auto: 일일 백업 2026-06-10 02:00

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

agents/stock/workspace/sim/backtest.py

@@ -14,9 +14,22 @@ from __future__ import annotations
 import math
 import sqlite3
 import sys
+from datetime import datetime
 
 from . import config, signals
 
+
+def _cal_days(entry_date: str | None, cur_date: str) -> int | None:
+    """두 'YYYYMMDD' 사이 달력 일수 — 시간손절용. 파싱 실패 시 None."""
+    if not entry_date:
+        return None
+    try:
+        d0 = datetime.strptime(entry_date, '%Y%m%d')
+        d1 = datetime.strptime(cur_date, '%Y%m%d')
+        return max(0, (d1 - d0).days)
+    except Exception:
+        return None
+
 sys.path.insert(0, str(config.SCRIPTS))
 import daily_candles_cache as dcc  # noqa: E402
 
@@ -111,7 +124,8 @@ def run(overrides: dict | None, codes: list[str], date_from: str = '', date_to:
             dates_seen = [c['date'] for c in h[:i + 1]]
             flow = _flow_net_upto(flows.get(code), dates_seen)
             pos = positions[code]
-            dec = signals.evaluate_holding(pos, ind, flow, None)
+            dec = signals.evaluate_holding(pos, ind, flow, None,
+                                           held_days=_cal_days(pos.get('entry_date'), day))
             pos.update(dec['position_update'])
             act = dec['action']
             if act in ('sell', 'scale_out'):
@@ -170,18 +184,18 @@ def run(overrides: dict | None, codes: list[str], date_from: str = '', date_to:
             dec = signals.evaluate_candidate(code, code, [], ind, flow, None, True)
             if dec['action'] == 'buy':
                 fill = dec['buy_price']
+                stop, target = signals.compute_stop_target(fill, ind['atr'], ind['recent_low'])
                 eq = equity(day_prices)
-                tranche_val = (eq / config.MAX_POSITIONS) / max(1, config.ENTRY_TRANCHES)
+                tranche_val = signals.target_value(eq, fill, stop) / max(1, config.ENTRY_TRANCHES)
                 qty = _qty_for(fill, tranche_val)
                 cost = qty * fill * (1 + comm)
                 if qty < 1 or cost > cash:
                     continue
-                stop, target = signals.compute_stop_target(fill, ind['atr'], ind['recent_low'])
                 cash -= cost
                 positions[code] = {'code': code, 'name': code, 'qty': qty, 'entry_price': fill,
                                    'stop': stop, 'target': target, 'peak': fill, 'trailing_on': False,
                                    'scaled_out': False, 'tranches': 1, 'tranche_value': tranche_val,
-                                   'last_add_price': fill}
+                                   'last_add_price': fill, 'entry_date': day}
 
         eq = equity(day_prices)
         if eq > peak_eq: