bt
bt: A local Python library for composing and comparing historical portfolio backtests. Ranked #16 of 18 in Quant Tools by our editors (7.5/10); pricing: Free plan; best for lightweight Python backtesting.
At a glance
- Editor score7.5 / 10
- PricingFree plan
- Best forLightweight Python backtesting
- Free planYes
- Paid fromFree
- Live trade executionNo
- Facts checked24 Sep 2026
Where it wins
- Compose strategies from reusable algorithm components.
- Model portfolio rebalancing, transaction costs and commissions.
- Compare benchmarks with performance statistics and visualizations.
Where it doesn't
- No broker-connected live trading.
- No paper trading.
- Requires a local Python environment to run.
Our verdict on bt
For developers and quantitative researchers who want to test systematic investment strategies against historical price data, bt is an open-source Python package designed for local execution. It turns reusable algorithm components into portfolio backtests, with tools for rebalancing, cost modeling and performance analysis. Its focus is research and evaluation rather than operating a trading account, so it suits people comfortable working in Python more than buyers seeking a hosted trading interface.
The library’s strength is the scope of its backtest workflow: strategy construction, portfolio rebalancing rules, transaction costs and commissions, benchmarks, statistics and visualization sit within one package. That makes bt useful for comparing systematic approaches under modeled costs and reviewing how a portfolio performs against a benchmark. It is a focused framework, not a complete trading platform; the project does not provide broker-connected execution or paper trading. Choose it when a local, code-oriented backtest is the goal, rather than when a strategy needs to move directly into simulated or live orders.
Because bt is open source, it is available as a free Python package rather than a set of paid plans. Deployment is self-hosted, which gives technical users a local workflow but means the package is not a hosted service. Documentation and community are the stated support channels, so buyers should be comfortable consulting project materials and community resources. bt is a practical fit for solo researchers and teams that want composable historical testing; those who need managed infrastructure, broker integrations or execution features should consider a different kind of tool.
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bt pricing
bt fact sheet
| Free plan | Yes |
|---|---|
| Paid from | Free |
| Strategy backtesting | Yes |
| Live trade execution | No |
| Paper trading | No |
| Asset classes | Not verified |
| Strategy languages | Python |
| Historical data access | Yes |
| Deployment | Self-hosted |
| Support | Community, Docs |
| Built for | Solo, Small business, Mid-market (editorial estimate) |
| Pricing | Free plan |
| Website | pmorissette.github.io |
| Facts checked | 24 Sep 2026 |
Alternatives to bt
- QuantConnectA multi-asset research and trading workflow with backtesting, paper trading, and live deployment.9.3
- ProRealTimeMulti-platform charting, backtesting and automated trading through broker partners.9.0
- BacktraderA free, open-source Python framework for strategy research and broker-connected trading.8.8
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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