Recommended
Books on Quantitative Finance
Whilst like any author, I recommend my own books, there are certainly
many other books which you will need to read in order to master
quantitative finance. Here I try to catalogue and discuss the ones that
I regard as essential reading. The list has been kept small as
possible, since I do
not wish to overwhelm the prospective reader. (If you wish me
to include your book, send me a copy and I'll consider it. If I get
enough free books, I'll start a separate review section.)
I have now created a books
forum; the idea is to provide a place for those doing
self-study to discuss details in quantitative finance books. So if you
are stuck or confused by some detail that's the place to ask.
My books
Introductory analysis
Probability Theory and Stochastic
Processes
Basic mathematical finance
(except my books...)
Medium mathematical finance
Interest rate modelling
Credit Derivatives
Numerical Techniques
C++
C++ and quant finance
My books
My philosophy on writing books is to write the book that I wish someone
had given me when I was learning the subject. My book "The Concepts and
Practice of Mathematical Finance" aims to do that for the
person I was when I was getting my first quant job and learning
mathematical finance. It should probably have been called "The Concepts
and Practice of Financial Engineering" as the emphasis is more on
applications than dry theory, although the theory is certainly included.
My second book is the book I wanted to read on C++: "C++ design patterns
and derivatives pricing." Its objective is to teach the
reader C++ design using examples from quantitative finance. The target
reader is the wannabe quant who knows how to program procedurally, and
knows basic C++ syntax, but doesn't really get all this object-oriented
stuff.
With Nick Denson and Andrew Downes, I have written the book "Quant Job Interview
Questions and Answers." We gathered questions from many banks
over several years from lots of job candidates and distilled them into
a book. We include full answers for all questions, and also include
possible follow-up questions to help you test your understanding.
Purchasers of this book will have a huge competitive edge over those
who do not...
My third solo book
is not yet done...
Introductory
analysis
There is a famous quote: "the reader who finds he does not have the
prerequisites for the prerequisites should not lose heart" (or
something similar,) well basic analysis is the prerequisite for the
prequisites.
"Yet Another Introduction to Analysis " by Victor Bryant is the book
that I wish I had had when I was learning analysis, and if I was to
write a book on the topic this is the way I would write it, (except
that I won't because Bryant has already done it.) Bryant teaches
analysis with lots of motivation and examples. The reader he has in
mind knows calculus but cannot see the point of analysis. All
mathematics is (or should be!) invented to solve problems and Bryant
never forgets this, and explains why as well as how as he introduces
each theorem. If you find analysis too dry, this is the book for you.
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"Principles of Mathematical Analysis" by Walter Rudin. This a
great second book on analysis. It starts from first principles but is
drier that Bryant. So first read Bryant to get some idea of what is
going on, and then work through Rudin to get all the details and to
learn
enough to prepare you for measure theory.
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Probability Theory and Stochastic Processes
Modern financial mathematics relies heavily on probability theory, if
you want to do it well, you really need to learn to think
probablistically and to study the theory. To really understand
stochastic processes, you need to work through a program of
- basic probability theory
- basis analysis
- discrete-time martingales
- continuous-time martingales
- stochastic integration
I present a sequence of probability books to help you do this.
"Elementary Probability Theory" by Kai Lai Chung. This is the book I
first learnt probability theory from. Chung really knows how to write
and his target audience is undergraduates doing a first course in
probability. The new edition has a section on mathematical finance but
I haven't read that bit.
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"Probability and Random Processes" by Geoffrey Grimmett and David
Stirzaker. This is the other book I used when studying probability as
an undergraduate. It goes faster and further than Chung but the authors
have a real desire to teach as well as present material and is well
worth reading.
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"Probability with Martingales" by David Williams. This book is a joy to
read. The author takes a subject often regarded as hard and makes it
easy, whilst making it come alive with a chatty informal style. All
this without sacrificing rigour. Definitely one of my favourite maths
books. This is not a first book on probability theory but is a first
book on discrete time martingales.
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"Diffusions, Markov Processes and Martingales: by Chris Rogers
and David Williams. This is a two volume set. It is a natural
sequel to Williams' "probability with martingales," although the
authors quickly repeat much material from that book. This is a very
good choice for getting the basics of Brownian motions and continuous
time martingales in a rigorous fashion. The second volume then goes on
to discuss stochastic calculus. Whilst the second volume is good too, I
would recommend reading it after Chung and R.Williams (below.)
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"Introduction to Stochastic Integration" by K. L. Chung, R.J.
