feat(stock-lab): position_sizer — ATR Wilder + entry/stop/target

stock-lab/app/screener/position_sizer.py

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+"""ATR Wilder smoothing + entry/stop/target 계산."""
+
+import pandas as pd
+
+
+def compute_atr_wilder(df_one_ticker: pd.DataFrame, window: int = 14) -> float:
+    """단일 종목 DataFrame(date·open·high·low·close)에 대해 Wilder ATR 마지막 값."""
+    g = df_one_ticker.sort_values("date").copy()
+    high = g["high"].astype(float)
+    low  = g["low"].astype(float)
+    close = g["close"].astype(float)
+    prev_close = close.shift(1)
+    tr = pd.concat([
+        (high - low),
+        (high - prev_close).abs(),
+        (low  - prev_close).abs(),
+    ], axis=1).max(axis=1)
+    atr = tr.ewm(alpha=1 / window, adjust=False).mean()
+    return float(atr.iloc[-1])
+
+
+def round_won(x: float) -> int:
+    return int(round(x))
+
+
+def plan_positions(ctx, tickers: list, params: dict) -> dict:
+    """각 ticker 에 대해 entry/stop/target/atr14 반환."""
+    atr_window = int(params.get("atr_window", 14))
+    stop_mult  = float(params.get("atr_stop_mult", 2.0))
+    rr         = float(params.get("rr_ratio", 2.0))
+
+    prices = ctx.prices.sort_values("date")
+    out: dict = {}
+    for t in tickers:
+        sub = prices[prices["ticker"] == t]
+        if sub.empty:
+            continue
+        close = float(sub["close"].iloc[-1])
+        atr14 = compute_atr_wilder(sub, window=atr_window)
+        entry  = round_won(close * 1.005)
+        stop   = round_won(close - stop_mult * atr14)
+        target = round_won(entry + rr * (entry - stop))
+        r_pct  = (entry - stop) / entry * 100 if entry else 0.0
+        out[t] = {
+            "entry_price":  entry,
+            "stop_price":   stop,
+            "target_price": target,
+            "atr14":        atr14,
+            "r_pct":        r_pct,
+        }
+    return out

stock-lab/app/test_screener_position_sizer.py

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+import datetime as dt
+import pandas as pd
+
+from app.screener.engine import ScreenContext
+from app.screener.position_sizer import compute_atr_wilder, plan_positions
+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_atr_wilder_positive_and_smooth():
+    df = make_prices(["A"], days=30)
+    atr = compute_atr_wilder(df[df["ticker"] == "A"], window=14)
+    assert atr > 0
+
+
+def test_plan_positions_returns_entry_stop_target():
+    asof = dt.date(2026, 5, 12)
+    master = make_master(["A"])
+    prices = make_prices(["A"], days=30, asof=asof, start_close=50000)
+    flow = make_flow(["A"], days=30, asof=asof)
+    ctx = _ctx(master, prices, flow)
+    sizing = plan_positions(ctx, ["A"], {"atr_window": 14, "atr_stop_mult": 2.0, "rr_ratio": 2.0})
+
+    row = sizing["A"]
+    assert row["entry_price"] > 0
+    assert row["stop_price"] < row["entry_price"]
+    assert row["target_price"] > row["entry_price"]
+    assert row["atr14"] > 0