feat: add quant layer, portfolio-review, and strategy-backtest skills

fundamental-analysis: added statistical risk layer
- normality test (Jarque-Bera) — validates Sharpe/VaR reliability
- unit root test (ADF) — validates technical analysis applicability
- rolling skew/kurtosis — tail risk monitoring
- interpretation rules for crash risk detection

portfolio-review (NEW): portfolio health check and similarity search
- HRP optimization, correlation matrix, risk parity weights
- t-SNE clustering for hidden correlations
- stock similarity search for diversification
- rule-engine BUY_MORE/HOLD/SELL per holding

strategy-backtest (NEW): historical strategy validation
- SMA crossover, RSI mean-reversion, buy-and-hold, momentum
- comparison framework with Sharpe, max DD, win rate
- validation workflow for trade-analyze recommendations

Coverage: 67% → 79% of API endpoints (104/131)

openclaw-skills/strategy-backtest/SKILL.md

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+---
+name: strategy-backtest
+description: "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."
+user-invocable: true
+metadata: { "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.
+
+```bash
+BASE=https://invest-api.k8s.home
+
+curl -sk -X POST "$BASE/api/v1/backtest/sma-crossover" \
+  -H "Content-Type: application/json" \
+  -d '{"symbol": "{TICKER}", "short_window": 20, "long_window": 50, "days": 365, "initial_capital": 10000}'
+```
+
+Best for: trending markets, medium-term holds.
+Weak in: sideways/choppy markets (many false signals).
+
+### 2. RSI Mean Reversion
+
+Buy when RSI < oversold threshold, sell when RSI > overbought threshold.
+
+```bash
+curl -sk -X POST "$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.
+
+```bash
+curl -sk -X POST "$BASE/api/v1/backtest/buy-and-hold" \
+  -H "Content-Type: application/json" \
+  -d '{"symbol": "{TICKER}", "days": 365, "initial_capital": 10000}'
+```
+
+### 4. Momentum (multi-stock rotation)
+
+Rank stocks by recent performance, hold top N, rebalance periodically.
+
+```bash
+curl -sk -X POST "$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:**
+
+```bash
+# 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