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VectorBT is a Python toolkit for trading research. Explore market data, build indicators and signals, and compare thousands of ideas across assets and timeframes. NumPy arrays, Numba acceleration, and an optional Rust engine let you run large experiments in a few lines of Python.
Move from exploring price patterns to evaluating strategies in one workflow. Inspect trades, fees, drawdowns, and portfolio performance, then explore the results with interactive charts. Built for traders, researchers, and AI agents, VectorBT brings data analysis, strategy simulation, and visualization together in a composable Python API.
VectorBT is the open-source community edition of VectorBT PRO. PRO extends the library with parallelization, additional data integrations, portfolio optimization, pattern recognition, event projections, limit orders, leverage, and over 100 other features, with new features added weekly.
See VectorBT vs PRO or browse PRO feature examples.
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Research strategies at scale with pandas, NumPy, and Numba. |
Use precompiled kernels for supported operations without JIT compilation. |
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Work with custom accessors and high-performance operations directly on pandas objects. |
Analyze multiple assets and sweep large parameter grids with flexible array broadcasting. |
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Build custom indicators and use integrations for TA-Lib, Pandas TA, and more. |