Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Runs trading strategy backtests by accepting natural language descriptions or structured JSON entry/exit rules. Returns Sharpe ratio, total return, max drawdown, win rate, trade count, and equity curves. Supports multi-ticker portfolios and head-to-head strategy comparison.
Removes the need for local market data, backtesting infrastructure, or strategy-coding boilerplate — you describe the strategy in plain English and get full metrics back.
When to use it
- Testing RSI mean reversion on individual stocks before paper trading
- Comparing MACD crossover against Bollinger band breakout strategies on SPY
- Backtesting a momentum portfolio across AAPL, MSFT, and GOOGL
- Validating a trading idea described in plain English without writing code
- Ranking multiple candidate strategies by Sharpe ratio to pick the best
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: backtest MACD crossover on SPY with a 20/50 EMA filter
- 1Parses the natural language strategy description and identifies indicators, tickers, and filters
- 2Sends the strategy text and ticker list to the Vynn backtest API using the configured API key
- 3Receives backtest results including Sharpe ratio, total return, max drawdown, win rate, and trade count
- 4Formats and returns the equity curve and summary metrics to the user
Sharpe ratio, annualized return %, max drawdown %, win rate, trade count, and equity curve for the MACD crossover strategy on SPY
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.