BacktestBot

Backtest trading strategies against historical market data with performance analytics and risk metrics

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.