Binance
Broad liquidity and many pairs make it useful for cross-sectional research, but leverage, funding, and regional access assumptions must be handled carefully.
Interactive research tool
Crypto Strategy Lab
Compare educational AI-quant strategy assumptions across Binance, OKX, Bybit, and Coinbase-style markets. The backtest uses deterministic simulated data so readers can study methodology without mistaking results for live signals.
Backtest controls
Configure a research scenario
This is an educational simulator. It does not fetch live exchange data, place orders, or recommend trades.
Tip: the page URL stores your settings (exchange, strategy, asset, controls) so you can bookmark or share a research scenario.
Share presets: Trend / BTC Funding / ETH Mean / SOL
Simulated data uses deterministic pseudo-random paths seeded by exchange and asset. Results are for learning about backtest mechanics only.
Total Return --
Max Drawdown --
Sharpe-style --
Trades --
Sim. Costs --
Funding Carry --
Assumptions snapshot
These are simplified, educational assumptions for comparing methodology. Real-world execution costs depend on fee tier, order type, venue microstructure, and market regime.
Scenario Notes
Choose settings and run the backtest to see exchange assumptions, strategy logic, and risk interpretation.
Exchange strategy notes
How the four platform profiles differ
The tool models platform differences as assumptions. Real trading would require live data, account permissions, API monitoring, exchange-specific fees, and strict operational controls.
OKX
Spot and derivatives depth can support funding and basis research, with attention to contract specifications and API timing.
Bybit
Derivatives-heavy assumptions fit funding pressure and momentum research, but liquidation cycles and leverage risk should be central to testing.
Coinbase
A spot-oriented profile suits lower-leverage research and cleaner custody assumptions, with fewer perpetual funding features in the model.