Tutorials on algorithmic trading#
Here is a collection of blog posts and tutorials that are relevant for algorithmic trading in Python.
Financial Models and Numerical Methods#
A collection of Jupyter notebooks based on different topics in the area of quantitative finance.
Gallery of Jupyter Books#
Multiple data research and quantative finance books for Python and Jupyter
Teddy Koker’s blog#
Articles on trading, gambling and machine learning.
Backtesting option strategy with Backtrader#
An example tutorial.
ML Algotrading Wiki#
A wiki website with research and various news sources.
MLTraders’ Algotrading and Machine Learning work for everybody..
Pair Trading: A market-neutral trading strategy with integrated Machine Learning#
The primary goal in an investment endeavor is the implementation of strategies that minimize the risk while also maximizing the financial gain or return from the said investment. While there have been many popular strategies and techniques developed over the years that point towards the same goal, the ‘Pairs-Trading’ strategy is one that has been used to great extent in modern hedge-funds, for its simplicity and inherent market-neutral qualities.
ML for Trading#
This book aims to show how ML can add value to algorithmic trading strategies in a practical yet comprehensive way. It covers a broad range of ML techniques from linear regression to deep reinforcement learning and demonstrates how to build, backtest, and evaluate a trading strategy driven by model predictions.
The anatomy of an ML-powered stock picking engine.