feat(quant): M7.3 研究行情口径显式化（默认不复权 none，可切 qfq）

- DailyBarRepository.get_range_many / stream_range_many_columns 增加 adjust 参数
  （默认 'none'）→ SQL 层过滤口径，消除 stock_daily 混 source/adjust 污染因子的风险
- ResearchSpec / SelectionQuery 增加 price_adjustment（none|qfq），随 config_snapshot
  落库可溯源；ResearchService._load_daily 与 SelectionService 装配按口径取数
- tests/test_price_adjustment.py：repo 读取按 adjust 过滤（none/qfq 各自命中）、
  spec 默认与字段记录；全量 pytest 通过

backend/app/application/services/selection_service.py

@@ -62,6 +62,7 @@ class SelectionService:
             as_of - timedelta(days=query.warmup_days),
             as_of,
             columns,
+            adjust=query.price_adjustment,
         )
         financial: dict[str, FinancialIndicator] = {}
         if query.method == "condition" and self._uses_fundamental(query):

backend/app/domain/entities/research.py

@@ -62,6 +62,10 @@ class ResearchSpec(BaseModel):
 
     type: str = Field(default="backtest", pattern="^(factor_test|backtest)$")
     universe: UniverseSpec = UniverseSpec()
+    price_adjustment: str = Field(
+        default="none", pattern="^(none|qfq)$",
+        description="研究行情口径：none 不复权（默认）/ qfq 前复权（result 与 config_snapshot 中显式）",
+    )
     factors: list[FactorSpec] = Field(min_length=1)
     selection: SelectionSpec = SelectionSpec()
     rebalance: str = Field(default="monthly", pattern="^(weekly|monthly)$")

backend/app/domain/entities/selection.py

@@ -25,6 +25,10 @@ class SelectionQuery(BaseModel):
     """一次选股查询（v2 §14.2 Selection 输入）。"""
 
     universe: UniverseSpec = UniverseSpec()
+    price_adjustment: str = Field(
+        default="none", pattern="^(none|qfq)$",
+        description="行情口径：none 不复权（默认）/ qfq 前复权（结果 config_snapshot 中显式）",
+    )
     # 研究时点：None → 引擎用 <= 今天最近可用交易日；显式给历史日期即做历史选股
     as_of: date | None = Field(
         default=None, description="选股时点；历史回测/解释用具体日期，当前选股可留空"

backend/app/domain/repositories/market.py

@@ -42,8 +42,14 @@ class DailyBarRepository(Protocol):
 
     def get_range(self, symbol: str, start: date, end: date) -> list[DailyBar]: ...
 
-    def get_range_many(self, symbols: Sequence[str], start: date, end: date) -> list[DailyBar]:
+    def get_range_many(
-        """批量区间查询（研究服务装配面板用，避免逐只查询）。"""
+        self,
+        symbols: Sequence[str],
+        start: date,
+        end: date,
+        adjust: str = "none",
+    ) -> list[DailyBar]:
+        """批量区间查询（研究装配面板用）；adjust 指定行情口径（none 不复权 / qfq）。"""
 
     def stream_range_many_columns(
         self,
@@ -51,6 +57,7 @@ class DailyBarRepository(Protocol):
         start: date,
         end: date,
         columns: Sequence[str],
+        adjust: str = "none",
     ) -> Iterator[tuple]:
         """流式（分批 yield）返回 symbol, trade_date(iso str), 数值列(float) 元组。
 

backend/app/infrastructure/persistence/sqlalchemy/repositories/market_impl.py

@@ -158,16 +158,24 @@ class SqlAlchemyDailyBarRepository:
         ).all()
         return [DailyBar.model_validate(r, from_attributes=True) for r in rows]
 
-    def get_range_many(self, symbols: Sequence[str], start: date, end: date) -> list[DailyBar]:
+    def get_range_many(
-        rows = self._session.scalars(
+        self,
+        symbols: Sequence[str],
+        start: date,
+        end: date,
+        adjust: str = "none",
+    ) -> list[DailyBar]:
+        stmt = (
             select(StockDailyModel)
             .where(
                 StockDailyModel.symbol.in_(list(symbols)),
                 StockDailyModel.trade_date >= start,
                 StockDailyModel.trade_date <= end,
+                StockDailyModel.adjust == adjust,  # 研究主口径：不复权（v2 §8）
             )
             .order_by(StockDailyModel.trade_date)
-        ).all()
+        )
+        rows = self._session.scalars(stmt).all()
         return [DailyBar.model_validate(r, from_attributes=True) for r in rows]
 
     def stream_range_many_columns(
@@ -176,6 +184,7 @@ class SqlAlchemyDailyBarRepository:
         start: date,
         end: date,
         columns: Sequence[str],
+        adjust: str = "none",
     ) -> Iterator[tuple]:
         """流式返回 (symbol, trade_date_iso, *float_cols) 元组，分批拉取。
 
