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Backtesting
Testing a strategy on historical data. Done honestly (with slippage, fees, and funding) it earns the right to paper-trade, not the right to go live.
A close-price backtest assumes you traded at the closing price with no slippage and no queue, which flatters almost any strategy. A trustworthy test crosses the spread, charges fees, and applies funding over the holding period.
Most frameworks here backtest, including Freqtrade, NautilusTrader, and Superior Trade. A clean backtest is the start of the process, not the end.
Related
- Superior Trade Managed execution, backtesting, and a deployment lifecycle behind agent-callable endpoints, with an atomic one-call exit and HIP-3 coverage. Closed core, public OpenAPI and docs.
- Freqtrade The most-used open-source crypto bot: build, backtest, hyperopt, dry-run, and run live, with an ML module (FreqAI). Now supports Hyperliquid. Not agent-callable out of the box.
- NautilusTrader High-performance event-driven engine (Rust core, Python API). Backtest and go live on the same code. Production-grade, but you wire the agent layer yourself.
- Composer No-code rules-based strategy platform with solid backtest and deploy, but built for humans more than callable agents.
What links here
Alpaca MCP · Composer · Freqtrade · HKUDS AI-Trader · Kraken CLI · NautilusTrader · Superior Trade · TradingAgents