From 5bde8f9f5f4d2869a0d2ca4295b1b0bde89d4973 Mon Sep 17 00:00:00 2001
From: Simon <simon@doorcome.cn>
Date: Wed, 9 Sep 2026 07:15:41 +0800
Subject: [PATCH] =?UTF-8?q?feat(chart):=20M9-5=20=E5=A4=8D=E6=9D=83?=
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- ChartService qfq 基准改为该股最新因子（截至今天）归一：历史区间随最新除权
  平移正确（v3 §20.5 Chart Display vs Execution basis 分离）
- 显示口径与执行 basis 不一致时，成交/信号 marker 价格按当日因子换算到 K 线坐标系
  （fill 早段价格在 qfq 下折算验证 100→50）
- tests：qfq 回测 marker 折算 + selection 标记保留；全量 pytest 通过
---
 .../app/application/services/chart_service.py |  8 ++-
 backend/tests/test_charts.py                  | 66 +++++++++++++++++++
 2 files changed, 72 insertions(+), 2 deletions(-)

diff --git a/backend/app/application/services/chart_service.py b/backend/app/application/services/chart_service.py
index 1088fb1..631b335 100644
--- a/backend/app/application/services/chart_service.py
+++ b/backend/app/application/services/chart_service.py
@@ -43,10 +43,14 @@ def _factor_multipliers(
     end: date,
     mode: str,
 ) -> dict[date, float]:
-    """返回 {trade_date: 显示折算系数}；mode=none → 空。qfq: f/f_latest；hfq: f。"""
+    """返回 {trade_date: 显示折算系数}；mode=none → 空。
+
+    基准（v3 §20.5）：qfq 以**该股最新因子**（截至今天，而非图表区间末）归一，
+    保证历史区间随最新除权平移正确；hfq 直接用累积因子。
+    """
     if mode == "none":
         return {}
-    factors: list[AdjustFactor] = adj_repo.get_range(symbol, date(1990, 1, 1), end)
+    factors: list[AdjustFactor] = adj_repo.get_range(symbol, date(1990, 1, 1), date.today())
     if not factors:
         return {}
     by_day = {f.trade_date: float(f.factor) for f in factors}
diff --git a/backend/tests/test_charts.py b/backend/tests/test_charts.py
index db293fc..596da0f 100644
--- a/backend/tests/test_charts.py
+++ b/backend/tests/test_charts.py
@@ -231,3 +231,69 @@ class TestChartApi:
         positions = client.get("/api/backtests/EXP-CHART-1/positions").json()
         assert isinstance(trades, list) and isinstance(positions, list)
         assert client.get("/api/backtests/EXP-NOPE/stocks/x/chart").status_code == 404
+
+
+class TestAdjustCoordinate:
+    def test_qfq_backtest_marker_converted(self, seeded, tmp_path) -> None:
+        """显示前复权时，早期成交 marker 价格按因子折算贴图（v3 §20.5 坐标）。"""
+
+        from app.domain.entities.research import (
+            ActionRecord,
+            BacktestResult,
+            BacktestSummary,
+            CurvePoint,
+            RankedPick,
+            Trade,
+        )
+
+        engine, Session, df = _seeded_with_factors(tmp_path)
+        dates = sorted(df["trade_date"].unique())
+        split = dates[len(dates) // 2]
+        with Session() as session:
+            SqlAlchemyAdjustFactorRepository(session).upsert_many(
+                [
+                    AdjustFactor(symbol=_SYMS[0], trade_date=d,
+                                 factor=Decimal("1.0") if d < split else Decimal("2.0"))
+                    for d in dates
+                ]
+            )
+            session.commit()
+            svc = ChartService(
+                SqlAlchemyStockRepository(session),
+                SqlAlchemyDailyBarRepository(session),
+                SqlAlchemyAdjustFactorRepository(session),
+            )
+            # 早期（factor=1.0 段）一笔买入成交价 100
+            result = BacktestResult(
+                summary=BacktestSummary(
+                    start=dates[0], end=dates[-1], initial_capital=1e6, final_equity=1e6,
+                    total_return_pct=0, annual_return_pct=0, sharpe=0, max_drawdown_pct=0,
+                    volatility_pct=0, win_rate_pct=0, total_trades=1, avg_turnover_pct=0,
+                ),
+                equity_curve=[CurvePoint(date=dates[0], value=1e6)],
+                drawdown=[], monthly_returns=[], yearly_returns=[],
+                positions=[], trades=[
+                    Trade(entry_date=dates[5], exit_date=dates[-1], symbol=_SYMS[0],
+                          entry_price=100.0, exit_price=200.0, return_pct=100),
+                ],
+                selection_history=[
+                    RankedPick(date=dates[5], symbol=_SYMS[0], rank=1, score=1.0)
+                ],
+                signal_history=[
+                    ActionRecord(date=dates[5], symbol=_SYMS[0], signal="BUY", filled=True, price=100.0),
+                ],
+                fills=[
+                    ActionRecord(date=dates[5], symbol=_SYMS[0], signal="BUY", filled=True, price=100.0),
+                ],
+                turnover_pct=0,
+                config_snapshot={"price_adjustment": "none"},
+            )
+            chart_none = svc.backtest_stock_chart(result, _SYMS[0], dates[0], dates[-1], "none")
+            chart_qfq = svc.backtest_stock_chart(result, _SYMS[0], dates[0], dates[-1], "qfq")
+        # none：fill 价 100；qfq 显示：早期因子 1.0 / 最新 2.0 → 折算 50
+        none_fill = chart_none.fills[0]
+        qfq_fill = chart_qfq.fills[0]
+        assert none_fill.price == 100.0
+        assert qfq_fill.price is not None and abs(qfq_fill.price - 50.0) < 1e-3
+        # 选股意图标记保留
+        assert any(m.kind == "selection" for m in chart_qfq.selections)