Implementing Models in Quantitative Finance: Methods and Cases (Springer Finance) [Hardcover]

Gianluca Fusai (Author), Andrea Roncoroni (Author)

Book Description

ISBN-10: 3540223487 | ISBN-13: 978-3540223481 | Publication Date: March 4, 2008 | Edition: 1

This book puts numerical methods in action for the purpose of solving practical problems in quantitative finance. The first part develops a toolkit in numerical methods for finance. The second part proposes twenty self-contained cases covering model simulation, asset pricing and hedging, risk management, statistical estimation and model calibration. Each case develops a detailed solution to a concrete problem arising in applied financial management and guides the user towards a computer implementation. The appendices contain "crash courses" in VBA and Matlab programming languages.

Editorial Reviews

Review

From the reviews: "As the title suggests the book is divided into two parts. … The style of the book is very inviting and it should be on the shelf of every serious researcher and practitioner in quantitative finance, including graduate students. Teachers could easily use the book in their applied courses. Overall, I think the book is a clear self-contained guide to implementing models in quantitative finance and as such it is going to be very popular in quant and academic circles." (Ita Cirovic Donev, MathDL, July, 2008) "This application-oriented book presents the major numerical methods currently used and describes how these methods can be used to solve problems in quantitative finance. … Each chapter includes exercises for student practice … . The presentation is at an intermediate-advanced level and serves as an introductory tutorial to the field of quantitative finance. Quantitative analysts, researchers and graduate students in quantitative finance will find this book useful." (Stefan Henn, Mathematical Reviews, Issue 2009 g)

From the Back Cover

This book puts numerical methods into action for the purpose of solving concrete problems arising in quantitative finance. Part one develops a comprehensive toolkit including Monte Carlo simulation, numerical schemes for partial differential equations, stochastic optimization in discrete time, copula functions, transform-based methods and quadrature techniques. The content originates from class notes written for courses on numerical methods for finance and exotic derivative pricing held by the authors at Bocconi University since the year 2000. Part two proposes eighteen self-contained cases covering model simulation, derivative valuation, dynamic hedging, portfolio selection, risk management, statistical estimation and model calibration. It encompasses a wide variety of problems arising in markets for equity, interest rates, credit risk, energy and exotic derivatives. Each case introduces a problem, develops a detailed solution and illustrates empirical results. Proposed algorithms are implemented using either Matlab® or Visual Basic for Applications® in collaboration with contributors.

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Product Details

• Hardcover: 631 pages
• Publisher: Springer; 1 edition (March 4, 2008)
• Language: English
• ISBN-10: 3540223487
• ISBN-13: 978-3540223481
• Product Dimensions: 9.4 x 6.3 x 1.1 inches
• Shipping Weight: 2.1 pounds (View shipping rates and policies)
• Average Customer Review: 4.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #897,711 in Books (See Top 100 in Books)

Customer Reviews

Most Helpful Customer Reviews

9 of 10 people found the following review helpful:

4.0 out of 5 stars Great value for money, October 26, 2009

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Governor (Sydney Australia) - See all my reviews

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This review is from: Implementing Models in Quantitative Finance: Methods and Cases (Springer Finance) (Hardcover)

The biggest problem with this book is the risk that it will be stolen.

Everyone in the commercial bank where I work seems interested in it. The coverage is extremely broad, but the exposition is patient and thorough. I have already used the book to great effect in validating a couple of exotic equity derivative pricing models, and it has inspired me to flesh out my understanding of some technical topics that I might otherwise have skipped. On the question of mathematical depth, I found the level about right, and I am more an apprentice rocket mechanic than 'rocket scientist'.

My only gripe (and it is a modest one) is that the book doesn't cover all the topics I would have liked. Some of the topics are a little too specific to certain asset classes. I would have preferred better coverage of some advanced topics in statistics that have generic applications across multiple classes.