivatives.
Chapter 14: Pricing Derivatives by Simulation.
Chapter 15: Structuring and Pricing Residential Mortgage-Backed Securities.
Chapter 16: Using Derivatives in Portfolio Management.
PART FIVE: Capital Budgeting Decisions.
Chapter 17: Capital budgeting under uncertainty.
Chapter 18: Real options.
REFERENCES.
INDEX.