pmorissette/bt

Health v2 · maintenance only

Adoption not part of the score

2966 stars · 493 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

bt is a flexible Python backtesting framework for testing quantitative trading strategies. It uses composable Algos and AlgoStacks with a tree structure to build modular, reusable strategy logic, and provides charting and detailed performance statistics.

Use cases

• backtest a quantitative trading strategy in python
• test a monthly rebalanced portfolio strategy on historical data
• compare performance statistics across multiple backtests
• build modular reusable trading strategy logic
• visualize backtest results with charts
• simulate long-only equal-weight allocation strategies

When to choose

• you are a quant developing and testing trading strategies in Python
• you want composable, reusable strategy logic blocks instead of monolithic backtest scripts
• you want built-in stats and charting for backtest comparison
• you want to leverage the Python data ecosystem (pandas, ffn) in your strategies

When to avoid

• you need live trading or broker execution - bt is backtesting only
• you need high-frequency or tick-level backtesting performance
• you need a production-stable release - bt is self-described as alpha stage
• you are not working in Python

Facets

framework · maturity active

simulation data-visualization benchmarking fintech data-science python cross-platform backtesting quantitative-finance algorithmic-trading trading-strategies finance algorithms

Member repositories

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