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