feat(옵투나·웹): 후처리 재탐색·ob_modes·적용감사·수집통계

- Optuna web jobs/TPE/apply snapshot·틱로더 정합, jobs limit·감사로그
- 백테 UI 호가모드·후보 적용 흐름, feed_collect_stats API/탭
- 가설검증·교차검증 룰, 4전략 스모크·OB slot41 진단 스크립트

Co-authored-by: Cursor <cursoragent@cursor.com>

kis_trader/backtest/optuna_tail_tpe_space.py

@@ -14,12 +14,16 @@ from typing import Any, Dict, List, Optional
 import optuna
 
 from kis_trader.backtest.optuna_tpe_common import (
+    ORDERBOOK_TPE_AXIS_KEYS,
     RATCHET_TPE_AXIS_KEYS,
+    WHIPSAW_TPE_AXIS_KEYS,
     r1,
     r2,
     r3,
     r4,
+    suggest_orderbook_entry_tpe,
     suggest_ratchet_tiers_pct,
+    suggest_whipsaw_tpe,
 )
 
 # 래칫: 꼬리는 소폭 % (기존 메뉴 0.3~2.0 대역) — 숫자축 + 조립 문자열
@@ -60,13 +64,14 @@ _TAIL_BASE_KEYS: List[str] = [
     "pattern_morning_star",
     # 당일손익 다단트레일(trail_tiers/drop/arm) — 운영 리스크 손잡이. TPE·apply 탐색 제외(DB/UI 고정).
     "max_loss_krw",
-    "whipsaw_enabled",
-    "whipsaw_subbar_sec",
-    "whipsaw_lookback_sec",
-    "whipsaw_dip_pct",
-    "whipsaw_recovery_tol_pct",
 ]
-TAIL_TPE_AXIS_KEYS: List[str] = list(_TAIL_BASE_KEYS) + list(RATCHET_TPE_AXIS_KEYS)
+# 휩쏘 키는 WHIPSAW_TPE_AXIS_KEYS 와 동일 (아래 합침)
+TAIL_TPE_AXIS_KEYS: List[str] = (
+    list(_TAIL_BASE_KEYS)
+    + list(RATCHET_TPE_AXIS_KEYS)
+    + list(ORDERBOOK_TPE_AXIS_KEYS)
+    + list(WHIPSAW_TPE_AXIS_KEYS)
+)
 
 
 def tail_tpe_axis_keys(entry_mode: Optional[str] = None) -> List[str]:
@@ -176,22 +181,9 @@ def suggest_tail_params_tpe(
 
     combo["max_loss_krw"] = trial.suggest_int("max_loss_krw", 50000, 300000, step=25000)
 
-    # 휩쏘 TRIGGER — 실매값(False/30/90/0.003/0.001) 포함. ON·OFF·초·% 축 분리.
-    combo["whipsaw_enabled"] = trial.suggest_categorical(
-        "whipsaw_enabled", [False, True],
-    )
-    combo["whipsaw_subbar_sec"] = trial.suggest_categorical(
-        "whipsaw_subbar_sec", [15, 30, 45, 60],
-    )
-    combo["whipsaw_lookback_sec"] = trial.suggest_categorical(
-        "whipsaw_lookback_sec", [60, 90, 120, 180],
-    )
-    combo["whipsaw_dip_pct"] = r4(
-        trial.suggest_float("whipsaw_dip_pct", 0.001, 0.01, step=0.001),
-    )
-    combo["whipsaw_recovery_tol_pct"] = r4(
-        trial.suggest_float("whipsaw_recovery_tol_pct", 0.0005, 0.003, step=0.0005),
-    )
+    # 호가 + 휩쏘 — 본 trial 엔진 경로 (휩쏘는 꼬리 필수 축)
+    combo.update(suggest_orderbook_entry_tpe(trial))
+    combo.update(suggest_whipsaw_tpe(trial, force=True))
 
     combo["skip_hts_scan_dupes"] = False