Quant Finance Reading List
April 25, 2013 Leave a comment
QUANTITATIVE FINANCE READING LIST
This is the big one! I’ve tried to list as many great quantitative finance books as I can. The lists cover general quant finance, careers guides, interview prep, quant trading, mathematics, numerical methods and programming in C++, Python, Excel, MatLab and R. If you have any suggestions for more books, please contact me at mike@quantstart.com and I’ll get them added.
This list was last updated on 8th April 2013.
General Quant Finance Reading
One area that routinely catches out prospective quants at interview is their lack of basic financial markets knowledge. It’s all well and good being the best mathematician and programmer on the globe, but if you can’t tell your stock from your bond, or your bank from your fund, you’ll find it a lot harder to pass those HR screenings.
These books also make much better bedtime reading than graduate texts on stochastic calculus…
The Big Short: Inside the Doomsday Machine – Michael Lewis
Liar’s Poker – Michael Lewis
When Genius Failed: The Rise and Fall of Long-Term Capital Management – Roger Lowenstein
More Money Than God: Hedge Funds and the Making of a New Elite (Council on Foreign Relations Books (Penguin Press)) – Sebastian Mallaby
How I Became a Quant: Insights from 25 of Wall Street’s Elite – Richard Lindsey, Barry Schachter
My Life as a Quant: Reflections on Physics and Finance – Emanuel Derman
Financial Engineering: The Evolution of a Profession (Robert W. Kolb Series) – Tanya Beder, Cara Marshall
The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It – Scott Patterson
Nerds on Wall Street: Math, Machines and Wired Markets – David Leinweber
Physicists on Wall Street and Other Essays on Science and Society – Jeremey Bernstein
The Complete Guide to Capital Markets for Quantitative Professionals (McGraw-Hill Library of Investment and Finance) – Alex Kuznetsov
Models.Behaving.Badly.: Why Confusing Illusion with Reality Can Lead to Disaster, on Wall Street and in Life – Emanuel DermanInterview Preparation
On top of needing to be aware of capital markets and how they function, the mathematics of derivatives pricing and quantitative trading methods, being able to program in C++ and possibly Python, you also need to study how to ace that quant interview!
The following books are fantastic resources for getting you prepared. Make sure you study not only the content of the brainteasers, but also try deconstructing how they’re put together and what you’re really being asked.
Heard on The Street: Quantitative Questions from Wall Street Job Interviews – Timothy Crack
Frequently Asked Questions in Quantitative Finance – Paul Wilmott
Quant Job Interview Questions And Answers – Mark Joshi, Nick Denson, Andrew Downes
A Practical Guide To Quantitative Finance Interviews – Xinfeng Zhou
Cracking the Coding Interview: 150 Programming Questions and Solutions – Gayle McDowell
Quantitative/High-Frequency Trading
The career paths for quants have shifted recently towards direct quantitative trading and away from derivatives pricing.
Although Black-Scholes theory is still immensely important for hedging and exotic option pricing purposes, it is now necessary to be intimately familiar with systematic trading and the firms that employ it.
It is difficult to get hold of information from funds about their trading strategies (no surprise there!), but these books provide an in-depth overview into how the “black box” operates.
Inside the Black Box: The Simple Truth About Quantitative Trading (Wiley Finance) – Rishi Narang
Quantitative Trading: How to Build Your Own Algorithmic Trading Business (Wiley Trading) – Ernie Chan
Trading Systems: A New Approach to System Development and Portfolio Optimisation – Emilio Tomasini, Urban Jaekle
All About High-Frequency Trading (All About Series) – Michael Durbin
Quantitative Trading and Money Management, Revised Edition – Fred Gehm
Algorithmic Trading and DMA: An introduction to direct access trading strategies – Barry Johnson
Dynamic Hedging: Managing Vanilla and Exotic Options – Nassim Nicholas Taleb
Option Volatility & Pricing: Advanced Trading Strategies and Techniques – Sheldon Natenberg
Volatility Trading – Euan Sinclair
Mathematical Finance
This would more accurately be described as financial engineering as the books listed below relate to derivatives pricing theory.
