Feature Iteration Run #1054: zz_sylvain

# AUTOLOOP: zz_sylvain (8 iterations)

> **Phase**: Y4.7 Option B (DSL → Python code → FeatureSet candidate)
> **Target indicator**: zz_sylvain
> **Base feature_set_id**: 1387
> **Claim**: (default) Propose a new k_* feature that improves risk-adjusted returns
> **Objective mode**: scalarize
> **Metrics**: ['profit_factor', 'sharpe_ratio', 'win_rate', 'max_drawdown', 'test_accuracy']
> **Total duration**: 398.03s
> **Total accepted**: 1
> **Total rejected**: 7

## Iterations 詳情

### Iteration 1
- DSL: `obv_ensemble_3 * (1 - hl_range) / (1 + atr_norm) * (1 - price_position) * (1 - return_5)` (feature=k_loop_iter_1_d93449)
- DSL valid: True
- FeatureSet candidate id: 1386
- baseline PF: 1.947 → modified PF: 1.085
- t_stat: 0.000, p_value: 0.463, cohens_d: 0.243
- scalar_score: -0.4789
- accepted: False, reason: scalar_score -0.4789 <= 0.0, sharpe_delta -16.8215 < -0.3, hypothesis test not confirmed

**Metrics summary:**
  - profit_factor: baseline=1.947, modified=1.085, diff=-0.862
  - sharpe_ratio: baseline=19.162, modified=2.341, diff=-16.821
  - win_rate: baseline=0.600, modified=0.500, diff=-0.100
  - max_drawdown: baseline=0.056, modified=0.187, diff=0.131
  - test_accuracy: baseline=0.992, modified=0.992, diff=-0.000

### Iteration 2
- DSL: `k_high.pct_change(12) * (1 + hl_range) / (1 + atr_norm) * (1 - price_position) * (1 - return_5)` (feature=k_loop_iter_2_39bce4)
- DSL valid: True
- FeatureSet candidate id: 1387
- baseline PF: 1.947 → modified PF: 2.466
- t_stat: 0.000, p_value: 0.012, cohens_d: 0.388
- scalar_score: 1.4881
- accepted: True, reason: accepted

**Metrics summary:**
  - profit_factor: baseline=1.947, modified=2.466, diff=0.519
  - sharpe_ratio: baseline=19.162, modified=24.727, diff=5.565
  - win_rate: baseline=0.600, modified=0.636, diff=0.036
  - max_drawdown: baseline=0.056, modified=0.050, diff=-0.006
  - test_accuracy: baseline=0.992, modified=0.992, diff=-0.000

### Iteration 3
- DSL: `k_high.pct_change(12) * (1 + hl_range) * (1 - price_position) * i_rsi(k_close, 14) / 100` (feature=k_iter3_k_high_pct_change_hl_range_price_position)
- DSL valid: False
- FeatureSet candidate id: None
- baseline PF: 0.000 → modified PF: 0.000
- t_stat: 0.000, p_value: 1.000, cohens_d: 0.000
- scalar_score: 0.0000
- accepted: False, reason: quality_gate: NaN ratio 1.000 exceeds 0.3

### Iteration 4
- DSL: `k_high.pct_change(12) * (1 + hl_range) * (1 - k_close_position_in_hl) / (1 + atr_norm * 10) * i_rsi(k_close, 14) / 100` (feature=k_iter4_k_high_pct_change_hl_range_k_close_position_in_)
- DSL valid: False
- FeatureSet candidate id: None
- baseline PF: 0.000 → modified PF: 0.000
- t_stat: 0.000, p_value: 1.000, cohens_d: 0.000
- scalar_score: 0.0000
- accepted: False, reason: safe_eval DSL: 變數未定義: k_close_position_in_hl

### Iteration 5
- DSL: `k_high.pct_change(12) * (1 - price_position) * (1 - return_5) / (1 + atr_norm * 10) + k_momentum_pct_change * obv_ensemble_3 / (1 + atr_norm * 10)` (feature=k_loop_iter_5_ad427a)
- DSL valid: True
- FeatureSet candidate id: 1388
- baseline PF: 2.466 → modified PF: 1.512
- t_stat: 0.000, p_value: 0.001, cohens_d: 0.646
- scalar_score: -3.7887
- accepted: False, reason: scalar_score -3.7887 <= 0.0, sharpe_delta -13.0368 < -0.3, hypothesis test not confirmed

**Metrics summary:**
  - profit_factor: baseline=2.466, modified=1.512, diff=-0.954
  - sharpe_ratio: baseline=24.727, modified=11.690, diff=-13.037
  - win_rate: baseline=0.636, modified=0.538, diff=-0.098
  - max_drawdown: baseline=0.050, modified=0.135, diff=0.085
  - test_accuracy: baseline=0.992, modified=0.992, diff=-0.000

### Iteration 6
- DSL: `obv_rebased.pct_change * (1 + hl_range) * (1 - price_position) / (1 + atr_norm)` (feature=k_iter6_pct_change_hl_range_price_position_atr_norm)
- DSL valid: False
- FeatureSet candidate id: None
- baseline PF: 0.000 → modified PF: 0.000
- t_stat: 0.000, p_value: 1.000, cohens_d: 0.000
- scalar_score: 0.0000
- accepted: False, reason: safe_eval DSL triggered unexpected TypeError: unsupported operand type(s) for *: 'method' and 'float'

### Iteration 7
- DSL: `k_high.pct_change(12) * (1 - price_position) * i_macd(k_close, 12, 26, 9) / (1 + atr_norm * 10)` (feature=k_loop_iter_7_30d194)
- DSL valid: True
- FeatureSet candidate id: 1389
- baseline PF: 2.466 → modified PF: 1.215
- t_stat: 0.000, p_value: 0.000, cohens_d: 1.043
- scalar_score: -4.7600
- accepted: False, reason: scalar_score -4.7600 <= 0.0, sharpe_delta -18.5347 < -0.3, hypothesis test not confirmed

**Metrics summary:**
  - profit_factor: baseline=2.466, modified=1.215, diff=-1.251
  - sharpe_ratio: baseline=24.727, modified=6.193, diff=-18.535
  - win_rate: baseline=0.636, modified=0.495, diff=-0.141
  - max_drawdown: baseline=0.050, modified=0.289, diff=0.239
  - test_accuracy: baseline=0.992, modified=0.974, diff=-0.018

### Iteration 8
- DSL: `k_high.pct_change(12) * (1 + hl_range) * (1 - price_position) * (1 - return_5) / (1 + atr_norm)` (feature=k_loop_iter_8_6b4e6f)
- DSL valid: True
- FeatureSet candidate id: 1390
- baseline PF: 2.466 → modified PF: 1.512
- t_stat: 0.000, p_value: 0.001, cohens_d: 0.646
- scalar_score: -3.7887
- accepted: False, reason: scalar_score -3.7887 <= 0.0, sharpe_delta -13.0368 < -0.3, hypothesis test not confirmed

**Metrics summary:**
  - profit_factor: baseline=2.466, modified=1.512, diff=-0.954
  - sharpe_ratio: baseline=24.727, modified=11.690, diff=-13.037
  - win_rate: baseline=0.636, modified=0.538, diff=-0.098
  - max_drawdown: baseline=0.050, modified=0.135, diff=0.085
  - test_accuracy: baseline=0.992, modified=0.992, diff=-0.000