PyBroker
A Python framework for developing and backtesting algorithmic trading strategies with machine learning.
What is PyBroker?
PyBroker is a Python framework for developing algorithmic trading strategies with a focus on machine learning integration. It provides tools for creating trading rules, building models, backtesting strategies, and evaluating performance using reliable metrics. The framework solves the problem of building and testing data-driven trading systems efficiently and accurately.
Quantitative traders, algorithmic trading developers, and data scientists who want to create, test, and deploy trading strategies using Python and machine learning techniques.
Developers choose PyBroker for its high-performance backtesting engine accelerated with Numba, integrated support for machine learning model training and walkforward analysis, and reliable bootstrapped metrics that provide more accurate strategy evaluation compared to basic backtesting tools.
Overview
Algorithmic Trading in Python with Machine Learning
Use Cases
Best For
- Backtesting algorithmic trading strategies with high performance requirements
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