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Overview of Your Python Infrastructure Building Blocks

Learn the important components for building an algorithmic trading system from scratch. This has been built for newbies using the easiest programming language called Python.

  • Intermediate training
  • Videos in HD format
  • Approximate 10 hours
  • Downloadable PDFs

Watch Trailer

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.

What Will You Learn?

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:

  • Condensed Coding and Simple
  • Mature community for extended trading strategy ideas
  • Open source which means it’s free unlike my love of commercial MATLAB

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:

  • Fairly fast and Open source meaning it is free
  • Highly popular and most popular NOSQL database out there
  • Has enterprise level features like clustering and redundancy

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.

  • Fastest possible and Open source meaning it is free
  • Highly popular and most popular NOSQL database out there
  • Has enterprise level features like clustering and redundancy

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

Your Online Instructor

Bryan Downing

I’m Bryan Downing and I’m the founder and owner of ‘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.