Our list of some of the best Financial Engineering books & series in recent years. Get inspired by one or more of the following books.
- 1. A Primer For The Mathematics Of Financial Engineering, Second Edition (Financial Engineering Advanced Background Series) (2011)
- 2. Mathematics for Finance: An Introduction to Financial Engineering (Springer Undergraduate Mathematics Series) (2010)
- 3. A Linear Algebra Primer for Financial Engineering: Covariance Matrices, Eigenvectors, OLS, and more (Financial Engineering Advanced Background Series) (2014)
- 4. Practical Methods of Financial Engineering and Risk Management: Tools for Modern Financial Professionals (2014)
- 5. Solutions Manual – A Primer For The Mathematics Of Financial Engineering, Second Edition (2011)
- 6. Solutions Manual – A Linear Algebra Primer for Financial Engineering (Financial Engineering Advanced Background Series) (Volume 4) (2016)
- 7. An Introduction to Quantitative Finance (2013)
- 8. Algorithmic Trading with Interactive Brokers (Python and C++) (2019)
- 9. Quantitative Financial Analytics: The Path To Investment Profits (2017)
- 10. Statistics and Data Analysis for Financial Engineering: with R examples (Springer Texts in Statistics) (2016)
- 11. Clinical Engineering Financial Management and Benchmarking: Essential tools to manage finances and remain competitive for clinical engineering/healthcare technology management professionals (2018)
- 12. Financial Engineering: Derivatives and Risk Management (2001)
- 13. Machine Learning For Financial Engineering (2012)
1. A Primer For The Mathematics Of Financial Engineering, Second Edition (Financial Engineering Advanced Background Series) (2011)
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…
2. Mathematics for Finance: An Introduction to Financial Engineering (Springer Undergraduate Mathematics Series) (2010)
As with the first edition, Mathematics for Finance: An Introduction to Financial Engineering combines financial motivation with mathematical style. Assuming only basic knowledge of probability and calculus, it presents three major areas of mathematical finance, namely Option pricing based on the no-arbitrage principle in discrete and continuous time setting, Markowitz portfolio optimisation and Capital Asset Pricing Model, and basic stochastic interest rate models in discrete setting. From the reviews of the first edition: “This text is an excellent introduction to Mathematical…
3. A Linear Algebra Primer for Financial Engineering: Covariance Matrices, Eigenvectors, OLS, and more (Financial Engineering Advanced Background Series) (2014)
This book covers linear algebra methods for financial engineering applications from a numerical point of view. The book contains many such applications, as well as pseudocodes, numerical examples, and questions often asked in interviews for quantitative positions. • The Arrow—Debreu one period market model • One period index options arbitrage • Covariance and correlation matrix estimation from time series data • Ordinary least squares for implied volatility computation • Minimum variance portfolios and maximum return portfolios • Value at…
4. Practical Methods of Financial Engineering and Risk Management: Tools for Modern Financial Professionals (2014)
Risk control, capital allocation, and realistic derivative pricing and hedging are critical concerns for major financial institutions and individual traders alike. Events from the collapse of Lehman Brothers to the Greek sovereign debt crisis demonstrate the urgent and abiding need for statistical tools adequate to measure and anticipate the amplitude of potential swings in the financial markets—from ordinary stock price and interest rate moves, to defaults, to those increasingly frequent “rare events” fashionably called black swan events. Yet many on Wall Street continue to rely on standard models based on…
5. Solutions Manual – A Primer For The Mathematics Of Financial Engineering, Second Edition (2011)
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…
6. Solutions Manual – A Linear Algebra Primer for Financial Engineering (Financial Engineering Advanced Background Series) (Volume 4) (2016)
Every exercise from the book “A Linear Algebra Primer for Financial Engineering“ is solved in detail in the Solutions Manual. The addition of this Solutions Manual offers the reader the opportunity of rigorous self-study of the linear algebra concepts presented in the NLA Primer, and of achieving a deeper understanding of the financial engineering applications therein. • The Arrow—Debreu one period market model • One period index options arbitrage • Covariance and correlation matrix estimation from time series data • Ordinary least squares for implied…
7. An Introduction to Quantitative Finance (2013)
The worlds of Wall Street and The City have always held a certain allure, but in recent years have left an indelible mark on the wider public consciousness and there has been a need to become more financially literate. The quantitative nature of complex financial transactions makes them a fascinating subject area for mathematicians of all types, whether for general interest or because of the enormous monetary rewards on offer. An Introduction to Quantitative Finance concerns financial derivatives a derivative being a contract between two entities whose…
