feat(stock-lab): Momentum20 노드 — N일 수익률 백분위

stock-lab/app/screener/nodes/momentum.py

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+"""20일 모멘텀."""
+
+import pandas as pd
+
+from .base import ScoreNode, percentile_rank
+
+
+class Momentum20(ScoreNode):
+    name  = "momentum"
+    label = "20일 모멘텀"
+    default_params = {"window_days": 20}
+    param_schema = {
+        "type": "object",
+        "properties": {
+            "window_days": {"type": "integer", "minimum": 5, "maximum": 120, "default": 20}
+        },
+    }
+
+    def compute(self, ctx, params: dict) -> pd.Series:
+        window = int(params.get("window_days", 20))
+        prices = ctx.prices
+        if prices.empty:
+            return pd.Series(dtype=float)
+
+        ordered = prices.sort_values("date")
+        last = ordered.groupby("ticker").tail(window + 1)
+
+        def _ret(s):
+            if len(s) < window + 1:
+                return float("nan")
+            return s.iloc[-1] / s.iloc[0] - 1
+
+        raw = last.groupby("ticker")["close"].apply(_ret)
+        return percentile_rank(raw).fillna(50.0)

stock-lab/app/test_screener_nodes_momentum.py

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+import datetime as dt
+import pandas as pd
+
+from app.screener.engine import ScreenContext
+from app.screener.nodes.momentum import Momentum20
+from app.screener._test_fixtures import make_master, make_prices, make_flow
+
+
+def _ctx(master, prices, flow):
+    return ScreenContext(master=master, prices=prices, flow=flow,
+                         kospi=pd.Series(dtype=float, name="kospi"),
+                         asof=dt.date(2026, 5, 12))
+
+
+def test_higher_momentum_gets_higher_score():
+    asof = dt.date(2026, 5, 12)
+    master = make_master(["UP", "DN"])
+    up = make_prices(["UP"], days=30, asof=asof, trend_pct=0.5)
+    dn = make_prices(["DN"], days=30, asof=asof, trend_pct=-0.3)
+    prices = pd.concat([up, dn], ignore_index=True)
+    flow = make_flow(["UP", "DN"], days=30, asof=asof)
+
+    out = Momentum20().compute(_ctx(master, prices, flow), {"window_days": 20})
+    assert out["UP"] > out["DN"]