This trailer will walk you thought the important components you will need to build a fully functioning algorithmic trading system. There are Python source code samples inlcuded as well.
Prerequisites and Requirements
Python is easiest programming to learn about fairly advanced trading, algo research, and other critical elements in automated trading. Basic knowledge of Python is needed which include popular packages including pandas, matplotlib, and numpy.
This course will give you an overview of the critical components needed for your own algo trading system. This will give thought on pieces that will make you successful as indie automated trader to control your own destiny.
Module 1: Popular Programming for Algos and Automated Trading
Remember this course series will focus primarily on Python after all languages described below. I will post the advantages of it in a separate module so please just use the following for comparison reasons only.
Module 2: Why Python for my algos and automated trading
HFT Firms like Jump, Citadel, Two Sigma, etc use Python as their standard high level language before moving into C++. If you are new to all this programming thing, just focus on the intro resources I list below.
I am also planning to implement with Python 100% due to:
Module 3: Setting up your Python environment BB
The wonky thing about Python is setting up your environment. It depends on your chosen operating system to deploy Python. I found Python works great when you are on a Linux friendly environment like Ubuntu Distribution or even my preferred option like Apple MAC OS X.
Module 4: Brand spanking new to programming via Python learning:
I struggled with Python on Windows. I recommend to install Python on a Linux Virtual Machine via VMWare Workstation or free Virtual Box. Ubuntu or Mint Linux distribution is preferred for testing/development only.
Module 5: Intro overview of MongoDB open source NOSQL database
At first, I was a never a huge fan of this database option but after my fiascoes with both MYSQL and PostgreSQL on my Mac OS X environment, I quickly realized there had to be an easier way. Once setup properly, you will find MongoDB is really light but yet has the all the required database features you would expect. This includes:
Module 6: Intro to Redis for highest performance in your algo trading
Redis is another NOSQL database but primarily used for in-memory only vs MongoDB which is used for persistence which is disk based. Redis is considered one of the fastest databases on the planet so if implemented right, you could use this for HFT performance potentially.
Module 7: Interfacing with Interactive Brokers TWS with Python and other demos
I have so many demos of using Interactive Brokers with Trader Workstation (TWS). First, let’s focus on interfacing with Python
Module 8: Market Data Source with Yahoo Finance
In Python, there are numerous packages you could use to access Yahoo Finance which is FREE. There is one demo in this preview but do understand that this will be used throughout my Arbitrage/Pair Trading phase in the next course of this Python Algo Trading Course Series
Module 9: Pretty trading charts with Matplotlib and PyQtChart
As this is the Infrastructure Building Block phase, our first phase on Arbitrage Pair Trading will have many demos available with source code. Let’s just focus on the capabilities of these cool Python charting packages
I’m Bryan Downing and I’m the founder and owner of Quantlabs.net. ‘QLN’ (as I often call it) is unique – it’s the only quant-related website and membership service expressly designed to help you gain practical experience with the quantitative world.