feat(backend): Phase 2 研究引擎 — ResearchSpec / 因子 / 评估 / 低频回测 / 引擎抽象

- domain：ResearchSpec（universe/factors/selection/rebalance/costs 校验）+ 标准化 BacktestResult / FactorTestReport
- 因子引擎：注册表 + 元数据，内置 9 个行情因子（momentum/volatility/量比/乖离/反转），支持自定义注册；只用行情字段规避未来函数
- 评估：横截面 IC / RankIC（rank+pearson 免 scipy）/ ICIR / 分层收益
- 回测：TopK 等权低频，无未来函数记账（t 收盘成交、自 t+1 计收益），成本/涨跌停/停牌约束，未建模项显式写入 unimplemented（AGENT §24）
- 引擎抽象 QuantEngine + LocalEngine（pandas 默认实现）；qlib_adapter 桥接占位 —— pyqlib 无 aarch64+cp312 wheel（ROADMAP 已备注）
- 真实链路冒烟：600519 2024 月度动量回测闭环产出标准结果
- 测试 60 passed / ruff clean

backend/tests/test_quant_factors.py

@@ -0,0 +1,89 @@
+"""因子计算与注册表测试（合成数据、确定性断言方向与相对排序）。"""
+
+from __future__ import annotations
+
+import pandas as pd
+from app.quant.factors import (
+    FactorDef,
+    FactorError,
+    compute_factor,
+    get_factor,
+    list_factors,
+    register,
+)
+
+from conftest_quant import synthetic_daily
+
+
+def test_registry_builtins_present() -> None:
+    names = {f.name for f in list_factors()}
+    assert {"momentum_20", "momentum_60", "volatility_20", "ma_bias_20"} <= names
+
+
+def test_unknown_factor_raises() -> None:
+    try:
+        compute_factor("not_a_factor", synthetic_daily({"A": 0.0}))
+    except FactorError:
+        return
+    raise AssertionError("应抛 FactorError")
+
+
+def test_momentum_ordering_matches_drift() -> None:
+    daily = synthetic_daily({"AAA": 0.002, "BBB": 0.0, "CCC": -0.002}, n=160)
+    _defn, panel = compute_factor("momentum_20", daily)
+    tail = panel.iloc[-1]
+    assert tail["AAA"] > tail["BBB"] > tail["CCC"]
+    assert tail["AAA"] > 0  # 上涨股 20 日动量为正
+
+
+def test_volatility_ranks_noise() -> None:
+    # 手写：SMOOTH 每日 +0.2%；WILD 在 ±5% 间摆动 → WILD 的 20 日波动率应显著更高
+
+    from datetime import date, timedelta
+
+    dates = [date(2024, 1, 1) + timedelta(days=i) for i in range(120)]
+    rows = []
+    smooth, wild = 100.0, 100.0
+    for j, d in enumerate(dates):
+        smooth *= 1.002
+        wild *= 1.05 if j % 2 == 0 else 0.95
+        for sym, px in (("SMOOTH", smooth), ("WILD", wild)):
+            rows.append(
+                {
+                    "symbol": sym,
+                    "trade_date": d,
+                    "close": px,
+                    "high": px,
+                    "low": px,
+                    "volume": 1e6,
+                    "amount": 1e8,
+                }
+            )
+    daily = pd.DataFrame(rows)
+    _defn, panel = compute_factor("volatility_20", daily)
+    assert float(panel["WILD"].iloc[-1]) > float(panel["SMOOTH"].iloc[-1]) * 5
+
+
+def test_custom_factor_registration() -> None:
+    @register(FactorDef("test_double_close", "close*2 测试因子", "close * 2", lookback=1))
+    def _fn(fields: dict[str, pd.DataFrame]) -> pd.DataFrame:
+        return fields["close"] * 2
+
+    try:
+        daily = synthetic_daily({"A": 0.001}, n=40)
+        defn, panel = compute_factor("test_double_close", daily)
+        assert defn.direction == "higher_is_better"
+        assert float(panel.iloc[-1, 0]) > 200.0
+    finally:
+        # 清理注册表，避免污染其他测试
+        from app.quant import factors as _factors
+
+        _factors._REGISTRY.pop("test_double_close", None)  # noqa: SLF001
+
+
+def test_factor_def_metadata_present() -> None:
+    defn, _fn = get_factor("momentum_60")
+    assert defn.description
+    assert defn.formula
+    assert defn.lookback == 60
+    assert defn.direction in {"higher_is_better", "lower_is_better"}