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A balanced introduction to the theoretical foundations and real-world applications of mathematical finance
The ever-growing use of derivative products makes it essential for financial industry practitioners to have a solid understanding of derivative pricing. To cope with the growing complexity, narrowing margins, and shortening life-cycle of the individual derivative product, an efficient, yet modular, implementation of the pricing algorithms is necessary. Mathematical Finance is the first book to harmonize the theory, modeling, and implementation of today's most prevalent pricing models under one convenient cover. Building a bridge from academia to practice, this self-contained text applies theoretical concepts to real-world examples and introduces state-of-the-art, object-oriented programming techniques that equip the reader with the conceptual and illustrative tools needed to understand and develop successful derivative pricing models.
Utilizing almost twenty years of academic and industry experience, the author discusses the mathematical concepts that are the foundation of commonly used derivative pricing models, and insightful Motivation and Interpretation sections for each concept are presented to further illustrate the relationship between theory and practice. In-depth coverage of the common characteristics found amongst successful pricing models are provided in addition to key techniques and tips for the construction of these models. The opportunity to interactively explore the book's principal ideas and methodologies is made possible via a related Web site that features interactive Java experiments and exercises.
While a high standard of mathematical precision is retained, Mathematical Finance emphasizes practical motivations, interpretations, and results and is an excellent textbook for students in mathematical finance, computational finance, and derivative pricing courses at the upper undergraduate or beginning graduate level. It also serves as a valuable reference for professionals in the banking, insurance, and asset management industries.
- Sales Rank: #1796572 in Books
- Published on: 2007-08-24
- Original language: English
- Number of items: 1
- Dimensions: 9.23" h x 1.53" w x 6.44" l, 1.94 pounds
- Binding: Hardcover
- 544 pages
Review
"…very useful to practitioners and students…" (MAA Reviews, December 26, 2007)
"An excellent textbook for students in mathematical finance, computational finance, and derivative pricing courses at the upper undergraduate or beginning graduate level." (Mathematical Reviews 2007)
From the Back Cover
A balanced introduction to the theoretical foundations and real-world applications of mathematical finance
The ever-growing use of derivative products makes it essential for financial industry practitioners to have a solid understanding of derivative pricing. To cope with the growing complexity, narrowing margins, and shortening life-cycle of the individual derivative product, an efficient, yet modular, implementation of the pricing algorithms is necessary. Mathematical Finance is the first book to harmonize the theory, modeling, and implementation of today's most prevalent pricing models under one convenient cover. Building a bridge from academia to practice, this self-contained text applies theoretical concepts to real-world examples and introduces state-of-the-art, object-oriented programming techniques that equip the reader with the conceptual and illustrative tools needed to understand and develop successful derivative pricing models.
Utilizing almost twenty years of academic and industry experience, the author discusses the mathematical concepts that are the foundation of commonly used derivative pricing models, and insightful Motivation and Interpretation sections for each concept are presented to further illustrate the relationship between theory and practice. In-depth coverage of the common characteristics found amongst successful pricing models are provided in addition to key techniques and tips for the construction of these models. The opportunity to interactively explore the book's principal ideas and methodologies is made possible via a related Web site that features interactive Java experiments and exercises.
While a high standard of mathematical precision is retained, Mathematical Finance emphasizes practical motivations, interpretations, and results and is an excellent textbook for students in mathematical finance, computational finance, and derivative pricing courses at the upper undergraduate or beginning graduate level. It also serves as a valuable reference for professionals in the banking, insurance, and asset management industries.
About the Author
Christian Fries, PhD, is Lecturer of Mathematical Finance at the University of Frankfurt and head of financial model development at DZ Bank AG Frankfurt, both located in Germany. With extensive knowledge in various programming languages, Dr. Fries has conducted quantitative analysis and overseen the implementation of mathematical modeling platforms at numerous financial institutions. His research interests within the field of mathematical finance include the LIBOR Market Model, Efficient Calculation of Risk Measures with Monte-Carlo Methods, Pricing of Bermudan Options with Monte-Carlo Methods, and Markov Functional Models.
Most helpful customer reviews
9 of 11 people found the following review helpful.
An excellent quant book
By The Wizard
The book starts with discussing basic mathematical finance such as Ito's lemma and Black-Scholes theory. This is a rather compact summary without proofs and I therefore believe a novice reader first should read an introductory book such as the one by Baxter & Rennie. The main part of the books is then devoted to various issues that one encounters in the implementation of financial models. I found this part very useful and I guess most quants have encountered the interesting problems that the author discusses such as: calculation of greeks in Monte-Carlo implementations, backward pricing of path-dependent products, implementation of Markov models, etc.
6 of 8 people found the following review helpful.
This book is unbelievable precious
By Igor Cakulev
The book has so many nuggets of wisdom is hard to mention them all. I know I struggled with some concepts before and somehow they were explained in a remarkable way. So now I am just asking myself, was I so stupid before?
Perfect for practitioners, but not in the sense of generic cookbook like the Hull's book where the math is dangerously simplified.
The theory is explained with flawless clarity. Numerous tricks are given for free. For example, I always looked at interpolation as something trivial, however Fries explains arbitrage violations using different interpolation, i.e. negative probability density for smoothing interpolations, discrete for linear. This book is especially useful for somebody that is interested in Libor Market Model. There is also extension of it like the cross-currency version of it; I haven't seen it anywhere else (at least not in books).
From the negative side, I only wished more code posted, but that is just me being greedy. Given the amount spent on implementation issues, I would also like to see little bit more on calibration.
6 of 8 people found the following review helpful.
A nice path through Mathematical Finance
By M. Paulsen
The subtitle of this book is Theory, Modeling and Implementation and this book has plenty of material on all these areas of Mathematical Finance. The author, who has a solid background in mathematics and is a succesful professional in the finance industry, is very generous with the tricks of the trade. To my knowledge, there is no other book who takes the reader (preferably someone with a good working knowledge in university mathematics) on a path from the mathematics of Itô calculus to models of volatility and interest rate derivatives and then to numerics and object oriented programming. For a commited reader this book will be very rewarding, since it has so much to offer. It should be excellent preparation for e.g. an internship in a quantitative team at a bank (especially for derivatives) or could serve as course literature for a university course in applied financial modeling (the examples from industry will motivate the students, believe me). All in all, this is an excellently versatile book with such a richness concerning the material.
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