stock/.opencode/skills/stock-backtest/SKILL.md

name, description

name	description
stock-backtest	Design, run, and interpret strategy backtests for A-share stocks

What I Do

Guide the agent through backtesting trading strategies:

1. Help design strategy rules from user descriptions
2. Run backtests on historical data
3. Interpret results and identify potential issues
4. Suggest improvements

Capital Context (CRITICAL)

The user has ~5万 RMB capital. Backtest interpretation must be capital-aware:

• When presenting metrics, translate key numbers to the user's context:
  • "Annualized return 15% = ¥7,500 on 5万"
  • "Max drawdown 12% = ¥6,000 worst-case loss"
  • "Average win ¥800, average loss ¥1,200 per trade"
• Assess whether a strategy is practically usable with 5万 considering position sizing constraints
• Flag if a strategy requires more positions than 5万 can support

Key Backtest Metrics

• Cumulative return: total return over the period
• Annualized return: normalized yearly return (translate to ¥ on 5万)
• Win rate: percentage of profitable trades
• Max drawdown: worst peak-to-trough decline (translate to ¥)
• Sharpe ratio: risk-adjusted return
• Benchmark comparison: vs CSI 300 index

Strategy Parameters

Common strategy elements to help users define:

• Entry conditions (e.g., MA crossover, breakout, pullback)
• Exit conditions (e.g., stop loss %, take profit %, trailing stop, time-based)
• Position sizing (e.g., fixed %, Kelly fraction)
• Test period and stock universe

When to Use Me

Use when the user asks to:

• Backtest a trading strategy
• Verify a strategy's historical performance
• Compare multiple strategies
• Evaluate whether a strategy is worth using

Workflow

1. Clarify strategy rules with user
2. Translate rules into testable parameters
3. Run backtest via stock-backtest tools
4. Present results with interpretation:

Output Format

1. Strategy Summary: rules in plain language
2. Performance Metrics: all key metrics in table form
3. Capital Context Translation:

   Metric	Value	On 5万 Capital
   Annualized Return	18%	¥9,000/year
   Max Drawdown	15%	¥7,500 worst case
   Avg Win per Trade	¥450	—
   Avg Loss per Trade	¥600	—

4. Equity Curve Description: shape, drawdown periods, recovery time
5. Benchmark Comparison: outperformance/underperformance vs CSI 300
6. Practicality Assessment for 5万:
   • Can the user afford the position sizes?
   • Does the strategy require too many concurrent positions?
   • Is the max drawdown psychologically tolerable?
7. Potential Concerns: overfitting, look-ahead bias, survivorship bias, regime dependence

Risk Disclaimer

Always remind: backtest results reflect historical data. Live performance will differ. Strategies can fail in new market regimes. The user bears all trading risk.