Viktor Barzin
cd75c4ab7e
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In-place extension (no fork). Existing tests still pass; new fields are optional and None when no benchmark is supplied.
99 lines
2.9 KiB
Python
99 lines
2.9 KiB
Python
"""Kevin-extension tests for compute_metrics (alpha/beta/winners/losers/best/worst)."""
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from datetime import datetime, timedelta, timezone
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from decimal import Decimal
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import pandas as pd
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from backtester.metrics import compute_metrics
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def _ts(day):
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return datetime(2026, 5, 15, tzinfo=timezone.utc) + timedelta(days=day)
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def test_compute_metrics_returns_alpha_and_beta_with_benchmark():
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spy = pd.DataFrame(
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{
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"open": [500, 500, 510, 510, 520],
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"high": [500] * 5,
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"low": [500] * 5,
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"close": [500, 500, 510, 510, 520],
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"volume": [0] * 5,
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},
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index=pd.date_range("2026-05-15", periods=5, freq="D", tz="UTC"),
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)
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trades = [
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{
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"symbol": "NVDA",
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"source_mention_id": 1,
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"entry_at": _ts(0),
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"entry_price": Decimal("100"),
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"exit_at": _ts(4),
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"exit_price": Decimal("110"),
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"qty": Decimal("10"),
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"pnl_usd": Decimal("100"),
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"pnl_pct": Decimal("10"),
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"holding_days_actual": 4,
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}
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]
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curve = [(_ts(i), Decimal(str(100000 + 25 * i))) for i in range(5)]
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result = compute_metrics(
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trade_log=trades,
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equity_curve=curve,
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initial_capital=Decimal("100000"),
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benchmark_bars=spy,
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)
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assert result.alpha_vs_spy_pct is not None
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assert result.beta_vs_spy is not None
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def test_compute_metrics_returns_winners_losers_best_worst():
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trades = [
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{
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"symbol": "NVDA",
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"source_mention_id": 1,
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"entry_at": _ts(0),
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"entry_price": Decimal("100"),
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"exit_at": _ts(5),
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"exit_price": Decimal("110"),
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"qty": Decimal("10"),
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"pnl_usd": Decimal("100"),
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"pnl_pct": Decimal("10"),
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"holding_days_actual": 5,
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},
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{
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"symbol": "INTC",
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"source_mention_id": 2,
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"entry_at": _ts(0),
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"entry_price": Decimal("50"),
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"exit_at": _ts(5),
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"exit_price": Decimal("45"),
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"qty": Decimal("20"),
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"pnl_usd": Decimal("-100"),
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"pnl_pct": Decimal("-10"),
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"holding_days_actual": 5,
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},
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]
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result = compute_metrics(
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trade_log=trades,
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equity_curve=[(_ts(0), Decimal("100000"))],
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initial_capital=Decimal("100000"),
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)
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assert result.avg_winner_pct == Decimal("10")
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assert result.avg_loser_pct == Decimal("-10")
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assert result.best_trade == {"symbol": "NVDA", "pnl_pct": Decimal("10")}
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assert result.worst_trade == {"symbol": "INTC", "pnl_pct": Decimal("-10")}
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def test_compute_metrics_no_benchmark_omits_alpha_beta():
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result = compute_metrics(
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trade_log=[],
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equity_curve=[(_ts(0), Decimal("100000"))],
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initial_capital=Decimal("100000"),
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)
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assert result.alpha_vs_spy_pct is None
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assert result.beta_vs_spy is None
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