openbb-invest-api/openclaw-skills/strategy-backtest/SKILL.md

name, description, user-invocable, metadata

name	description	user-invocable	metadata
strategy-backtest	Strategy backtesting — test SMA crossover, RSI, buy-and-hold, momentum strategies against historical data. Use when user wants to validate a trading idea or compare strategies.	true	openclaw emoji requires 🧪 bins curl

Strategy Backtest

Professional backtesting for strategy validation. Think like a quant researcher — data over intuition.

Trigger: User says "backtest", "test this strategy", "would this have worked", "compare strategies", or wants to validate a trade-analyze recommendation.

Available Strategies

1. SMA Crossover (trend-following)

When short SMA crosses above long SMA → buy. Crosses below → sell.

BASE=https://invest-api.k8s.home

curl -sk -X POST "$BASE/api/v1/backtest/sma-crossover" \
  -H "Content-Type: application/json" \
  -d '{"symbol": "{TICKER}", "short_window": 20, "long_window": 50, "days": 365, "initial_capital": 10000}'

Best for: trending markets, medium-term holds. Weak in: sideways/choppy markets (many false signals).

2. RSI Mean Reversion

Buy when RSI < oversold threshold, sell when RSI > overbought threshold.

curl -sk -X POST "$BASE/api/v1/backtest/rsi" \
  -H "Content-Type: application/json" \
  -d '{"symbol": "{TICKER}", "period": 14, "oversold": 30, "overbought": 70, "days": 365, "initial_capital": 10000}'

Best for: range-bound stocks, mean-reverting behavior. Weak in: strong trends (catches falling knives).

3. Buy and Hold (benchmark)

Always run this as the baseline comparison.

curl -sk -X POST "$BASE/api/v1/backtest/buy-and-hold" \
  -H "Content-Type: application/json" \
  -d '{"symbol": "{TICKER}", "days": 365, "initial_capital": 10000}'

4. Momentum (multi-stock rotation)

Rank stocks by recent performance, hold top N, rebalance periodically.

curl -sk -X POST "$BASE/api/v1/backtest/momentum" \
  -H "Content-Type: application/json" \
  -d '{"symbols": ["AAPL","MSFT","GOOGL","AMZN","NVDA","META","TSLA","JPM","V","WMT"], "lookback": 60, "top_n": 3, "rebalance_days": 30, "days": 365, "initial_capital": 10000}'

Best for: diversified portfolios, capturing sector rotation.

Standard Workflow

Always run all 3 single-stock strategies + buy-and-hold for comparison:

# Run all 4 in one go
curl -sk -X POST "$BASE/api/v1/backtest/buy-and-hold" -H "Content-Type: application/json" -d '{"symbol":"{TICKER}","days":365,"initial_capital":10000}'
curl -sk -X POST "$BASE/api/v1/backtest/sma-crossover" -H "Content-Type: application/json" -d '{"symbol":"{TICKER}","short_window":20,"long_window":50,"days":365,"initial_capital":10000}'
curl -sk -X POST "$BASE/api/v1/backtest/rsi" -H "Content-Type: application/json" -d '{"symbol":"{TICKER}","period":14,"oversold":30,"overbought":70,"days":365,"initial_capital":10000}'

Report Structure

## {TICKER} Strategy Backtest — {date}
### Period: {start_date} to {end_date} ({days} days)
### Initial Capital: $10,000

### Strategy Comparison
| Strategy | Return | Sharpe | Max DD | Win Rate | Trades |
|----------|--------|--------|--------|----------|--------|
| Buy & Hold | {%} | {val} | {%} | N/A | 1 |
| SMA 20/50 | {%} | {val} | {%} | {%} | {n} |
| RSI 14/30/70 | {%} | {val} | {%} | {%} | {n} |

### Winner: {strategy name}
- Outperformed buy-and-hold by: {%}
- Key advantage: {why it worked for this stock}

### Equity Curve Summary
- Buy & Hold final: ${value}
- Best strategy final: ${value}
- Worst drawdown period: {date range}

### Strategy Suitability for {TICKER}
- Stock behavior: [trending / mean-reverting / choppy]
- Best fit: {strategy} because {reason}
- Avoid: {strategy} because {reason}

### ⚠️ Backtest Caveats
- No transaction costs or slippage included
- Past performance ≠ future results
- Optimized parameters may overfit
- Consider out-of-sample testing (different time period)

Validation Workflow (after /trade-analyze)

When used to validate a trade-analyze recommendation:

1. Run buy-and-hold for baseline
2. If trade-analyze recommended BUY based on technical signals:
   • Run SMA crossover to see if trend-following would have worked
   • Run RSI to see if mean-reversion entries would have worked
3. Compare Sharpe ratios and max drawdowns
4. Conclusion: "The data {supports / does not support} the trade-analyze recommendation because {reason}"

Rules

• Always include buy-and-hold as benchmark — any strategy must beat it
• Sharpe > 1.0 = good risk-adjusted returns
• Max drawdown > 20% = strategy needs tighter risk management
• Win rate < 40% can still be profitable if average win >> average loss
• If all strategies underperform buy-and-hold → the stock rewards patience, not trading
• Keep under 500 words