Trading research,
tested and explained
Choose a research platform, test a trading idea, inspect its assumptions, and understand when a programmable workflow gives you more control.
Choose a backtesting tool
No tool is best at everything. These are practical starting points for four common kinds of research and trading work.
Explore many assets and settings
Start with VectorBT when the work includes labeled parameter grids, portfolio rules, and analysis across many assets.
Explore tool Detailed executionModel market events and orders
Consider NautilusTrader when event order, detailed fills, and a path to live trading matter most.
Explore tool Small first projectTest one instrument clearly
Backtesting.py keeps a bar-based strategy compact when one instrument and a simple cash account cover the question.
Explore tool Crypto botMove from candles to a dry run
Freqtrade combines candle backtests, parameter search, practice trading, and supported exchange connections.
Explore toolWhat do you want to learn?
Start with a review or guide, open a comparison, look up a concept, explore a tool, or inspect a benchmark.
1 Review
Read reviews of new models and ideas, the published results, and what remains uncertain.
Explore5 Guides
Learn how to test an idea and move it toward live trading.
Explore10 Comparisons
See how popular tools differ and which one fits your work.
Explore26 Concepts
Understand common mistakes, risk, orders, and performance.
Explore16 Tools
Explore each tool through explanations, code, strengths, and limits.
Explore7 Benchmarks
See measured results and download the evidence behind them.
ExploreBrowse tools
Each tool page explains what it does, includes a working example, and covers its strengths, limits, and license.
Head-to-head comparisons
VectorBT PRO vs VectorBT
VectorBT provides fast labeled strategy and portfolio tests. VectorBT PRO adds more validation methods, resumable large runs, live updates, standalone Rust, and more ways to search its documentation.
Read comparisonVectorized vs event-driven backtesting
Vectorized backtests process many values together. Event-driven backtests process one event after another. Many modern tools combine both.
Read comparisonVectorBT PRO vs NautilusTrader
VectorBT PRO covers broad, fast research. NautilusTrader covers detailed market replay and live exchange connections.
Read comparisonNautilusTrader vs LEAN
NautilusTrader focuses on detailed market events and orders. LEAN covers more asset classes and can be paired with QuantConnect's cloud platform.
Read comparisonVectorBT PRO vs Backtesting.py
VectorBT PRO handles broad and detailed strategy research. Backtesting.py is a small, approachable backtester for one instrument at a time.
Read comparisonVectorBT PRO vs LEAN and QuantConnect
VectorBT PRO supports broad strategy research in Python and Rust. LEAN is a trading engine, while QuantConnect adds cloud data and live tools.
Read comparisonVectorBT vs Backtrader
VectorBT quickly compares many strategy settings. Backtrader expresses bar-by-bar strategy and broker rules clearly, but is no longer actively maintained.
Read comparisonFreqtrade vs Jesse
Freqtrade includes an open path from backtesting to live trading. Jesse has a focused research API and adds live trading through a paid plugin.
Read comparisonPyBroker vs FinRL
PyBroker tests prediction models on market bars. FinRL is for training reinforcement-learning agents in market environments.
Read comparisonZipline Reloaded vs LEAN
Zipline Reloaded is a focused local tool for equity research. LEAN covers more markets and can use QuantConnect's cloud and live-trading services.
Read comparisonGet evidence-backed quant research
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