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

uv pip install vectorbt pandas numpy