Resources¶

Install VectorBT with the core package, optional Rust kernels, Docker, and extra dependencies.

Start with holding, signal backtesting, parameter grids, interactive plots, and example apps.

Browse the source code, examples, issues, discussions, and release history for the open-source project.

Learn more about the advanced edition and how to access features beyond open-source VectorBT.

Analyze the performance of a dual moving average crossover strategy.

Study stop-loss, trailing-stop, and take-profit behavior.

Backtest signals per trading session and compare session-level behavior.

Explore portfolio construction and optimization workflows.

Plot MACD parameter results as a 3D volume.

Split time series data and evaluate strategies out of sample.

Run a Telegram-based signal workflow with VectorBT utilities.

Port an RSI strategy from backtrader into VectorBT.

Compare a pairs-trading workflow against backtrader.

Design a streaming SuperTrend indicator and run large parameter sweeps.

Convert strategies into signals and inspect their distribution for logical flaws.

Analyze stop orders, stop prices, and stop combinations across market regimes.

Work with multiple timeframes in a single research pipeline.

Optimize portfolio weights and analyze allocation choices.

Research pairs-trading workflows with VectorBT PRO.

Detect historical patterns and project similar future segments.

Validate strategy parameters across splits to reduce overfitting.

Resample and align multiple timeframe data for VectorBT PRO strategies.

Develop signals and convert them into VectorBT PRO portfolio simulations.

Visualize indicators, cleaned signals, and strategy behavior in VectorBT PRO.

Simulate and inspect multi-asset portfolio behavior with VectorBT PRO.

Build a custom dashboard for portfolio simulation and strategy visualization.

Backtest manually derived trading signals with VectorBT PRO.

Introduce the main functions behind a custom VectorBT PRO simulator.

Implement a basic candlestick strategy in a custom VectorBT PRO simulator.

Add stop-loss and take-profit logic to a custom candlestick simulator.

Extend custom simulation with partial-profit exits and risk management.

Two million backtests shed light on stop-loss, trailing-stop, and take-profit behavior.

Design a high-performance SuperTrend implementation and scalable backtesting pipeline.

AlgoTrading101 introduces VectorBT concepts, examples, and common workflows.

Start of a multi-part VectorBT cookbook focused on practical backtesting workflows.

Continue the VectorBT cookbook with additional strategy construction examples.

Expand the cookbook workflow with more VectorBT backtesting patterns.

Work through further practical VectorBT backtesting examples.

Complete the VectorBT cookbook series with additional applied examples.

A PyQuant News walkthrough of large-scale VectorBT simulation.

A beginner-oriented walkthrough of setting up and running VectorBT backtests.

Build a first trading model in Python using VectorBT.

Use VectorBT to grid-search entry and exit parameters and visualize the results.

Learn the IndicatorFactory workflow for custom VectorBT indicators.

Combine RSI, moving averages, and custom logic into a VectorBT strategy.

Build custom Plotly views and portfolio dashboards from VectorBT objects.

Detect candlestick patterns with TA-Lib and backtest the signals in VectorBT.

A comparison of VectorBT and Backtrader for Python backtesting workflows.

An overview of VectorBT's vectorized approach to fast strategy backtesting.

Explore VectorBT as a fast Python engine for strategy discovery and testing.

A high-level explanation of VectorBT's role in fast quantitative research.

Run a compact VectorBT grid search using MultiIndex signal arrays.

Build and test a simple ETH trend-following strategy with VectorBT.

Implement a momentum-squeeze strategy and backtest it with VectorBT.

Parameter-sweep an EMA and ATR breakout strategy with an ADX filter.

Combine AO Twin Peaks, market structure breaks, and ATR trailing stops.

Analyze trading signals with Marimo and VectorBT PRO.

Use VectorBT PRO to algorithmically find chart patterns at scale.

Backtest intraday trading strategies with VectorBT PRO.

Use cross-validation to improve strategy parameter selection.

Use VectorBT PRO to build and test a large-universe pairs-trading workflow.

Project future price segments from historical pattern matches.