Although you don’t need to read every book below, they are all good. Each provides a different perspective or emphasis on options pricing theory.
If you know you are definitely going to become a derivatives pricing quant then you should aim to study as many books from the following list as possible.
Options, Futures, and Other Derivatives and DerivaGem CD Package (8th Edition) – John Hull
A Primer For The Mathematics Of Financial Engineering, Second Edition – Dan Stefanica
Solutions Manual – A Primer For The Mathematics Of Financial Engineering, Second Edition – Dan Stefanica
Paul Wilmott Introduces Quantitative Finance (The Wiley Finance Series) – Paul Wilmott
Paul Wilmott on Quantitative Finance 3 Volume Set (2nd Edition) – Paul Wilmott
The Concepts and Practice of Mathematical Finance (Mathematics, Finance and Risk) – Mark Joshi
More mathematical finance – Mark Joshi
Financial Calculus: An Introduction to Derivative Pricing – Martin Baxter, Andrew Rennie
An Introduction to the Mathematics of Financial Derivatives, Second Edition (Academic Press Advanced Finance) – Salih Neftci
Principles of Financial Engineering, Second Edition (Academic Press Advanced Finance) – Salih Neftci
Mathematics for Finance: An Introduction to Financial Engineering (Springer Undergraduate Mathematics Series) – Marek Capiski, Tomasz Zastawniak
Arbitrage Theory in Continuous Time (Oxford Finance) – Tomas Bjork
The Complete Guide to Option Pricing Formulas – Espen Haug
Interest Rate Derivatives
Interest Rate Models – Theory and Practice: With Smile, Inflation and Credit (Springer Finance) – Damiano Brigo, Fabio Mercurio
Interest Rate Modeling. Volume 1: Foundations and Vanilla Models – Leif B.G. Andersen, Vladimir V. Piterbarg
Interest Rate Modeling. Volume 2: Term Structure Models – Leif B.G. Andersen, Vladimir V. Piterbarg
Interest Rate Modeling. Volume 3: Products and Risk Management – Leif B.G. Andersen, Vladimir V. Piterbarg
The SABR/LIBOR Market Model: Pricing, Calibration and Hedging for Complex Interest-Rate Derivatives – Riccardo Rebonato, Kenneth McKay, Richard White
Discounting, Libor, CVA and Funding: Interest Rate and Credit Pricing (Applied Quantitative Finance)– Chris Kenyon, Roland Stamm
Interest Rate Swaps and Their Derivatives: A Practitioner’s Guide (Wiley Finance) – Amir Sadr
Term-Structure Models: A Graduate Course (Springer Finance / Springer Finance Textbooks) – Damir Filipovic
C++
C++ is one of the hardest areas for beginning quants to get to grips with.
Since it is such a large programming language, and may in fact be a quant’s first taste of programming, it can be extremely daunting.
The first five books on the list, if understood properly, would make you a competent C++ programmer. By reading the remainder, you will become an expert and probably the best in your peer group.
