├── FinancialMarkets.md └── README.md /FinancialMarkets.md: -------------------------------------------------------------------------------- 1 | [Expected Returns](http://www.amazon.com/Expected-Returns-Investors-Harvesting-Rewards/dp/1119990726) 2 | 3 | ## Oil 4 | 5 | [Oil 101](http://www.amazon.com/Oil-101-Morgan-Downey/dp/0982039204) 6 | 7 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # qfin 2 | Books for Quant Finance Interviews. (*comments on the usefulness* are based on the score of 0-5). 3 | 4 | ## Brain Teasers 5 | 6 | *comments on the usefullness*: 5 for fresh graduate, `max(2, 5 - #years of experience)` for experienced hires. 7 | 8 | ### Basic 9 | [A Practical Guide To Quantitative Finance Interviews](http://www.amazon.com/Practical-Guide-Quantitative-Finance-Interviews/dp/1438236662) 10 | 11 | All Martin Gardner's books, 12 | [book1](http://www.amazon.com/Mathematical-Logic-Puzzles-Dover-Recreational/dp/0486281523) * | 13 | [book2](http://www.amazon.com/Entertaining-Mathematical-Puzzles-Martin-Gardner/dp/0486252116) * 14 | 15 | ### Advanced 16 | 17 | [Mathematical Olympaid Challenges](http://www.amazon.com/Mathematical-Olympiad-Challenges-Titu-Andreescu/dp/0817645284) * 18 | 19 | [The USSR Olympiad Problem Book](http://www.amazon.com/The-USSR-Olympiad-Problem-Book/dp/0486277097) * 20 | 21 | ## Algorithms / Whiteboard Programming 22 | 23 | *comments on the usefullness*: 5 for high frequency or algo trader/researcher, pricing quants (model validation roles), start arb strategists. 24 | 25 | [Algorithm for interviews](http://www.amazon.com/Algorithms-Interviews-Adnan-Aziz/dp/1453792996) * 26 | 27 | [Leetcode](https://leetcode.com/) 28 | 29 | Cracking the Coding Interviews by [Careercup.com](http://www.careercup.com/) * 30 | 31 | ## Quant Equity / Portfolio Theory 32 | 33 | *comments on the usefullness*: 5 for quant equity strategists, 4 for quant macro strategists. 34 | 35 | [Quantitative Equity Portfolio Management: Modern Techniques and Applications](http://www.amazon.com/Quantitative-Equity-Portfolio-Management-Applications/dp/1584885580) * 36 | 37 | [Active Equity Management](http://www.amazon.com/Active-Equity-Management-Xinfeng-Zhou/dp/0692297774) * 38 | 39 | [Financial Modeling of the Equity Market: From CAPM to Cointegration](http://www.amazon.com/Financial-Modeling-Equity-Market-Cointegration/dp/0471699004) * 40 | 41 | ## Statistics 42 | 43 | *comments on the usefullness*: 5 for all roles. 44 | 45 | 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](http://www.amazon.com/Econometric-Analysis-7th-William-Greene/dp/0131395386) * 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) 46 | 47 | [Analysis of Financial Time Series](http://www.amazon.com/Analysis-Financial-Time-Series-Ruey/dp/0470414359) * I personally like other books more, but this book exposes one to the most number of time series models. 48 | 49 | [Time Series Analysis](http://press.princeton.edu/titles/5386.html) A much better book, also more expensive. 50 | 51 | ## C/C++ 52 | 53 | *comments on the usefullness*: 5 for high frequency or algo trader/researcher, pricing quants (model validation roles), start arb strategists. 54 | 55 | If you rarely program in C/C++, start with [C++ Design Patterns and Derivatives Pricing](http://www.amazon.com/Patterns-Derivatives-Pricing-Mathematics-Finance/dp/0521721628). This is by no means a complete introduction, but it gives you an overview of the language. 56 | 57 | Try using a **build system**, do not use an IDE. I prefer the naive [makefile](http://www.amazon.com/Managing-Projects-Make-Nutshell-Handbooks/dp/0596006101) and the advanced [CMake](http://www.cmake.org/). (My personal view is Autotools is unpretty and out-dated.) IDEs are nice to work with, but helpless for interview prep. 58 | 59 | Try writing C++ using only objects. Templates are nice to have as well. Use [Design Patterns](https://sourcemaking.com/) whenever you can. 60 | 61 | Here is a short but interesting article on [Expression Template](https://github.com/dmlc/mshadow/tree/master/guide/exp-template) that examplifies some basic usage of C++ templates. 62 | 63 | You **must** finish Scott Meyers' 64 | 65 | - [Effective C++](http://www.amazon.com/Effective-Specific-Improve-Programs-Designs/dp/0321334876) * 66 | - [Effective STL](http://www.amazon.com/Effective-STL-Specific-Standard-Template/dp/0201749629) 67 | 68 | before your first C++ interview. There are other books, [More Effective C++](http://www.amazon.com/More-Effective-Improve-Programs-Designs/dp/020163371X) and [Effecive Mordern C++](http://www.amazon.com/Effective-Modern-Specific-Ways-Improve/dp/1491903996), but I haven't read them yet. 69 | 70 | ## R 71 | 72 | *comments on the usefullness*: not heavily tested during interviews, but very helpful. 73 | 74 | There's no real good book for R. Hadley's [Advanced R](http://adv-r.had.co.nz/) is an excellent book, but it is only for advanced users. 75 | 76 | I would suggest starting from [An Introduction to R](https://cran.r-project.org/doc/manuals/r-release/R-intro.html) and familarize yourself with the following packages: 77 | 78 | - data.table 79 | - dplyr 80 | - foreach 81 | - ggplot2 82 | - reshape2 83 | 84 | and these packages as well: 85 | 86 | - stringr 87 | - lubridate 88 | - Matrix 89 | - gridExtra 90 | 91 | Once you are fluent with R, take a look at these advanced packages: 92 | 93 | - Rcpp 94 | - devtools 95 | - testthat 96 | - roxygen2 97 | 98 | Make sure you understand the usage and output of these functions: `lm`, `glm`, `anova`, `summary.lm`, `plot.lm`, `acf`, `pacf`. 99 | 100 | ## Python 101 | 102 | *comments on the usefullness*: 5 for all roles 103 | --------------------------------------------------------------------------------