Algorithmic Trading Model with ML4T Chapter 1 Storage Benchmark Examples

NOTE: This script is for learning purposes only and does not constitute a recommendation for buying or selling any stock mentioned in this script.

SUMMARY: This project aims to construct and test an algorithmic trading model and document the end-to-end steps using a template.

INTRODUCTION: This script aims to replicate the examples found in chapter one of the book Machine Learning for Algorithmic Trading by Stefan Jansen. The script seeks to validate further the Python environment and package requirements for running these code examples. The eventual goal is to integrate various example code segments into an end-to-end algorithmic trading system.

This benchmarking exercise used the Google Colab environment as it has the prerequisite libraries and packages already built-in.

Dataset ML Model: Time series analysis with numerical attributes

Dataset Used: Programmatically generated DataFrame with random data

Source and Further Discussion of the Code Examples:

The HTML formatted report can be found here on GitHub.