Williams. This is the same Chung but a different Williams! I found this
to be the most readable account of stochastic integration theory. It
assumes knowledge of continuous time martingales, however, so you must
learn those elsewhere first. The authors do all the details,
and focus on trying to present the most important case in careful and
clear detail rather than trying to work in absurd generality.
Unfortunately, it's currently out of print. (Someone please republish
it!)
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Basic mathematical
finance (0ther than my books...)
There is a rather large number of introductory textbooks on
financial mathematics each with its own bent. I haven't read
most of them inevitably. I mention a few I found helpful.
"Arbitrage Theory in Continuous Time" by Tomas Bjork. This books
presents a clear but fairly rigorous exposition of the basics of
financial mathematics. It bears some similarities to my book Concepts
but is stronger on rigour and lighter on practicalities. Unusually in
a rigorous book, Bjork never loses sight of the underlying ideas and
does a
good job of conveying them. The author's background is as a professor
in probability theory, and it shows in his approach and choice of
topics; the book is strong on risk-neutral evaluation and expectations,
but spends less time on PDEs.
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"Financial Calculus: An Introduction to Derivative Pricing"
by Martin W. Baxter, Andrew J.O. Rennie. This is a light and accessible
introduction to the martingale approach to derivatives pricing from a
reasonably pure viewpoint. The authors' objective was to teach the
reader the basics of the martingale theory without sacrificing too much
rigour, and in this they succeeded very well. Be aware, however, that
there is not
much discussion of practicalities nor of the PDE approach which is
barely mentioned.
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"The Mathematics of Financial Derivatives: A Student Introduction" by
Paul Wilmott, Sam Howison and Jeff Dewynne. This is written by experts
in applied PDEs for someone with a background in PDEs. It is therefore
a good exposition of the PDE approach and well worth reading for
getting a grounding in it. If you want to start with the PDE approach
and then move on later to the martingale approach it can also be a good
book to start with.
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"Stochastic Calculus for Finance" volumers I and II by Steven Shreve.
OK I haven't read these but lots of other people like them, and they do
seem to be a pair of the best introductory books available. In
particular, they seem to have a good blend of rigour and intuition.
Volume I does the binomial tree in great detail establishing all the
concepts necessary to do the continuous time case in Volume II.
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Medium mathematical
finance
Once you have mastered the basics, you will need more advanced books
both generalist and on specific areas.
"Martingale Methods in Financial Modelling" by Marek Musiela and Marek
Rutkowski. This book appears at first to be dry and difficult to read.
However, a lot of this is really just the formatting and font chosen by
Springer, and the book rewards perseverance, covering many advanced
topics in careful detail. As one can guess from the title, the book
emphasizes the modern martingale approach to financial engineering, and
it is written by two leading researchers on the practical side of the
field. Definitely not a first book, however. The book is good on
interest rate derivatives in particular.
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"Financial Modelling with Jump Processes" by Rama Cont and Peter
Tankov. Financial markets crash and are inherently jump. There has
therefore been much effort devoted in recent years to derivatives
pricing using jumpy processes. Cont and Tankov is a nice exposition of
this theory covering both jump-diffusion processes and more general
Levy processes. The point of view is quite applied with proofs
deemphasized.
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Interest rate
modelling
"Interest Rate Models - Theory and Practice: With Smile, Inflation and
Credit" by Damiano Brigo, Fabio Mercurio. This is a comprehensive book
on the theory and implementation of interest rate models with an
emphasis on the LIBOR market model. It has the great virtue that the
authors do all the details. Also, don't miss all the great quotes from
DC comics.
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Credit derivatives
"Credit Derivatives Pricing Models: Models, Pricing and Implementation"
by P.J. Schonbucher. Credit derivatives are a booming area. Schonbucher
introduces and discusses many of the standard models with a reasonable
level of detail. This is the best book currently available on the topic
(that I know of anyway...)
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Numerical
Techniques
"Monte Carlo Methods in Financial Engineering" by Paul Glasserman.
Monte Carlo is the most effective technique for high-dimensional
integration. This book is comprehensive and lucid, it's definitely
indispensable if you are implementing Monte Carlo pricing models.
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"Monte Carlo Methods in Finance" by Peter Jackel. Whilst Glasserman's
book is the definitive reference for Monte Carlo pricing in finance,
Peter's book is the best guide available on the use of
low-discrepancy
numbers particularly Sobol numbers for high dimensional
quasi-Monte-Carlo. Since their use can improve convergence rates from
O(n^(-1/2)) to O(n^-1), they are an important tool, and it's essential
to get
all the details right, Peter's book teaches you how to do this.
