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Simulation and Optimization in Finance: Modeling with MATLAB, @Risk, or VBA Hardcover – Oct 5 2010
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From the Inside Flap
In recent years, there has been a notable increase in the use of simulation and optimization methods in risk management, portfolio allocation, asset pricing, derivatives pricing, and capital budgeting under uncertainty.
With Simulation and Optimization in Finance and its companion Web site, authors Dessislava Pachamanova and Frank Fabozzi explain the application of these tools for both financial professionals and academics in this field.
Divided into five comprehensive parts, this reliable guide provides an accessible introduction to the simulation and optimization techniques most widely used in finance, while offering fundamental background information on the financial concepts surrounding these techniques.
In addition, the authors use simulation and optimization as a means to clarify difficult concepts in traditional risk models in finance, and explain how to build financial models with certain software. They review current simulation and optimization methodologies—along with the available software—and proceed with portfolio risk management, modeling of random processes, pricing of financial derivatives, and capital budgeting applications.
Designed for practitioners and students, this book:
Contains a unique combination of finance theory and rigorous mathematical modeling emphasizing a hands-on approach through implementation with software
Highlights both classical applications and more recent developments such as pricing of mortgage-backed securities
Includes models and code in both spreadsheet-based software (@RISK, Solver, and VBA) and mathematical modeling software (MATLAB)
Incorporates a companion Web site containing ancillary materials, including the models and code used in the book, appendices with introductions to the software, and practice sections
And much more
Filled with in-depth insights and practical advice, Simulation and Optimization in Finance offers essential guidance on some of the most important topics in financial management.
From the Back Cover
Engaging and accessible, this book and its companion Web site provide an introduction to the simulation and optimization techniques most widely used in finance, while, at the same time, offering essential information on the financial concepts surrounding these applications.
This practical guide is divided into five informative parts:
Part I, Fundamental Concepts, provides insights on the most important issues in finance, simulation, optimization, and optimization under uncertainty
Part II, Portfolio Optimization and Risk Measures, reviews the theory and practice of equity and fixed income portfolio management, from classical frameworks to recent advances in the theory of risk measurement
Part III, Asset Pricing Models, discusses classical static and dynamic models for asset pricing, such as factor models and different types of random walks
Part IV, Derivative Pricing and Use, introduces important types of financial derivatives, shows how their value can be determined by simulation, and discusses how derivatives can be employed for portfolio risk management and return enhancement purposes
Part V, Capital Budgeting Decisions, reviews capital budgeting decision models, including real options, and discusses applications of simulation and optimization in capital budgeting under uncertainty
Supplemented with models and code in both spreadsheet-based software (@RISK, Solver, and VBA) and mathematical modeling software (MATLAB), Simulation and Optimization in Finance is a well-rounded guide to a dynamic discipline.See all Product Description
Inside This Book(Learn More)
Most Helpful Customer Reviews on Amazon.com (beta)
This book has the optimal combination of theory and practice. It starts out with a through introduction to statistics, finance and optimization concepts. In the second part, the book describes portfolio optimization theory and applications in equity and fixed income markets. The third part focuses on asset pricing models discussing classical and dynamic models. The fourth section mainly focuses on derivative pricing and provides a very good introduction to Monte-Carlo simulation methods. Topics of current interest such as pricing MBS products are also described in this section. Part five focuses on capital budget decisions and has a very good introduction to real options. The Software hints in each chapter and the supplementary materials on the website help students and practitioners to immediately try out examples and fortify their knowledge.
Prof.Pachamanova's didactic approach and the vast coverage of topics makes this book a must have for new quantitative analysts, business students and engineers interested in a career in finance. As a Financial Modeling consultant who works at MathWorks (the maker of MATLAB), I get a lot of questions on recommendations for books to apply financial theory using computational tools. This book is a gem and would makes great addition to your quantitative investing library.
Full Disclosure: I took a Statistics class with Prof.Pachamanova during my MBA program at Babson College
Each theme is treated with superficiality. More properly this book is an introduction.