Quant Finance Reading List

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

Starting Your Career as a Wall Street Quant: A Practical, No-BS Guide to Getting a Job in Quantitative Finance – Brett Jiu

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.

About bambooinnovator
Kee Koon Boon (“KB”) is the co-founder and director of HERO Investment Management which provides specialized fund management and investment advisory services to the ARCHEA Asia HERO Innovators Fund (www.heroinnovator.com), the only Asian SMID-cap tech-focused fund in the industry. KB is an internationally featured investor rooted in the principles of value investing for over a decade as a fund manager and analyst in the Asian capital markets who started his career at a boutique hedge fund in Singapore where he was with the firm since 2002 and was also part of the core investment committee in significantly outperforming the index in the 10-year-plus-old flagship Asian fund. He was also the portfolio manager for Asia-Pacific equities at Korea’s largest mutual fund company. Prior to setting up the H.E.R.O. Innovators Fund, KB was the Chief Investment Officer & CEO of a Singapore Registered Fund Management Company (RFMC) where he is responsible for listed Asian equity investments. KB had taught accounting at the Singapore Management University (SMU) as a faculty member and also pioneered the 15-week course on Accounting Fraud in Asia as an official module at SMU. KB remains grateful and honored to be invited by Singapore’s financial regulator Monetary Authority of Singapore (MAS) to present to their top management team about implementing a world’s first fact-based forward-looking fraud detection framework to bring about benefits for the capital markets in Singapore and for the public and investment community. KB also served the community in sharing his insights in writing articles about value investing and corporate governance in the media that include Business Times, Straits Times, Jakarta Post, Manual of Ideas, Investopedia, TedXWallStreet. He had also presented in top investment, banking and finance conferences in America, Italy, Sydney, Cape Town, HK, China. He has trained CEOs, entrepreneurs, CFOs, management executives in business strategy & business model innovation in Singapore, HK and China.

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