BacktestBot

Backtest trading strategies against historical market data with detailed performance analytics.

What it does

BacktestBot enables you to define, test, and evaluate trading strategies using historical data, including:

• Strategy definition — describe strategies in natural language or structured rules (entry/exit signals, position sizing, stop losses)
• Historical simulation — run strategies against years of tick or daily data across equities, options, futures, and crypto
• Performance metrics — Sharpe ratio, max drawdown, win rate, profit factor, CAGR, and trade-level breakdown
• Risk analysis — value-at-risk, correlation to benchmarks, worst-case drawdown periods, and tail risk metrics
• Comparison — test multiple strategy variants side-by-side and rank by risk-adjusted returns

Usage

Ask your agent to backtest strategies and analyze results:

• "Backtest a mean reversion strategy on SPY using RSI below 30 as entry over the last 5 years"
• "Compare buy-and-hold vs momentum rotation across the S&P 500 sectors since 2020"
• "What is the max drawdown if I use a 2% trailing stop on AAPL swing trades?"
• "Optimize the lookback period for my moving average crossover strategy on QQQ"

Configuration

Set the following environment variables:

• BACKTESTBOT_API_KEY — API key for BacktestBot. Used to authenticate requests for historical OHLCV data, strategy simulations, and performance metrics.
• BACKTESTBOT_DATA_DIR — (optional) local directory for cached historical data. Defaults to ~/.backtestbot/data.