What are the best books on quantitative finance?
Out of the 25 best quantitative finance programs in the world, four universities posted their suggested reading lists online.
Those four were:
- Boston University
- Carnegie Mellon
- Columbia University
- University of Waterloo
The books that made at least two of the reading lists included:
- Advanced Modeling in Finance Using Excel and VBA by Mary Jackson and Mike Staunton
- Options, Futures and Other Derivatives by John C. Hull
- Stochastic Processes by Sheldon Ross
- The Complete Guide to Capital Markets for Quantitative Professionals by Alex Kuznetsov
- When Genius Failed: The Rise and Fall of LTCM by Roger Lowenstein
If you’re looking for the best books on quantitative finance, these five options are a great start.
Want to dive deeper?
See each reading list in its entirety below. Or, check out which investing books were most recommended by today’s top investors.
Note: While there are differences between the terms quantitative finance, computational finance, mathematical finance and financial engineering, for this article the terms were combined.
For each recommendation below, I’ve included a link to the book’s page on Amazon. If you click through and make a purchase, The Ways To Wealth receives a small commission.
Carnegie Mellon Quantitative Finance Reading List
Regarded as one of the top computational finance programs, Carnegie Mellon recommends the following books for students wanting to learn more about the subject.
- Corporate Finance by J. Berk and P. DeMarzo
- The Complete Guide to Capital Markets for Quantitative Professionals by Alex Kuznetsov
- Options, Futures and Other Derivatives by John C. Hull
Columbia University Financial Engineering Reading List
Ranked second on Quantnet’s list of top financial engineering programs, the recommended reading list for incoming students was recently posted on the Quantnet forums.
General Background
- A Demon of Our Own Design: Markets, Hedge Funds, and the Perils of Financial Innovation by Richard Bookstaber
- Capital Ideas by Peter L. Bernstein
- My Life as a Quant by Emanuel Derman
- The Complete Guide to Capital Markets for Quantitative Professionals by Alex Kuznetsov
- When Genius Failed: The Rise and Fall of LTCM by Roger Lowenstein
Quantitative Background
- A Primer for the Mathematics of Financial Engineering by Dan Stefanica
- Investments by W. F. Sharpe, G. J. Alexander and J. V. Bailey
- The Mathematics of Derivatives: Tools for Designing Numerical Algorithms by Robert L. Navin
Miscellaneous Books On Quantitative Methods
- Advanced Modeling in Finance Using Excel and VBA by Mary Jackson and Mike Staunton
- A First Course in Stochastic Processes by Karlin and Taylor
- Introduction to Probability Models by Sheldon Ross
- Modern Applied Statistics with S-Plus by W. N. Venables, Brian D. Ripley
- Monte Carlo Methods in Financial Engineering by Paul Glasserman
- Simulation by Sheldon M. Ross
- Stochastic Calculus and Financial Applications by J. Michael Steele
- Stochastic Processes by Sheldon Ross
- The Econometrics of Financial Markets by John Y. Campbell, Andrew W. Lo and A. Craig MacKinlay
- C++ Language Tutorial
Boston University Quantitative Finance Reading List
Ranked 12th on Quantnet, incoming students are suggested to read the following books.
General Background
- Options, Futures and Other Derivatives by John C. Hull
- Principles of Financial Engineering by Saleh Neftci
APPLIED MATHEMATICS
- Black Scholes and Beyond by Neil Chriss
- Stochastic Calculus for Finance I: The Binomial Asset Pricing Model by Steven Shreve
- Stochastic Calculus for Finance II: Continuous-Time Models by Steven Shreve
COMPUTER SCIENCE
- Financial Engineering and Computation by Yuh-Dauh Lyuu
- R Cookbook by Paul Teetor
University of Waterloo Quantitative Finance Reading List
Ranked #14 on Quantnet, University of Waterloo lists the following books as recommended reading for prospective students.
