20260114_055743_crash_bounce_hedge.md

# AI Review: crash_bounce_hedge **Date:** Wed Jan 14 05:57:43 CET 2026 **Strategy File:** /root/trade_rules/strategies/crash_bounce_hedge.py --- ```json { "score": 45, "flags": ["overfitting", "complexity", "inconsistent", "concentration"], "review": "## Strategy Assessment: crash_bounce_hedge\n\n### Role Compliance (hedge)\n- **Val Return**: 3.9% ✓ (exceeds 0% minimum)\n- **Val Sharpe**: -0.08 ✗ (fails 0.3 minimum requirement)\n- **Trades**: Appears sufficient ✓\n- **Issue**: While validation return is positive, the Sharpe ratio indicates the strategy is too volatile/risky for a hedge role\n\n### Year-over-Year Consistency Analysis\n**Major Red Flag**: Highly inconsistent performance across years:\n- 2020-2023: Mostly negative or flat (-12.5%, -1.5%, -0.4%, +0.8%)\n- 2024-2025: Suddenly profitable (+4.7%, +7.3%)\n- Sharpe ratios swing wildly: from -0.90 to +0.61\n\nThis suggests the strategy may have accidentally captured regime-specific patterns rather than robust crash-bounce dynamics. The poor performance in 2022 (a major crash year) is particularly concerning for a \"crash bounce\" strategy.\n\n### Overfitting Concerns\n\n1. **Too Many Conditions (5 entry filters)**:\n - Drop percentage check\n - RSI oversold\n - Capitulation wick pattern\n - Volume threshold\n - Bar range requirement\n \n This creates a highly specific \"needle in haystack\" setup that may not recur reliably.\n\n2. **Non-Standard Parameters**:\n - `min_drop_pct: 10` - Not a rounded standard value (should be 10, 15, 20, etc. ✓ this one is okay)\n - `rsi_exit: 55` - Non-standard (should be 50 or 60)\n - `min_wick_ratio: 0.25` - Precise ratio suggests curve-fitting\n - `vol_threshold: 1.3` - Should be rounded to 1.5 or 2.0\n - `take_profit: 10, stop_loss: 4` - The 10:4 ratio seems optimized\n\n3. **Complex Capitulation Detection**:\n The wick ratio calculation (lower_wick / bar_range > 0.25) combined with range percentage is a very specific pattern that may not generalize.\n\n### Execution Issues\n\n- **Exit Logic Flaw**: \"Two consecutive green candles\" is checked within the same bar loop, creating potential same-candle execution if the current bar is the second green candle\n- **State Management**: The `green_count` resets to 0 on red candles, which is correct, but the consecutive green exit may trigger too quickly in choppy bounces\n\n### Concentration Risk\n\nWith only 89-103 total trades across 5+ years and highly variable year-to-year returns, there's significant risk that a small number of trades in 2024-2025 drive all the positive performance. The strategy appears to work well in some market conditions but fails in others (notably 2022's bear market).\n\n### Strategy Concept Issues\n\n**Philosophical Problem**: A \"hedge\" strategy should protect during crashes, not bet on bounces AFTER crashes. By the time all 5 conditions are met (10% drop, RSI<30, capitulation wick, high volume, large range), the crash may already be priced in. True hedge strategies are often short or inverse correlation plays.\n\nThe -12.5% return in 2022 suggests this isn't hedging anything—it's a tactical long-only bounce trader that only works in certain market structures.\n\n### Positive Aspects\n\n- Proper warmup period (100 bars)\n- No lookahead bias detected\n- Reasonable stop loss / take profit structure\n- Attempts to capture a real phenomenon (capitulation bounces)\n\n### Recommendation\n\n**Reject or Major Revision Required**. While the strategy passes the validation return threshold, it fails the Sharpe requirement for hedge strategies and shows concerning regime-dependency. The complexity (5+ conditions) and inconsistent year-over-year performance suggest this is curve-fit to recent market behavior rather than capturing a robust edge.", "rule_suggestion": "Add constraint: Strategies must show consistent profitability OR consistent loss mitigation across at least 3 out of 5 years in the train period. Avoid strategies where performance is concentrated in the most recent 1-2 years, as this suggests recency bias. For hedge strategies specifically, require that the strategy performs its hedging function (positive returns or reduced drawdowns) during known adverse market conditions within the train period." } ```