Sams Teach Yourself C++ in One Hour a Day (7th Edition) – Jesse Liberty, Rogers Cadenhead
C++: A Beginner’s Guide, Second Edition – Herbert Schildt
Accelerated C++: Practical Programming by Example – Andrew Koenig, Barbara Moo
Introduction to C++ for Financial Engineers: An Object-Oriented Approach (The Wiley Finance Series)– Daniel Duffy
Effective C++: 55 Specific Ways to Improve Your Programs and Designs (3rd Edition) – Scott Meyers
More Effective C++: 35 New Ways to Improve Your Programs and Designs – Scott Meyers
Exceptional C++: 47 Engineering Puzzles, Programming Problems, and Solutions – Herb Sutter
More Exceptional C++: 40 New Engineering Puzzles, Programming Problems, and Solutions – Herb Sutter
Exceptional C++ Style: 40 New Engineering Puzzles, Programming Problems, and Solutions – Herb Sutter
C++ Coding Standards: 101 Rules, Guidelines, and Best Practices – Herb Sutter, Andrei Alexandrescu
API Design for C++ – Martin Reddy
Effective STL: 50 Specific Ways to Improve Your Use of the Standard Template Library – Scott Meyers
The C++ Standard Library: A Tutorial and Reference (2nd Edition) – Nicolai Josuttis
C++ Templates: The Complete Guide – David Vandevoorde, Nicolai Josuttis
Modern C++ Design: Generic Programming and Design Patterns Applied – Andrei Alexandrescu
C++ Template Metaprogramming: Concepts, Tools, and Techniques from Boost and Beyond – David Abrahams, Aleksey Gurtovoy
The Boost C++ Libraries – Boris Schäling
Beyond the C++ Standard Library: An Introduction to Boost – Björn Karlsson
Introduction to the Boost C++ Libraries; Volume I – Foundations – Robert Demming, Daniel Duffy
Introduction to the Boost C++ Libraries; Volume II – Advanced Libraries – Robert Demming, Daniel Duffy
C++ Concurrency in Action: Practical Multithreading – Anthony Williams
Programming with POSIX Threads – David Butenhof
Advanced Linux Programming – Mark Mitchell, Alex Samuel, Jeffrey Oldham
Advanced Programming in the UNIX Environment (2nd Edition) – W. Richard Stevens, Stephen Rago
Advanced UNIX Programming (2nd Edition) – Marc Rochkind
Design Patterns: Elements of Reusable Object-Oriented Software – Erich Gamma, Richard Helm, Ralph Johnson, John Vlissides
Head First Design Patterns – Elisabeth Freeman, Eric Freeman, Bert Bates, Kathy Sierra, Elisabeth Robson
The C++ Programming Language, 4th Edition – Bjarne Stroustrup
C++: The Complete Reference, 4th Edition – Herbert Schildt
C++ Pocket Reference – Kyle Loudon
STL Pocket Reference (Pocket Reference (O’Reilly)) – Ray Lischner
C++ Cookbook (Cookbooks (O’Reilly)) – D. Ryan Stephens, Christopher Diggins, Jonathan Turkanis, Jeff Cogswell
Python
In recent years Python has rapidly become a staple in the quantitative finance world.
I personally know of many funds that employ it as the end-to-end computational infrastructure for carrying out systematic trading.
It is an easy language to learn, but it is harder to master, because it has many useful libraries. Regardless of which type of quant you wish to become, I would suggest learning Python, as it is only going to become more widely adopted as time goes on.
Learning Python: Powerful Object-Oriented Programming – Mark Lutz
Programming Python – Mark Lutz
Python Cookbook – Alex Martelli, Anna Ravenscroft, David Ascher
Think Python – Allen B. Downey
Python for Data Analysis – Wes McKinney
Beginning Python: From Novice to Professional – Magnus Lie Hetland
Python Programming for the Absolute Beginner, 3rd Edition – Michael Dawson
More Python Programming for the Absolute Beginner – Jonathan S. Harbour
Python Programming: An Introduction to Computer Science 2nd Edition – John Zelle
Python Algorithms: Mastering Basic Algorithms in the Python Language – Magnus Lie Hetland
Foundations of Python Network Programming – John Goerzan, Brandon Rhodes
Beginning Python Visualization: Crafting Visual Transformation Scripts – Shai Vaingast
Pro Python System Administration – Rytis Sileika
Python 3 Object Oriented Programming – Dusty Phillips
Learn Python the Hard Way – Zed Shaw
MySQL for Python – Albert Lukaszewski
Python Testing: Beginner’s Guide – Daniel Arbuckle
Python Testing Cookbook – Greg L. Turnquist
Python Essential Reference (4th Edition) – David M. Beazley
The Python Standard Library by Example – Doug Hellmann
Foundations of Agile Python Development – Jeff Younker
MATLAB
Although Python is rapidly gaining ground in the hedge fund space, many exceptional individuals were trained up on MatLab in academia and took that expertise to the financial markets. You will still see a substantial usage of MatLab within funds.
If you have been applying for jobs with MatLab in the job description, the following books will help you impress your interviwer.
