Product Description

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.

Product Details

• Amazon Sales Rank: #380029 in Books
• Published on: 2008-03-04
• Original language: English
• Number of items: 1
• Binding: Hardcover
• 608 pages

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)

About the Author

Gianluca Fusai is Associate Professor in Financial Calculus at Università degli Studi del Piemonte Orientale (Italy) and a Research Associate at Financial Options Research Center, Univeristy of Warwick. He holds a Ph.D in Finance from the Warwick Business School and a MS in Statistics and Operational Research from University of Essex, UK. His research interest are Financial Engineering, Numerical Methods, Portfolio Selection, and Financial Statistics. On this topics he has published in journals like Journal of Computational Finance, Risk, Annals of Applied Probability, International Journal of Theoretical and Applied Finance. He has worked as a consultant in the private sector (Mediolanum Assicurazioni, Selenia Luxco, Nike Consulting, Software Company, Equitable House).

Andrea Roncoroni is Associate Professor of Finance at ESSEC Business School (Paris-Singapore), Senior Lecturer at Bocconi University (Milan), and Co-director of the Master in Energy Finance at MIP - Politecnico di Milano. He holds PhDs in Applied Mathematics and in Finance. His research interests cover Energy and Commodity Finance, Financial Modeling, Risk Management and Derivative Structuring. He consults for private companies and lectures for private and public institutions (International Energy Agency, Italian Stock Exchange, Italian Energy Authority, Italian Power Exchange, University Paris Dauphine, University of Oslo). He regularly publishes in academic journals (J.of Business, J.of Banking and Finance, Intl.J.of Business).

Customer Reviews

Great value for money
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.