@@ -193,6 +202,7 @@ class SqlAlchemyDailyBarRepository:
                 StockDailyModel.symbol.in_(list(symbols)),
                 StockDailyModel.trade_date >= start,
                 StockDailyModel.trade_date <= end,
+                StockDailyModel.adjust == adjust,
             )
             .order_by(StockDailyModel.symbol, StockDailyModel.trade_date)
             .execution_options(yield_per=20000)

backend/app/quant/service.py

@@ -75,6 +75,7 @@ def load_daily_df(
     start: date,
     end: date,
     columns: list[str],
+    adjust: str = "none",
 ) -> pd.DataFrame:
     """从 Repository 装配行情长表（供研究/选股共用）。
 
@@ -86,12 +87,14 @@ def load_daily_df(
     streamer = getattr(daily_repo, "stream_range_many_columns", None)
     if streamer is not None:
         try:
-            return _frame_from_stream(streamer(symbols, start, end, sorted(columns)), sorted(columns))
+            return _frame_from_stream(
+                streamer(symbols, start, end, sorted(columns), adjust=adjust), sorted(columns)
+            )
         except Exception:  # noqa: BLE001 —— 流式路径失败回退旧路径（兼容非 SQL 实现）
             pass
     get_many = getattr(daily_repo, "get_range_many", None)
     if get_many is not None:
-        bars = list(get_many(symbols, start, end))
+        bars = list(get_many(symbols, start, end, adjust=adjust))
     else:  # 兜底：逐只查询
         bars = []
         for sym in symbols:
@@ -134,5 +137,10 @@ class ResearchService:
         # 引擎所需列裁剪（LocalEngine 只取 close + 因子字段；Qlib 回测取全 OHLCV）
         required = self._engine.required_columns(spec)
         return load_daily_df(
-            self._daily_repo, [s.symbol for s in stocks], data_start, end, sorted(required)
+            self._daily_repo,
+            [s.symbol for s in stocks],
+            data_start,
+            end,
+            sorted(required),
+            adjust=spec.price_adjustment,
         )

backend/tests/test_api.py

@@ -48,7 +48,7 @@ def client(tmp_path) -> TestClient:
     bars = bars_dataframe_to_daily_bars(daily_df)
 
     class _MemDailyRepo:
-        def get_range_many(self, symbols, start, end):
+        def get_range_many(self, symbols, start, end, adjust="none"):
             out = []
             for b in bars:
                 if b.symbol in symbols and start <= b.trade_date <= end:

backend/tests/test_jobs_experiments.py

@@ -59,7 +59,7 @@ class _FakeDailyRepo:
     def __init__(self, bars):
         self._bars = bars
 
-    def get_range_many(self, symbols, start, end):
+    def get_range_many(self, symbols, start, end, adjust="none"):
         return [b for b in self._bars if b.symbol in symbols and start <= b.trade_date <= end]
 
     def get_range(self, symbol, start, end):