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"Numerical Mathematics and Computing" by Cheney and Kincaid. This is an
undergraduate textbook designed to teach someone with a smattering of
numerical analysis how to program models for numerical computation. I
found the book very clear and straightforward, and it covers many
topics useful to a quant.
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"Numerical Recipes in C++: The Art of Scientific Computing" by William
H. Press, Saul A. Teukolsky, William Vetterling, Brian P. Flannery.
This is a compendious collection of C++ source code and discussion of
numerical techniques that form an indispensable resource for the
working quant. The code suffers a bit from being translated from
FORTRAN but is very useful.
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C++
C++ is a standard tool for implementing pricing models in banks. Some
day, something better will supercede it, but for now you have to learn
it if you want to get a job as a quantitative analyst. There are also
very many books on this topic. The great virtue of C++ books is that
they take a lot less time to read than mathematical finance books so
you can get through a lot more of them.
First books
There are many first books on C++. I am going to list three and suggest
you pick the one that bests suits your background.
"C++ How to Program" by Harvey M. Deitel, Paul J. Deitel. This is an
introductory textbook for American undergraduates. This means it goes
slow, is comprehensive, uses lots of colour and is easy to read. I
would recommend this book if you haven't done much computing in other
languages.
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"C++ Primer" by Stanley B. Lippman, Josee Lajoie, Barbara Moo. This is
an introduction to C++ but it is really suited to someone who is very
competent in other programming languages. So if you are au fait with
programming and want something that will get you going quickly buy
this. It's a classic and has sold over half a million copies.
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"Thinking in C++' by Bruce Eckel. This two volume set is about how to
use the C++ language properly and aim to teach you the right way to
think about C++. In this it succeeds. It is, however, hard going for
those who do not know C, and the author assumes some knowledge of that
language. It's long and a lot of hard work but if you work
through it, you will really know how to program in C++.
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Topic books
Once you've got the basics, there are a number of books that aim to get
you from the novice level to the intermediate level. These generally
discuss small topics one by one rather than trying to be comprehensive.
"Effective C++", "More effective C++" and "Effective STL" by Scott
Meyers. Effective C++ was one of the first books to really discuss how
to use C++ as a language rather than focussing on the syntax. Meyers'
style is to give you lots of informal advice about the right way to do
things and in my experience, if Scott gives you a guideline you really
ought to follow it.
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"Exceptional C++", "More exceptional C++", "Exceptional C++ style" by
Herb Sutter. The author presents problems, invites the reader to solve
them, and then generally demonstrates that the reader doesn't
understand C++ nearly as well as he thought. There is a particular
focus on writing exception-safe code -- hence the title. Whilst the
presentation can be irritating at times, and I don't buy some of his
advice, Sutter will definitely improve your understanding of C++.
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"Large-Scale C++ Software Design" by John Lakos. Ever had a large
project that turned into spaghetti, or had a project where you were
afraid to change certain files because of the time it would take to
rebuild the project. This book is on how to avoid such problems by
organizing your code correctly from the start. Whilst the book is a
little-dated and there's a certain amount of overlap wth Sutter's
books, it's still a good read.
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"The C++ Standard Library: A Tutorial and Reference" by Nicolai M.
Josuttis. C++ ships with a lot of classes and algorithms; these are
called the Standard Library. Learning to use them properly will make
your code quicker to develop, more robust and more efficient. Reading
Josutti is a great way to do the learning.
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"C++ Templates: The Complete Guide" by David Vandevoorde, Nicolai M.
Josuttis. Everything you ever wanted to know about templates and quite
a few things you didn't. Templates in C++ have gone way beyond their
designers' original intention of providing a way of doing generic
programming to being a method of doing computations at compile time.
This book is the definitive book on the topic.
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Reference books
There are certain books that you should own and consult but shouldn't
try to read from cover to cover.
"The C++ Programming Language" by Bjarne Stroustrup. This is the
definitive guide to the language from the guy who invented it. Very
useful but paedagogy is not Bjarne's strength.
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"The C++ Standard: Incorporating Technical Corrigendum No. 1" by
British Standards Institute. This has to be one of the driest books
ever written, but sometimes you really want to know what the "legal"
rule is for some piece of C++ and this book is then great.
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C++ and quant finance
There are by now at least 5 books on this. I like my own, of course. I
haven't read the others but Daniel Duffy's books seem worthwhile. Erik
Schlogl's book will be good when it comes out. The books by Brooks and
London are not recommended.
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