Finance
- An Introduction to Mathematical Finance: Options and Other Topics by Sheldon M. Ross
- Derivatives: The Tools that Changed Finance by Phelim P. Boyle and Feidhlim P. Boyle
- Investment Science by David G. Luenberger
- Options, Futures and Other Derivatives by John C. Hull
Probability and Statistics
- Introduction to Mathematical Statistics by Robert Hogg and Allen Craig (Chapters 1-6)
- Stochastic Processes by Sheldon Ross (Chapters 4-6)
Econometrics
- Econometric Analysis by William H. Greene
Real Analysis
- Principles of Mathematical Analysis by W. Rudin (Chapters 1-7)
- Real Analysis by H. Royden and P. Fitzpatrick
Calculus
- Calculus by J. Stewart
Linear Algebra
- Linear Algebra, Mat Labs by T. Lawson
C++
- Accelerated C++: Practical Programming by Example by A. Koenig and B. Moo
- C++: A Beginner’s Guide by H. Schildt
- Effective C++: 55 Specific Ways to Improve Your Programs and Designs by S. Meyers
- Sams Teach Yourself C++ in One Hour a Day by J. Liberty and R. Cadenhead
Python
- Learning Python by M. Lutz
- Programming Python by M. Lutz
- Python Cookbook by D. Beazley and B. K. Jones
- Think Python by Allen B. Downey
MATLAB
- Matlab, Third Edition: A Practical Introduction to Programming and Problem Solving by Stormy Attaway
- Numerical Methods in Finance and Economics: A MATLAB-Based Introduction by Paolo Brandimarte
- Simulation and Optimization in Finance: Modeling with MATLAB, @Risk, or VBA by D. Pachamanova and F. J. Fabozzi
- Stochastic Simulation and Applications in Finance with MATLAB Programs by H. T. Huynh, V. S. Lai and I. Soumare
R
- A Beginner’s Guide to R by A. F. Zuur, E. N. Ieno, and E. Meesters
- Data Manipulation with R by P. Spector
- Introductory Statistics with R by P. Dalgaard
- Introductory Time Series with R by P.S.P. Cowpertwait and A.V. Metcalfe
Excel/VBA
- Advanced Modeling in Finance Using Excel and VBA by Mary Jackson and Mike Staunton
- Credit Risk Modeling using Excel and VBA by G. Löeffler and P. N. Posch
- Excel 2010 Power Programming with VBA by J. Walkenbach
- Next Generation Excel: Modeling in Excel for Analysts and MBAs (For MS Windows and Mac OS) by I. Gottlieb
- Option Pricing Models and Volatility Using Excel-VBA (text only) by F. D. Rouah and G. Vainberg
General Readings in Finance
- How I Became a Quant: Insights from 25 of Wall Street’s Elite by R. Lindsey and B. Schachter
- Liar’s Poker by M. Lewis
- Models Behaving Badly: Why Confusing Illusion with Reality Can Lead to Disaster, on Wall Street and in Life by E. Derman
- The Big Short: Inside the Doomsday Machine by M. Lewis
- When Genius Failed: The Rise and Fall of LTCM by Roger Lowenstein
Interview Preparation Readings
- A Practical Guide To Quantitative Finance Interviews by X. Zhou
- Cracking the Coding Interview: 150 Programming Questions and Solutions by G. McDowell
- Frequently Asked Questions in Quantitative Finance by P. Wilmott
- Heard on the Street: Quantitative Questions from Wall Street Job Interviews by T. Crack
- Quant Job Interview Questions and Answers by M. Joshi, N. Denson and A. Downes
- Starting Your Career as a Wall Street Quant: A Practical, No-Bs Guide to Getting a Job in Quantitative Finance by B. Jiu
Further Reading
If you’re interested in reading business and investing books from outside the field of quantitative finance, check out the following lists:
- The best investing books for beginners to learn the stock market
- The best business books of all time
- The best investing books of all time
- Elon Musk’s recommended reading list
- Howard Marks’ recommended reading list
- Joel Greenblatt’s recommended reading list
- Michael Burry’s recommended reading list
- Nassim Taleb’s recommended reading list
- Warren Buffett’s recommended reading list
