feat(stock-lab): VcpLite 노드 — 변동성 수축률 백분위

stock-lab/app/test_screener_nodes_vcp_lite.py

@@ -0,0 +1,36 @@
+import datetime as dt
+import pandas as pd
+
+from app.screener.engine import ScreenContext
+from app.screener.nodes.vcp_lite import VcpLite
+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_contracting_stock_scores_higher_than_expanding():
+    asof = dt.date(2026, 5, 12)
+    master = make_master(["CON", "EXP"])
+    prices = make_prices(["CON", "EXP"], days=260, asof=asof)
+
+    # CON: 최근 40일 변동성 축소 (high/low 좁힘)
+    mask_recent_con = (prices["ticker"] == "CON") & (
+        prices["date"] >= (asof - dt.timedelta(days=40)).isoformat()
+    )
+    prices.loc[mask_recent_con, "high"] = (prices.loc[mask_recent_con, "close"] * 1.003).astype(int)
+    prices.loc[mask_recent_con, "low"]  = (prices.loc[mask_recent_con, "close"] * 0.997).astype(int)
+
+    # EXP: 최근 40일 변동성 확대
+    mask_recent_exp = (prices["ticker"] == "EXP") & (
+        prices["date"] >= (asof - dt.timedelta(days=40)).isoformat()
+    )
+    prices.loc[mask_recent_exp, "high"] = (prices.loc[mask_recent_exp, "close"] * 1.05).astype(int)
+    prices.loc[mask_recent_exp, "low"]  = (prices.loc[mask_recent_exp, "close"] * 0.95).astype(int)
+
+    flow = make_flow(["CON", "EXP"], days=260, asof=asof)
+    out = VcpLite().compute(_ctx(master, prices, flow), VcpLite.default_params)
+    assert out["CON"] > out["EXP"]