feat(risk): represent split-adjusted price basis (#298)

Co-authored-by: Codex <noreply@openai.com>

Author: Pigbibi

docs/qsl_long_horizon_risk_observation_v2.zh-CN.md

@@ -72,7 +72,7 @@ v2 复用已验证的 v1 计算器，**仅**在以下范围输出 `ADVISORY_RECO
 | 多策略组合 | `PORTFOLIO_COMPOSER_REQUIRED` | 必须重算相关性、边际风险贡献和组合净收益 |
 | DCA 或外部现金流 | `CASHFLOW_COMPOSER_REQUIRED` | 必须使用现金流匹配、时间一致的路径 |
 | 混合、现金或绝对收益基准 | `BENCHMARK_POLICY_COMPOSER_REQUIRED` | 不能伪装为权益无杠杆基准 |
-| 非净成本总收益基准口径 | `BENCHMARK_RETURN_BASIS_COMPOSER_REQUIRED` | 当前回撤比较不具可比性 |
+| 非净成本总收益基准口径（包括 `SPLIT_ADJUSTED_PRICE_RETURN`） | `BENCHMARK_RETURN_BASIS_COMPOSER_REQUIRED` | 当前回撤比较不具可比性；拆分复权收盘价不得伪称总收益 |
 
 `PARKED` 没有尺度、最大回撤或前沿；它不是失败后的默认继续运行，更不能触发实盘动作。
 

python/scripts/long_horizon_risk_composer_v2.py

@@ -105,6 +105,10 @@
 _RETURN_BASES = {
     "TOTAL_RETURN_NET_OF_COST",
     "TIME_WEIGHTED_TOTAL_RETURN",
+    # Some verified research lanes intentionally retain only split-adjusted
+    # closes.  They must be representable without being mislabeled as a total
+    # return series; the generic v1-compatible composer still parks them.
+    "SPLIT_ADJUSTED_PRICE_RETURN",
     "CASHFLOW_MATCHED_RETURN",
 }
 _RISK_FACTORS = {

python/tests/test_long_horizon_risk_observation_v2.py

@@ -168,6 +168,17 @@ def test_cashflow_matched_strategies_cannot_be_coerced_to_time_weighted_linear_m
         with self.assertRaisesRegex(composer.LongHorizonRiskComposerError, "requires CASHFLOW_MATCHED_RETURN"):
             composer_v2.validate_long_horizon_risk_observation_v2(invalid)
 
+    def test_split_adjusted_price_benchmark_is_represented_but_not_mislabeled_as_total_return(self):
+        observation = self._observation()
+        observation["benchmark_policy"]["return_basis"] = "SPLIT_ADJUSTED_PRICE_RETURN"
+        observation["observation_sha256"] = composer_v2.calculate_risk_observation_v2_sha256(observation)
+
+        recommendation = composer_v2.compose_long_horizon_risk_recommendation_v2(observation, self._profile())
+
+        self.assertEqual(recommendation["status"], "PARKED")
+        self.assertEqual(recommendation["reason_codes"], ["BENCHMARK_RETURN_BASIS_COMPOSER_REQUIRED"])
+        self.assertIsNone(recommendation["recommended_scale_bps"])
+
 
 if __name__ == "__main__":
     unittest.main()