- Tapa blanda: 352 páginas
- Editor: FE Press, LLC (24 de marzo de 2011)
- Colección: Financial Engineering Advanced Background Series
- Idioma: Inglés
- ISBN-10: 0979757622
- ISBN-13: 978-0979757624
- Valoración media de los clientes: Sé el primero en opinar sobre este producto
- Clasificación en los más vendidos de Amazon: nº136.765 en Libros en idiomas extranjeros (Ver el Top 100 en Libros en idiomas extranjeros)
A Primer For The Mathematics Of Financial Engineering, Second Edition (Financial Engineering Advanced Background Series) (Inglés) Tapa blanda – 24 mar 2011
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Reviews for “A Primer for the Mathematics of Financial Engineering”, First Edition:
``One of the hottest degrees on today's campus is a Masters in Financial Engineering. Whether you need to retrieve hallowed memories or just want to familiarize yourself with the mathematics underlying this degree, this unique book offers a terrific return on investment.”
--Peter Carr, PhD
Global Head of Modeling, Morgan Stanley; Director of the Masters Program in Mathematical Finance, Courant Institute, NYU
``This is the book I always recommend to people who ask about their mathematics before doing an MFE, and a few people could do with reading it after as well."
Director, P&D Quantitative Recruitment
NEW TOPICS: Dollar duration, Dollar convexity, DV01; the effect of parallel shifts in the yield curve to changes in bond yields; bond portfolio immunization; arbitraging the Put-Call parity; percentage vs. log returns for individual assets and portfolios; optimum investment portfolios: maximum return portfolios and minimum variance portfolios; the numerical precision of finite difference approximations of the Greeks.
New or expanded sections: new chapter on solving nonlinear problems; expanded Lagrange multipliers sections; streamlined Taylor series and Taylor expansion sections; Mathematical Appendix at the end of the book.
This book builds the solid mathematical foundation required to understand the quantitative models used in financial engineering. It contains 175 exercises, many of these being frequently asked interview questions. A Solutions Manual including detailed solutions to every exercise in the Primer was published by FE Press. International shipping and Errata at www.fepress.org
The First Edition of the Primer was warmly received by a large audience, including students and prospective students of financial engineering programs, academics teaching in such programs or in finance departments, and practitioners from the financial industry. The book proved to be very well suited for self-study, particularly with the addition of the Solutions Manual
Financial applications (selected): Put-Call parity, bond mathematics, numerical computation of bond yields, Black-Scholes model, numerical estimation for Greeks, implied volatility, yield curves bootstrapping
Mathematical topics (selected): numerical approximation of definite integrals; Taylor approximations and Taylor series expansions; finite difference approximations; Stirling's formula, polar coordinates; numerical methods for solving one dimensional problems; Newton's method for higher dimensional problems
Biografía del autor
Dan Stefanica has been the Director of the Baruch MFE Program since its inception in 2002, and is the author of the best-selling A Primer For The Mathematics Of Financial Engineering and A Linear Algebra Primer for Financial Engineering: Covariance Matrices, Eigenvectors, OLS, and more, and co-author of 150 Most Frequently Asked Questions on Quant Interviews. He teaches graduate courses on numerical methods for financial engineering, as well as pre-program courses on advanced calculus and numerical linear algebra with financial applications. His research spans numerical analysis, graph theory, and geophysical fluid dynamics. He has a PhD in mathematics from New York University and taught previously at the Massachusetts Institute of Technology.
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This book bridges a very important gap between math and finance, and that is from the pure theoretical math to applied finance. People do not realize that financial engineering employs some of the most advanced theories in both theoretical math and probility. Which is why Wall Street is looking for physicists and engineering students for quantative finance.
This is a great self study, or textbook which instructs the student how to apply their math background to finance. The author does an excellent job of teaching the math, while using financial engineering as the examples and problems. Which in the end takes you from basic Calculus to Taylor series and Lagrange.
Actually it would be a great way to teach calculus in the future. Instead of using theoretical physics and the sciences for examples and problems, simply use finance.
The psuedocode is just a bonus in my mind. This is an excellent math book for students, even if they are not planning on a future in financial engineering because it does illustrate applied math like no other textbook.
I originally used it while I was a student and nowadays as practitioner, it is my go-to book to refresh my memory for most of the covered topics.
Dan has a clean, easy to read, with full proof explanations and examples style, which helps the reader to quickly and rigorously understand the basic ideas and concepts.
The book contains a plethora of topics that any quant in finance will come across at some point. The selection helps the reader to gain a robust foundation before moving to more advance constructions (from integrals -> continuous probabilities -> risk neutral estimation and properties of Black-Scholes as well as other topics e.g. Taylor expansion, numerical methods, bond mathematics, portfolio construction, etc.).
I would highly recommend it.
It is not an undergraduate level calculus textbook as someone may think. This book emphasizes advanced calculus methods and math foundations with applications in the financial world. Thus, I would strongly recommend it to anyone who is interested in quantitative finance and needs to enhance their math knowledge towards that.
Specifically, there are five main aspects that highlight the book's value:
1. It covers the most important calculus and math foundations for quantitative analysis in solving financial problems. It goes from basic calculus, numerical integration and probability concepts to Newton's method, Taylor's formula, finite difference & ODEs, multivariate calculus and Lagrange multipliers. All math theorems/proofs/formulas are very clear and easy to follow.
2. It provides plenty of examples of real-world financial applications, such as options, put-call parity, Greeks and hedging, Black-Scholes PDE, and interest rates, Bonds, portfolio optimization. These practical problems are very common in the financial industry, and many of them have been frequently asked as interview questions for quant finance jobs.
3. It also provides many straightforward pseudocodes for implementing some programming algorithms, such as Simpson's numerical integration, Black-Scholes's option pricing model, computing implied vol, Newton's method, etc. No matter what programming language you use, it is very easy to implement following the pseudocodes. You will find how efficient it is.
4. It provides extensive practice exercises. I almost finished all exercise problems, some of them are theoretical, requiring derivations and proofs, and some are practical, requiring computation and programming. Very challenging but intellectually stimulating.
5. The book is well-organized and very easy to follow. Every chapter covers a major math topic with financial applications/examples. No need to worry if you don't have a finance background since all finance terminologies are well explained. Math notations are consistent and easy to understand and remember.
This book has been continuously ranked as one of the most famous quant finance books by QuantNet.com.
If you ask about what math background is required for a Master in Financial Engineering/Mathematical Finance program, the answer is always: read this book. If you want to review/refine/enhance your math knowledge for entering a MFE program, read this book.