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vectorbt
High-performance vectorized backtesting with parameter optimization, portfolio simulation, and rich performance metrics
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# Vectorized Backtesting with vectorbt
## Overview
vectorbt is a Python library for **vectorized backtesting** — running strategy simulations using NumPy/pandas array operations instead of bar-by-bar loops. This makes it 100–1000x faster than event-driven frameworks (backtrader, zipline), enabling parameter optimization across thousands of combinations in seconds.
**Key strengths:**
- Blazing speed via NumPy vectorization
- Built-in parameter grid search and optimization
- 50+ built-in performance metrics (Sharpe, Sortino, Calmar, max drawdown, profit factor)
- Rich plotting (equity curves, drawdowns, trade markers, heatmaps)
- Native pandas integration — your data stays in DataFrames throughout
## Installation