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Algorithmic Trading Resources

Part of being an algo trader is constantly learning and growing your expertise. Expand your programming knowledge and learn new skills with these educational courses focusing on various aspects of algorithmic trading. For more, check out our short instructional videos and articles.

Learn Algorithmic Trading with Courses from Quantra*

What You Will Learn:

  • The basics of forex trading
  • How macroeconomic factors affect the forex market
  • How to fetch data and code a momentum trading strategy
  • How to backtest any strategy on the Quantra Blueshift platform
  • How to manage intraday risk while trading in the forex markets

What You Will Learn:

  • Familiarize yourself with the Python programming language
  • Implement Python in the context of financial markets
  • Import real market OHLC data, visualize and manipulate it the way you want
  • Create strong building blocks to code your own algorithmic trading strategy in Python

What You Will Learn:

  • What is Algorithmic Trading and its advantages over manual trading
  • Different strategy paradigms & modeling ideas used for algorithmic trading and back-testing
  • The requirements for setting up an algorithmic trading platform
  • How to backtest any strategy on the Quantra Blueshift platform
  • How to manage intraday risk while trading in the forex markets

What You Will Learn:

  • Basics of Machine Learning for trading
  • Implement different machine learning algorithms to trade in financial markets
  • Analyze the Machine Learning model predictions in train and test data set
  • Code and backtest trading strategies using a machine learning algorithm in Python

What You Will Learn:

  • Code trading strategies using technical indicators such as moving averages, Relative Strength Index, etc.
  • Build your own trading strategies and backtest their performance on historical data
  • Code a momentum trading strategy using TA-Lib library
  • Analyze the trading strategies using various performance metrics

What You Will Learn:

  • The basics of cryptocurrencies
  • How to choose wallets and exchanges to trade cryptocurrencies
  • How to code and backtest a Ichimoku Cloud strategy
  • How to create a strategy based on the day of the week and backtest it
  • How to trade the divergence between RSI and price series and the risks associated with intraday trading using AROON indicator

What You Will Learn:

  • Advanced trading strategies for cryptocurrencies
  • Unsupervised machine learning algorithms in cryptocurrencies
  • Pairs trading on cryptocurrencies
  • Time series analysis such as Hurst exponent to optimize the entry points
  • Quantitative trading strategy framework and implement a long-only momentum strategy

Articles From QuantNews

Algo Trading with Python and REST API | Part 1: Preparing Your Computer

In this multi-part series we will dive in-depth into how algorithms are created, starting from the very basics. In this article, you will learn how to prepare your computer for algo trading with REST API and Python. If you have already prepared your computer, please feel free to skip ahead.

Intro to Machine Learning in Less than 50 Lines of Code

In this article we will cover the basic framework of coding out a machine learning algorithm on FXCM's CFD index, SPX500. This article is based on the free course Introduction to Machine Learning.

Algo Trading with REST API and Python – Developing a RSI Range Strategy

In this article, we will code a closed-bar RSI strategy using Python and FXCM's Rest API. Parameters will include symbol/instrument, timeframe, RSI periods, lot size, and stop/limit distance.

Setting up a Bitcoin Breakout Trading Algorithm on FXCM's Trading Station Platform

This article will show how to setup a breakout strategy geared specifically towards trading Bitcoin. If you have not used FXCM's desktop trading platform before, it can be downloaded and installed for free from FXCM's download page.

Bollinger Bands Backtest using Python and REST API I | Part 1

Welcome to this tutorial on a Bollinger Bands strategy using REST API and Python. We will be using a Jupyter notebook to do a simple backtest of a strategy that will trigger trades based on the lower band of the Bollinger Bands indicator.

3 Ways to Identify a Ranging Market with Your Algo

When an instrument's price is not moving in an uptrend or a downtrend, but instead is moving sideways, we say the instrument is range bound. This article will discuss 3 ways to programmatically identify a ranging market.