backend/tests/test_price_adjustment.py

@@ -0,0 +1,106 @@
+"""M7.3 行情口径测试：Repository 读路径按 adjust 过滤（不复权主口径），spec 记录口径。
+
+混合行场景：同 symbol/date 存在 tushare/none 与 sina/qfq 行时，研究读取
+（get_range_many / stream）默认只取 adjust=none —— 消除「混合口径污染因子」风险。
+"""
+
+from __future__ import annotations
+
+from datetime import date
+from decimal import Decimal
+
+from app.domain.entities.market import DailyBar
+from app.domain.entities.research import ResearchSpec
+from app.domain.entities.selection import SelectionQuery
+from app.infrastructure.persistence.sqlalchemy.base import Base
+from app.infrastructure.persistence.sqlalchemy.repositories.market_impl import (
+    SqlAlchemyDailyBarRepository,
+)
+from sqlalchemy import create_engine
+from sqlalchemy.orm import Session
+
+_D = date(2024, 6, 3)
+_D2 = date(2024, 6, 4)
+_D3 = date(2024, 6, 5)
+
+
+def _bar(adjust: str, close: str, source: str = "tushare", day=None) -> DailyBar:
+    return DailyBar(
+        symbol="600519.SH",
+        trade_date=day or _D,
+        source=source,
+        adjust=adjust,
+        open=Decimal("100"), high=Decimal("101"), low=Decimal("99"),
+        close=Decimal(close), volume=Decimal("1000"), amount=Decimal("100000"),
+    )
+
+
+class TestAdjustFilter:
+    def _session(self, tmp_path) -> Session:
+        engine = create_engine(f"sqlite:///{tmp_path / 'adj.db'}", future=True)
+        Base.metadata.create_all(engine)
+        return Session(engine)
+
+    def test_get_range_many_filters_adjust(self, tmp_path) -> None:
+        with self._session(tmp_path) as session:
+            repo = SqlAlchemyDailyBarRepository(session)
+            # 唯一键 (symbol, trade_date)：同键共存不可能 —— 用连续三天模拟
+            # none 主口径两天 + sina/qfq 兜底一天
+            repo.upsert_many(
+                [
+                    _bar("none", "1700", day=_D),
+                    _bar("none", "1710", day=_D2),
+                    _bar("qfq", "1680", source="sina", day=_D3),
+                ]
+            )
+            session.commit()
+
+            none_rows = repo.get_range_many(["600519.SH"], _D, _D3, adjust="none")
+            assert len(none_rows) == 2 and {float(r.close) for r in none_rows} == {1700, 1710}
+            qfq_rows = repo.get_range_many(["600519.SH"], _D, _D3, adjust="qfq")
+            assert len(qfq_rows) == 1 and float(qfq_rows[0].close) == 1680
+
+    def test_stream_filters_adjust(self, tmp_path) -> None:
+        with self._session(tmp_path) as session:
+            repo = SqlAlchemyDailyBarRepository(session)
+            repo.upsert_many(
+                [
+                    _bar("none", "1700", day=_D),
+                    _bar("none", "1710", day=_D2),
+                    _bar("qfq", "1680", source="sina", day=_D3),
+                ]
+            )
+            session.commit()
+            rows = list(
+                repo.stream_range_many_columns(
+                    ["600519.SH"], _D, _D3, ["close"], adjust="none"
+                )
+            )
+            assert len(rows) == 2 and {float(r[-1]) for r in rows} == {1700, 1710}
+            qrows = list(
+                repo.stream_range_many_columns(
+                    ["600519.SH"], _D, _D3, ["close"], adjust="qfq"
+                )
+            )
+            assert len(qrows) == 1 and float(qrows[0][-1]) == 1680
+
+
+class TestSpecRecordsAdjustment:
+    def test_research_spec_default_and_field(self) -> None:
+        spec = ResearchSpec(
+            type="backtest",
+            factors=[{"name": "momentum_60", "weight": 1}],
+            period=(date(2024, 1, 1), date(2024, 6, 1)),
+        )
+        assert spec.price_adjustment == "none"
+        snap = spec.model_dump(mode="json")
+        assert snap["price_adjustment"] == "none"  # 结果 config_snapshot 可溯源
+
+    def test_selection_query_adjustment_in_snapshot(self) -> None:
+        q = SelectionQuery(factors=[{"name": "momentum_60", "weight": 1}], top_n=5)
+        assert q.price_adjustment == "none"
+        assert q.model_dump()["price_adjustment"] == "none"
+        q2 = SelectionQuery(
+            factors=[{"name": "momentum_60", "weight": 1}], top_n=5, price_adjustment="qfq"
+        )
+        assert q2.price_adjustment == "qfq"

backend/tests/test_selection.py

@@ -69,7 +69,7 @@ class _MemDailyRepo:
     def get_range(self, symbol, start, end) -> list[DailyBar]:
         return self._bars([symbol], start, end)
 
-    def get_range_many(self, symbols, start, end) -> list[DailyBar]:
+    def get_range_many(self, symbols, start, end, adjust="none") -> list[DailyBar]:
         return self._bars(list(symbols), start, end)
 
     def latest_date(self, symbol: str) -> date | None:

backend/tests/test_selection_backtest_consistency.py

@@ -42,7 +42,7 @@ class _MemDailyRepo:
     def get_range(self, symbol, start, end):
         return [b for b in self._bars if b.symbol == symbol and start <= b.trade_date <= end]
 
-    def get_range_many(self, symbols, start, end):
+    def get_range_many(self, symbols, start, end, adjust="none"):
         syms = set(symbols)
         return [b for b in self._bars if b.symbol in syms and start <= b.trade_date <= end]
 

backend/tests/test_selection_condition.py

@@ -38,7 +38,7 @@ class _MemDailyRepo:
     def get_range(self, symbol, start, end):
         return [b for b in self._bars_all if b.symbol == symbol and start <= b.trade_date <= end]
 
-    def get_range_many(self, symbols, start, end):
+    def get_range_many(self, symbols, start, end, adjust="none"):
         syms = set(symbols)
         return [b for b in self._bars_all if b.symbol in syms and start <= b.trade_date <= end]