Recommended Readings for the 2015 MQF Program


Background Textbooks

Finance

  • Phelim P Boyle and Feidhlim P. Boyle: Derivatives, The Tools that Changed Finance - - Click Here
  • John C. Hull: Options, Futures, and Other Derivatives, 9-th Edition - - Click Here and Click Here
  • David G. Luenberger: Investment Science - - Click Here
  • Sheldon M. Ross: An Introduction to Mathematical Finance: Options and Other Topics - - Click Here

Probability and Statistics

Topics: Distribution of random variables; Conditional probability and stochastic independence; Some special distributions; Distributions of functions of random variables; Limiting distributions; Estimations; Markov Chains; and Brownian Motion and Markov Processes.

  • Robert Hogg and Allen Craig: Introduction to Mathematical Statistics, 7-th Edition - - Click Here, Chapters 1-6
  • Sheldon M. Ross: Stochastic Processes - - Click Here, Chapters 4-6

Econometrics

Familiarity with multiple regression would be helpful. Most standard econometric textbook will cover this topic. For example:

Real Analysis

Topics: The real number system; Elements of set theory; Numerical sequences and series; Continuity; The Riemann integral; and Sequences and series of functions. These topics can be found in the classic textbook by:

  • W. Rudin: Principles of Mathematical Analysis - - Click Here, Chapters 1-7
  • H. Royden amd P.Fitzpatrick: Real Analysis, 4-th Edition - - Click Here

Calculus

Topics: Techniques of integration; Partial derivatives; Multiple integrals; Vector calculus; Optimization of multivariable functions; Ordinary differential equations. Most concepts in univariate differential and integral calculus will be used routinely. There are many books that cover these topics, for example:

Linear Algebra

Topics: Matrix algebra; Determinants; Vector spaces and linear transformation; Orthogonality and projections; and Eigenvalues and eigenvectors. There are many excellent textbooks on linear algebra that cover these topics, for example:

Lecture Notes

Undergraduate Probability Theory

Undergraduate Stochastic Processes

  • Notes based on Essentials of Stochastic Processes by Rick Durrett - - Click Here

Undergraduate Finance

  • Bass, R. F: The Basics of Financial Mathematics - - Click Here
  • Wirjanto, T. S: Finance Notes - - Click Here

Graduate Probability Theory

Graduate Finance

  • Shreve, S: Stochastic Calculus and Finance - - Click Here

Additional Readings

C++

C++ is a challenging programming language for novice quants to get grips with. The books listed below, if read and understood properly, would help make you somewhat proficient in the C++ programming:

  • J. Liberty and R. Cadenhead: Sams Teach Yourself C++ in One Hour a Day, 7-th Edition - - Click Here
  • H. Schildt: C++: A Beginner's Guide, 2-nd Edition - - Click Here
  • A. Koenig and B. Moo: Accelerated C++: Practical Programming by Example - - Click Here
  • S. Meyers: Effective C++: 55 Specific Ways to Improve Your Programs and Designs, 3-rd Edition - - Click Here

Python

Python has become inreasingly popular in the quantitative finance world. It is a relatively 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, it would a valuable asset to know Python, as it is only going to become more widely adopted in the financial industry as time goes on.

  • M. Lutz: Learning Python: Powerful Object-Oriented Programming - 5-th Edition - - Click Here
  • M. Lutz: Programming Python - - Click Here
  • D. Beazley and B. K. Jones: Python Cookbook, 3-rd Edition - - Click Here
  • Allen B. Downey: Think Python - - Click Here

MATLAB

MatLab is still widely used in the financial industry. The following textbooks will help you learn, and upgrade your skill in, Matlab:

  • Stormy Attaway: Matlab, 3-rd Edition: A Practical Introduction to Programming and Problem Solving - - Click Here
  • Paolo Brandimarte: Numerical Methods in Finance and Economics: A MATLAB-Based Introduction - - Click Here
  • H. T. Huynh, V. S. Lai, I. Soumare: Stochastic Simulation and Applications in Finance with MATLAB Programs - - Click Here
  • D. Pachamanova and F. J. Fabozzi: Simulation and Optimization in Finance + Website: Modeling with MATLAB, @Risk, or VBA - - Click Here

R

As with MatLab, R is extensively used in the financial industry as it is a natural language with which to carry out advanced statistical analysis for model vetting exercises and predictive analysis. A great way to learn R is to pair the following books with a course in statistics, which will often make use of R (such as STAT 974/ACTSC 974):

  • A. F. Zuur, E. N. Ieno, and E. Meesters: A Beginner's Guide to R - - Click Here
  • P. Dalgaard: Introductory Statistics with R - - Click Here
  • P. S.P. Cowpertwait and A. V. Metcalfe: Introductory Time Series with R - - Click Here
  • P. Spector: Data Manipulation with R - - Click Here

Excel/VBA

Although not having nearly as much computational horsepower as that of C++ or Python, Excel is still the most widely used software in the financial industry. If you are working on an investment banking prop trading desk as a quant, you will be asked to implement functions in Excel for the traders at some point in time. The following textbooks could prove handy:

  • I. Gottlieb: Next Generation Excel: Modeling in Excel for Analysts and MBAs, 2-nd Edition - - Click Here
  • M. Jackson and M. Staunton: Advanced modelling in finance using Excel and VBA - - Click Here
  • J. Walkenbach: Excel 2010 Power Programming with VBA - - Click Here
  • G. Löeffler and P. N. Posch: Credit Risk Modeling using Excel and VBA - - Click Here
  • F. D. Rouah and G. Vainberg: Option Pricing Models and Volatility Using Excel-VBA - - Click Here

General Readings in Finance

If you feel that you lack basic financial markets knowledge, and can not tell your stock from your bond, or your bank from your fund, then you should make these books your bedtime readings:

  • M. Lewis: The Big Short: Inside the Doomsday Machine - - Click Here
  • M. Lewis: Liar's Poker - - Click Here
  • R. Lowenstein: When Genius Failed: The Rise and Fall of Long-Term Capital Management - - Click Here
  • E. Derman: Models Behaving.Badly - Why Confusing Illusion with Reality Can Lead to Disaster, on Wall Street and in Life - - Click Here
  • R. Lindsey and B. Schachter: How I Became a Quant: Insights from 25 of Wall Street's Elite - - Click Here

Interview Preparation Readings

In a highly competitive world, it is simply not good enough just 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 would also need to prepare yourselves to be successful in the interviews. The following books are some resources for helping you do this. Make sure that you study not only the content of the brainteasers, but also try to deconstruct how they are put together in the first place and what you are really being asked.

  • P. Wilmott: Frequently Asked Questions in Quantitative Finance - - Click Here
  • T. Crack: Heard on The Street: Quantitative Questions from Wall Street Job Interviews - - Click Here
  • M. Joshi, N. Denson and A. Downes: Quant Job Interview Questions And Answers, 2-nd Edition - - Click Here
  • X. Zhou: A Practical Guide To Quantitative Finance Interviews - - Click Here
  • B. Jiu: Starting Your Career as a Wall Street Quant: A Practical, No-BS Guide to Getting a Job in Quantitative Finance - - Click Here
  • G. McDowell: Cracking the Coding Interview: 150 Programming Questions and Solutions - - Click Here

Historical Background Readings

  • The article by Jarrow and Protter gives a history of the development of stochastic calculus and its application to mathematical finance. It includes the sad tale of Doeblin, and explains why a Frenchman had a German name. It can be found here as a PDF file.
  • This article was written to commemorate Louis Bachelier (whom many consider to be the founding father of mathetmatical finance) on the Centenary of Thèorie de la Spèculation? It can be found in here as a PDF file.