qfin

Books for Quant Finance Interviews. (comments on the usefulness are based on the score of 0-5).

Brain Teasers

comments on the usefullness: 5 for fresh graduate, max(2, 5 - #years of experience) for experienced hires.

Basic

A Practical Guide To Quantitative Finance Interviews

All Martin Gardner's books, book1 * | book2 *

Advanced

Mathematical Olympaid Challenges *

The USSR Olympiad Problem Book *

Algorithms / Whiteboard Programming

comments on the usefullness: 5 for high frequency or algo trader/researcher, pricing quants (model validation roles), start arb strategists.

Algorithm for interviews *

Leetcode

Cracking the Coding Interviews by Careercup.com *

Quant Equity / Portfolio Theory

comments on the usefullness: 5 for quant equity strategists, 4 for quant macro strategists.

Quantitative Equity Portfolio Management: Modern Techniques and Applications *

Active Equity Management *

Financial Modeling of the Equity Market: From CAPM to Cointegration *

Statistics

comments on the usefullness: 5 for all roles.

Linear regression is the most heavily tested topic in statistics. Unfortunately, there are not many good books on this topic (either too elementary or too advanced). Greene's Econometric Analysis * might be an overshoot due to its length. Honestly, if you are able to manually calculate all outputs from R regression functions, you should be fine. (see my comments on R)

Analysis of Financial Time Series * I personally like other books more, but this book exposes one to the most number of time series models.

Time Series Analysis A much better book, also more expensive.

C/C++

comments on the usefullness: 5 for high frequency or algo trader/researcher, pricing quants (model validation roles), start arb strategists.

If you rarely program in C/C++, start with C++ Design Patterns and Derivatives Pricing. This is by no means a complete introduction, but it gives you an overview of the language.

Try using a build system, do not use an IDE. I prefer the naive makefile and the advanced CMake. (My personal view is Autotools is unpretty and out-dated.) IDEs are nice to work with, but helpless for interview prep.

Try writing C++ using only objects. Templates are nice to have as well. Use Design Patterns whenever you can.

Here is a short but interesting article on Expression Template that examplifies some basic usage of C++ templates.

You must finish Scott Meyers'

• Effective C++ *
• Effective STL

before your first C++ interview. There are other books, More Effective C++ and Effecive Mordern C++, but I haven't read them yet.

R

comments on the usefullness: not heavily tested during interviews, but very helpful.

There's no real good book for R. Hadley's Advanced R is an excellent book, but it is only for advanced users.

I would suggest starting from An Introduction to R and familarize yourself with the following packages:

• data.table
• dplyr
• foreach
• ggplot2
• reshape2

and these packages as well:

• stringr
• lubridate
• Matrix
• gridExtra

Once you are fluent with R, take a look at these advanced packages:

• Rcpp
• devtools
• testthat
• roxygen2

Make sure you understand the usage and output of these functions: lm, glm, anova, summary.lm, plot.lm, acf, pacf.

Python

comments on the usefullness: 5 for all roles