Matlab, Second Edition: A Practical Introduction to Programming and Problem Solving – Stormy Attaway
Numerical Methods in Finance and Economics: A MATLAB-Based Introduction – Paolo Brandimarte
Stochastic Simulation and Applications in Finance with MATLAB Programs – Huu Tue Huynh, Van Son Lai, Issouf Soumare
Simulation and Optimization in Finance + Website: Modeling with MATLAB, @Risk, or VBA – Dessislava Pachamanova, Frank J. Fabozzi
Numerical Methods with MATLAB – Amos Gilat, Vish Subramaniam
The Mathematics of Derivatives Securities with Applications in MATLAB – Mario Cerrato
Financial Modelling: Theory, Implementation and Practice with MATLAB Source – Joerg Kienitz, Daniel Wetterau
MATLAB: An Introduction with Applications – Amos Gilat
Getting Started with MATLAB: A Quick Introduction for Scientists and Engineers – Rudra Pratap
An Engineers Guide to MATLAB (3rd Edition) – Edward B. Magrab, Shapour Azarm, Balakumar Balachandran, James Duncan, Keith Herold, Gregory Walsh
Modeling Derivatives Applications in Matlab, C++, and Excel – Justin London
Financial Risk Forecasting: The Theory and Practice of Forecasting Market Risk with Implementation in R and Matlab – Jon Danielsson
R
As with MatLab, R is extensively used within systematic funds as it is a natural language with which to carry out advanced statistical analysis.
A great way to learn R is to pair the following books with an online course in statistics (which will often make use of R anyway). This will really help you get to grips with the methods of quantitative trading.
A Beginner’s Guide to R – Alain F. Zuur, Elena N. Ieno, Erik Meesters
Introductory Statistics with R – Peter Dalgaard
Introductory Time Series with R – Paul S.P. Cowpertwait, Andrew V. Metcalfe
Data Manipulation with R – Phil Spector
Data Mining with R: Learning with Case Studies – Luis Torgo
R in Action – Robert Kabacoff
R in a Nutshell – Joseph Adler
The Art of R Programming: A Tour of Statistical Software Design – Norman Matloff
R Graphics, Second Edition – Paul Murrell
An R Companion to Applied Regression – An R Companion to Applied Regression
R Cookbook – Paul Teetor
The R Book – Michael J. Crawley
The Essential R Reference – Mark Gardener
R Graphics Cookbook – Winston Chang
Excel/VBA
Although not possessing the computational horsepower of C++ or Python, Excel is probably the mostwidely used software in the financial world.
If you are working on an investment banking prop trading desk as a quant, you will almost certainly be asked to implement functions in Excel for the traders at some stage. Having a working knowledge of Excel prior to interview will give you yet another edge over your peers when applying for that exciting quant role.
Advanced modelling in finance using Excel and VBA – Mary Jackson, Mike Staunton
Excel 2010 Power Programming with VBA – John Walkenbach
Credit Risk Modeling using Excel and VBA – Gunter Löeffler, Peter N. Posch
Next Generation Excel: Modeling in Excel for Analysts and MBAs – Isaac Gottlieb
Financial Analysis and Modeling Using Excel and VBA – Chandan Sengupta
Microsoft Excel for Stock and Option Traders: Build Your Own Analytical Tools for Higher Returns – Jeff Augen
Financial Modelling in Practice: A Concise Guide for Intermediate and Advanced Level – Michael Rees
Option Pricing Models and Volatility Using Excel-VBA – Fabrice Douglas Rouah, Gregory Vainberg
Professional Financial Computing Using Excel and VBA – Donny C. F. Lai, Humphrey K. K. Tung, Michael C. S. Wong, Stephen Ng
Implementing Models of Financial Derivatives, with CD-ROM: Object Oriented Applications with VBA – Nick Webber
Phew! That was quite an extensive list. Congratulations if you have made it this far…
Please send me any suggestions of great quant books you’ve read that have helped you on your way. I am always willing to add more to this list. You can contact me by sending an email tomike@quantstart.com.
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