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Hi! My name is Mike and I'm the guy behind QuantStart.com. 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.

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Welcome to your FREE Algorithmic Trading resource where you will learn how to develop profitable algorithmic trading strategies and gain a career in quantitative trading.

Latest Articles

Installing Nvidia CUDA on Ubuntu 14.04 for Linux GPU Computing

In this article I am going to discuss how to install the Nvidia CUDA toolkit for carrying out high-performance computing (HPC) with an Nvidia Graphics Processing Unit (GPU). CUDA is the industry standard for working with GPU-HPC. In a previous article Valerio Restocchi showed us how to install Nvidia CUDA on a Mac OS X system. In this article I am going to describe the same procedure but carry it out under the latest version of Ubuntu, namely 14.04. Read more...

Event-Driven Backtesting with Python - Part VIII

It's been a while since we've considered the event-driven backtester, which we began discussing in this article. In Part VI I described how to code a stand-in ExecutionHandler model that worked for a historical backtesting situation. In this article we are going to code the corresponding Interactive Brokers API handler in order to move towards a live trading system. Read more...

Support Vector Machines: A Guide for Beginners

In this guide I want to introduce you to an extremely powerful machine learning technique known as the Support Vector Machine (SVM). It is one of the best "out of the box" supervised classification techniques. As such, it is an important tool for both the quantitative trading researcher and data scientist. Read more...

Vector Addition "Hello World!" Example with CUDA on Mac OSX

In my previous article I explained how to install CUDA on OS X. Now it's time to start coding. However, I don't want to merely show you some piece of "ready-made" code. I would also like to also explain to you the basic concepts behind parallel programming and, specifically, GPU programming. Hence, in this article and in the following ones, I will pair some key theory with code examples. Read more...

Installing Nvidia CUDA on Mac OSX for GPU-Based Parallel Computing

This is the first article in a series that I will write about on the topic of parallel programming and CUDA. In this guide I will explain how to install CUDA 6.0 for Mac OS X. CUDA is a proprietary programming language developed by NVIDIA for GPU programming, and in the last few years it has become the standard for GPU computing. GPU computing is a new branch of computer science and, more specifically, of parallel computing. Read more...