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A Primer For The Mathematics Of Financial Engineering, Second Edition (Financial Engineering Advanced Background Series), by Dan Stefanica
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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."
--Dominic Connor
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
- Sales Rank: #87588 in Books
- Published on: 2011-03-24
- Original language: English
- Number of items: 1
- Dimensions: 9.00" h x .80" w x 6.00" l,
- Binding: Paperback
- 352 pages
About the Author
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.
Most helpful customer reviews
17 of 17 people found the following review helpful.
Great book for any student
By Marc
First, primer means you have to have the fundamental math out of the way before you dive into this book. If you are fuzzy about what integration means, or the basic form of differentation then start with Calculus first. Though I think the author does a great job of teaching Calculus in this book.
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.
4 of 4 people found the following review helpful.
Comprehensive primer
By J. Watson
I read the first couple of chapters a couple of times to get my head around the math I haven't used for a while. It's a little easier together with Mathematica and another head-hurting book "Computational Financial Mathematics using Mathematica." It still hurts, but it's a good hurt.
29 of 31 people found the following review helpful.
A Unique Blend of Finance Concepts and Mathematical Foundation: A Must Read for Students contemplating an MFE Degree
By Devdeep Sarkar
Are you contemplating an MFE and/or MS in Math/Computational Finance Degree and asking yourself whether you have the right background?
I strongly believe that "A Primer for the Mathematics of Financial Engineering" by Prof. Dan Stefanica will take you through every step toward finding the Best answer. It will also help you start your journey as an MFE student with utmost confidence. This book is a must for all prospective students for an MFE (or equivalent) degree.
What I like the most about this book is the way the chapters are structured. Every chapter consists of two main parts. The first part deals with the basic mathematical foundation and/or numerical techniques required to understand a given subtopic of quantitative finance. Once the mathematical/numerical basis is set up, Prof. Stefanica moves on to describing how it can be applied to comprehend a specific set of topics in quantitative finance in the second part of each chapter.
Even if your math is not super strong to begin with, or you have not had much exposure to numerical techniques, you can easily master your skills while you are studying the first part of every chapter. And immediately following that, you see the application of the abstract mathematical concepts in the finance world. And then you can sharpen your skills much further by actually solving the stimulating questions/problems found at the end of each chapter.
Another thing I love about this book is the set of pseudo-codes. After describing the numerical techniques, be it Simpson's rules for numerical integration or Secant method for solving 1-D nonlinear problems, the author provides pseudo-codes showing practical examples of their implementation. You can easily translate these pseudo-codes to your favorite language (C++, Matlab, etc.) and start producing results immediately.
I hope you will enjoy studying the topics presented in this book... like I did.
Good Luck!
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