- Library of Utilities and Composable Base Strategies
- Multiple Time Frames
- Parameter Heatmap & Optimization
- Trading with Machine Learning
These tutorials are also available as live Jupyter notebooks:
In Colab, you might have to
!pip install backtesting.
- (contributions welcome)
For an overview of recent changes, see What's New.
Some answers to frequent and popular questions can be found on the issue tracker or on the discussion forum on GitHub. Please use the search!
This software is licensed under the terms of AGPL 3.0, meaning you can use it for any reasonable purpose and remain in complete ownership of all the excellent trading strategies you produce, but you are also encouraged to make sure any upgrades to Backtesting.py itself find their way back to the community.
API Reference Documentation
Core framework data structures. Objects from this module can also be imported from the top-level module directly, e.g …
Collection of common building blocks, helper auxiliary functions and composable strategy classes for reuse …
Data and utilities for testing.