8. Algorithmic Trading with Interactive Brokers (Python and C++) (2019)
Through Interactive Brokers, software developers can write applications that read financial data, scan for contracts, and submit orders automatically. Individuals can now take advantage of the same high-speed decision making and order placement that professional trading firms use.This book walks through the process of developing applications based on IB’s Trader Workstation (TWS) programming interface. Beginning chapters introduce the fundamental classes and functions, while later chapters show how they can be used to implement full-scale…
9. Quantitative Financial Analytics: The Path To Investment Profits (2017)
This book provides a comprehensive treatment of the important aspects of investment theory, security analysis, and portfolio selection, with a quantitative emphasis not to be found in most other investment texts. The statistical analysis framework of markets and institutions in the book meets the need for advanced undergraduates and graduate students in quantitative disciplines, who wish to apply their craft to the world of investments. In addition, entrepreneurs will find the volume to be especially useful. It also contains a clearly detailed explanation of many recent…
10. Statistics and Data Analysis for Financial Engineering: with R examples (Springer Texts in Statistics) (2016)
The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of…
11. Clinical Engineering Financial Management and Benchmarking: Essential tools to manage finances and remain competitive for clinical engineering/healthcare technology management professionals (2018)
This book provides the fundamental concepts and tools needed by Clinical Engineering (CE), also known as Health Technology Management (HTM), managers to properly manage their financial resources, as well as to prove to their senior leaders that they are comparing (benchmarking) well against their peers. After introducing basic accounting concepts and tools using a case study based on real data, different methods for financing the CE/HTM department are explored. Next, opportunities for improving financial performance are explained through analyses of budget, costs and productivity….
12. Financial Engineering: Derivatives and Risk Management (2001)
This text provides a thorough treatment of futures, ‘plain vanilla’ options and swaps as well as the use of exotic derivatives and interest rate options for speculation and hedging. Pricing of options using numerical methods such as lattices (BOPM), Mone Carlo simulation and finite difference methods, in additon to solutions using continuous time mathematics, are also covered. Real options theory and its use in investment appraisal and in valuing internet and biotechnology companies provide cutting edge practical applications. Practical risk management issues are examined in depth. Alternative…
13. Machine Learning For Financial Engineering (2012)
This volume investigates algorithmic methods based on machine learning in order to design sequential investment strategies for financial markets. Such sequential investment strategies use information collected from the market’s past and determine, at the beginning of a trading period, a portfolio; that is, a way to invest the currently available capital among the assets that are available for purchase or investment. The aim is to produce a self-contained text intended for a wide audience, including researchers and graduate students in computer science, finance, statistics, mathematics, and engineering….
Best Financial Engineering Books Worth Your Attention
We highly recommend you to buy all paper or e-books in a legal way, for example, on Amazon. But sometimes it might be a need to dig deeper beyond the shiny book cover. Before making a purchase, you can visit resources like Genesis and download some financial engineering books mentioned below at your own risk. Once again, we do not host any illegal or copyrighted files, but simply give our visitors a choice and hope they will make a wise decision.
Quantitative Management of Bond Portfolios
Author(s): Lev Dynkin, Anthony Gould, Jay Hyman, Vadim Konstantinovsky, Bruce Phelps
ID: 2536330, Publisher: Princeton University Press, Year: 2020, Size: 6 Mb, Format: pdf
Univariate Stable Distributions: Models for Heavy Tailed Data
Author(s): John P. Nolan
ID: 2861601, Publisher: Springer, Year: 2020, Size: 10 Mb, Format: pdf
Heavy-Tailed Time Series
Author(s): Rafal Kulik, Philippe Soulier
ID: 2876829, Publisher: Springer New York;Springer, Year: 2020, Size: 9 Mb, Format: pdf
Please note that this booklist is not definite. Some books are truly best-sellers according to Washington Post, others are written by unknown authors. On top of that, you can always find additional tutorials and courses on Coursera, Udemy or edX, for example. Are there any other relevant books you could recommend? Leave a comment if you have any feedback on the list.