Check out my new e-book on C++ where I teach you all the C++ you need to get a quant job paying $100k a year on average.

Hi! My name is Mike and I'm the guy behind I used to work in a hedge fund as a quantitative trading developer in London.

Now I research, develop, backtest and implement my own intraday algorithmic trading strategies using C++ and Python.



Welcome to the big list of QuantStart quantitative finance articles!

I've tried to write articles that will benefit YOU on your journey to becoming a professional quantitative analyst.

If you are a complete beginner to the world of quantitative finance, I suggest you take a look at my newbies guide first, then come back here.

Singapore Financial District via Jo@net

There's a lot of reading here, so I suggest starting with the Careers Advice and Quant Reading Lists as they will get you on the right track.

When you're ready to learn more advanced material, you can check out the trading, mathematics and programming articles:

I'm constantly adding articles each week, so keep checking back regularly.

If you would like to see articles on any other topic, please feel free to email me at

Careers Advice

This is the place to start if you are looking for guidance on how to accelerate your quant career. I've discussed PhDs, MFEs and as well as the different types of quant roles.

Quant Reading Lists

The following lists of books will get you up to speed on how to become a quant. I've broken them down into Maths Finance, C++, Python and Interview Guides. If you want to see in depth book reviews, check out the section below.

Algorithmic Trading

Algorithmic trading is an extremely interesting and growing area, particularly in the hedge fund industry. More funds spring up every year. However, to become a successful algorithmic trader requires a decent background in many topics.

The Binomial Model

The binomial model is a great way to introduce options pricing. Although the method is rarely used computationally, it provides good intuition on how options pricing works.

Stochastic Calculus

You can't do quantitative finance without stochastic calculus. The following articles discuss the relevant stochastic calculus you need to understand the famous Black-Scholes equation derivation.

Numerical PDE

The Black-Scholes equation is a partial differential equation (PDE). In order to solve it you can use numerical discretisation techniques such as Finite Difference Methods. The following articles walk you through the basic techniques.

C++ Implementation

As with stochastic calculus, you really cannot avoid learning C++ for pricing derivatives! Love it or hate it, it is essential. Although the following articles won't teach you how to program from scratch, I will point out intermediate to advanced features that you can impress interviewers with when you apply for that banking role!

Python Implementation

If you are more interested in becoming a quantitative trader in a hedge fund, then Python is something you definitely need to know. End-to-end trading systems are now being built entirely in Python, so I've written some articles to help you get started.

Book Reviews

I've reviewed some of my favourite Quant Finance books below. If you are interested in any of the following titles then please take a look.

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