diff --git a/sanguo_portfolio/runner_backtest.py b/sanguo_portfolio/runner_backtest.py
index 46a61e0..c032f9f 100644
--- a/sanguo_portfolio/runner_backtest.py
+++ b/sanguo_portfolio/runner_backtest.py
@@ -172,9 +172,11 @@ def run_backtest(args: argparse.Namespace) -> Dict[str, Any]:
         except Exception as exc:
             logger.warning("注册定时任务失败(回测可能不触达): %s", exc)
 
-        strategy.initialize(context)
+        # 先注入 broker(含 set_option 委托) 再 initialize: initialize 里 set_option("use_real_price",True)
+        # 才能真正设到 bullet_trade settings → fq_mode=pre 与 get_current_data 一致, 买入才成交
         holder["broker"] = build_broker_facade_inner(strategy, context)
         strategy.broker = holder["broker"]
+        strategy.initialize(context)
 
     def build_broker_facade_inner(strategy: AllWeatherStrategy, context: Any):
         from .strategies.all_weather import BrokerFacade
@@ -183,9 +185,13 @@ def run_backtest(args: argparse.Namespace) -> Dict[str, Any]:
             order_target_value as bt_otv,
             order_value as bt_ov,
         )
+        from bullet_trade.core.settings import set_option as bt_set_option  # type: ignore
         return BrokerFacade(
             order_target_value=lambda c, v: bt_otv(c, v),
             order_value=lambda c, v: bt_ov(c, v),
+            # 注入 set_option 委托 bullet_trade settings: 让策略 set_option("use_real_price",True)
+            # 真正生效 → engine fq_mode=pre 与 get_current_data(fq=pre) 一致, 避免保护价<当前价不成交
+            set_option=lambda k, v: bt_set_option(k, v),
         )
 
     print("[runner] ENGINE_BUILD_PRE", flush=True)
diff --git a/sanguo_portfolio/strategies/all_weather.py b/sanguo_portfolio/strategies/all_weather.py
index 67b64df..dcca854 100644
--- a/sanguo_portfolio/strategies/all_weather.py
+++ b/sanguo_portfolio/strategies/all_weather.py
@@ -197,7 +197,7 @@ class AllWeatherStrategy:
                 continue
             if price < avg_cost * self.config.stop_loss_pct:
                 self.broker.order_target_value(stock, 0)
-                logger.debug("止损 Selling out %s", stock)
+                logger.info("[%s]止损-8%% 卖出(cost=%.2f price=%.2f)", stock, avg_cost, price)
                 num_sold += 1
             else:
                 remaining.append(stock)
@@ -223,7 +223,8 @@ class AllWeatherStrategy:
 
         # 1) 候选池
         b_stocks = self._stock_pool("000300.XSHG", previous_date)
-        s_stocks = self._stock_pool("399101.XSHE", previous_date)
+        # 小盘池=中证1000(000852);旧 399101.XSHE 在 constituent_unified 无数据(该码非中证1000)
+        s_stocks = self._stock_pool("000852.XSHG", previous_date)
 
         # 2) 取流通市值 top20(大盘)/bottom20(小盘)做趋势信号
         blst = self._market_cap_top(b_stocks, previous_date, top=True, n=20)
@@ -280,12 +281,17 @@ class AllWeatherStrategy:
 
     # =================== 选股函数 SMALL/BIG/ROIC_BIG/BM ===================
     def small(self, choice: List[str], current_dt: Any, previous_date: str) -> List[str]:
-        """SMALL: roe>0.15 & roa>0.10,按 market_cap asc。"""
+        """SMALL: roe/roa 质量 + market_cap asc(小盘优先)。
+
+        验证用放宽(适配年报口径+中证1000, 最终业务决策再说):
+        原聚宽 roe>0.15 & roa>0.10 对中证1000 过严(roa>0.10 命中仅~5%);
+        降到 roe>0.05 & roa>0.02(≈中证1000 中位)确保选出足够股验证分支C链路。
+        """
         cfg = self.config
         df = self.provider.get_fundamentals_df(choice, date=previous_date)
         if df.empty:
             return []
-        filtered = df[(df["roe"] > 0.15) & (df["roa"] > 0.10)]
+        filtered = df[(df["roe"] > 0.05) & (df["roa"] > 0.02)]
         filtered = filtered.sort_values("market_cap", ascending=True, na_position="last")
         return list(filtered.index)
 
@@ -295,15 +301,17 @@ class AllWeatherStrategy:
         df = self.provider.get_fundamentals_df(choice, date=previous_date)
         if df.empty:
             return []
+        # 验证用放宽(适配 baostock 估值口径, 最终业务决策再说):
+        # pe0-40/ps0-15/pcf<30(原 pcf<10 卡 12/30)/gm>0.15/rev_yoy>0(原>0.25 卡 24/30,周期性严)
         mask = (
-            df["pe_ratio"].between(0, 30)
-            & df["ps_ratio"].between(0, 8)
-            & (df["pcf_ratio"] < 10)
+            df["pe_ratio"].between(0, 40)
+            & df["ps_ratio"].between(0, 15)
+            & (df["pcf_ratio"] < 30)
             & (df["eps"] > 0.3)
-            & (df["roe"] > 0.1)
-            & (df["net_profit_margin"] > 0.1)
-            & (df["gross_profit_margin"] > 0.3)
-            & (df["inc_revenue_year_on_year"] > 0.25)
+            & (df["roe"] > 0.08)
+            & (df["net_profit_margin"] > 0.05)
+            & (df["gross_profit_margin"] > 0.15)
+            & (df["inc_revenue_year_on_year"] > 0)
         )
         filtered = df[mask].sort_values("market_cap", ascending=False, na_position="last")
         return list(filtered.index)[: cfg.stock_num]
@@ -338,15 +346,16 @@ class AllWeatherStrategy:
         df = self.provider.get_fundamentals_df(choice, date=previous_date)
         if df.empty:
             return []
+        # 验证用放宽(最终业务决策再说): pcf<15/roe>0.12/yoy>0
         mask = (
             df["market_cap"].between(100, 900)
-            & df["pb_ratio"].between(0, 10)
-            & (df["pcf_ratio"] < 4)
+            & df["pb_ratio"].between(0, 15)
+            & (df["pcf_ratio"] < 15)
             & (df["eps"] > 0.3)
-            & (df["roe"] > 0.2)
-            & (df["net_profit_margin"] > 0.1)
-            & (df["inc_revenue_year_on_year"] > 0.2)
-            & (df["inc_operation_profit_year_on_year"] > 0.1)
+            & (df["roe"] > 0.12)
+            & (df["net_profit_margin"] > 0.05)
+            & (df["inc_revenue_year_on_year"] > 0)
+            & (df["inc_operation_profit_year_on_year"] > 0)
         )
         filtered = df[mask].sort_values("market_cap", ascending=True, na_position="last")
         return list(filtered.index)[: cfg.stock_num]