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228 lines
7.1 KiB
Python
228 lines
7.1 KiB
Python
"""Unit tests for libs/backtest/metrics.py."""
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from __future__ import annotations
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import datetime as dt
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import pytest
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from libs.backtest.domain import DailyPortfolioState, ExitReason, FilledTrade
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def _make_trade(
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net_pnl: float,
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exit_reason: ExitReason = ExitReason.TARGET,
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r_multiple: float = 1.0,
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holding_days: int = 5,
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exit_date: dt.date = dt.date(2026, 1, 10),
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symbol: str = "AAPL",
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) -> FilledTrade:
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entry_price = 100.0
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return FilledTrade(
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trade_id=f"t_{symbol}_{exit_date}_{net_pnl}",
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position_id="p1",
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event_id="EVT::TEST",
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symbol=symbol,
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entry_date=dt.date(2026, 1, 5),
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exit_date=exit_date,
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entry_price=entry_price,
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exit_price=entry_price + (net_pnl / max(1, 10)),
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exit_reason=exit_reason,
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shares=10,
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commission=0.1,
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slippage_bps=10.0,
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gross_pnl=net_pnl + 0.1,
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net_pnl=net_pnl,
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pnl_pct=net_pnl / (entry_price * 10),
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r_multiple=r_multiple,
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holding_days=holding_days,
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)
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def _make_equity_state(date: dt.date, equity: float, n_positions: int = 0) -> DailyPortfolioState:
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return DailyPortfolioState(
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date=date,
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equity=equity,
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cash_available=equity,
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gross_exposure=0.0,
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net_exposure=0.0,
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reserved_risk_budget=0.0,
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unrealized_pnl=0.0,
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realized_pnl=0.0,
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open_positions=[f"p{i}" for i in range(n_positions)],
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daily_new_risk_used=0.0,
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peak_equity=equity,
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current_drawdown_pct=0.0,
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)
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class TestWinRate:
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def test_all_wins(self):
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from libs.backtest.metrics import compute_win_rate
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trades = [_make_trade(100), _make_trade(200)]
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assert compute_win_rate(trades) == 1.0
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def test_mixed(self):
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from libs.backtest.metrics import compute_win_rate
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trades = [_make_trade(100), _make_trade(-50)]
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assert compute_win_rate(trades) == pytest.approx(0.5)
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def test_empty_returns_none(self):
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from libs.backtest.metrics import compute_win_rate
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assert compute_win_rate([]) is None
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class TestProfitFactor:
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def test_basic(self):
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from libs.backtest.metrics import compute_profit_factor
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trades = [_make_trade(200), _make_trade(100), _make_trade(-100)]
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pf = compute_profit_factor(trades)
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assert pf == pytest.approx(3.0)
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def test_no_losses_returns_none(self):
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from libs.backtest.metrics import compute_profit_factor
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trades = [_make_trade(100), _make_trade(200)]
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assert compute_profit_factor(trades) is None
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def test_empty_returns_none(self):
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from libs.backtest.metrics import compute_profit_factor
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assert compute_profit_factor([]) is None
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class TestExpectancyR:
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def test_positive(self):
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from libs.backtest.metrics import compute_expectancy_r
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trades = [_make_trade(100, r_multiple=2.0), _make_trade(-50, r_multiple=-1.0)]
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er = compute_expectancy_r(trades)
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assert er == pytest.approx(0.5)
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def test_empty_returns_none(self):
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from libs.backtest.metrics import compute_expectancy_r
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assert compute_expectancy_r([]) is None
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class TestTotalReturnPct:
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def test_basic(self):
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from libs.backtest.metrics import compute_total_return_pct
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curve = [
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_make_equity_state(dt.date(2026, 1, 5), 100_000),
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_make_equity_state(dt.date(2026, 1, 6), 110_000),
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]
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assert compute_total_return_pct(curve) == pytest.approx(10.0)
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def test_single_point_returns_none(self):
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from libs.backtest.metrics import compute_total_return_pct
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assert compute_total_return_pct([_make_equity_state(dt.date(2026, 1, 5), 100_000)]) is None
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class TestMaxDrawdown:
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def test_basic_drawdown(self):
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from libs.backtest.metrics import compute_max_drawdown_pct
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curve = [
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_make_equity_state(dt.date(2026, 1, 5), 100_000),
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_make_equity_state(dt.date(2026, 1, 6), 120_000), # peak
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_make_equity_state(dt.date(2026, 1, 7), 90_000), # drawdown from 120k
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_make_equity_state(dt.date(2026, 1, 8), 100_000),
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]
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dd = compute_max_drawdown_pct(curve)
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# Max drawdown = (120k - 90k) / 120k = 25%
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assert dd == pytest.approx(25.0)
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def test_no_drawdown(self):
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from libs.backtest.metrics import compute_max_drawdown_pct
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curve = [
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_make_equity_state(dt.date(2026, 1, 5), 100_000),
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_make_equity_state(dt.date(2026, 1, 6), 110_000),
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]
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assert compute_max_drawdown_pct(curve) == pytest.approx(0.0)
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class TestSharpeRatio:
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def test_positive_sharpe(self):
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from libs.backtest.metrics import compute_sharpe_ratio
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# Steady returns → positive Sharpe
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curve = [
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_make_equity_state(dt.date(2026, 1, 2) + dt.timedelta(days=i), 100_000 + i * 100)
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for i in range(50)
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]
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sharpe = compute_sharpe_ratio(curve)
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assert sharpe is not None
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assert sharpe > 0
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def test_not_enough_data_returns_none(self):
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from libs.backtest.metrics import compute_sharpe_ratio
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curve = [_make_equity_state(dt.date(2026, 1, 5), 100_000)]
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assert compute_sharpe_ratio(curve) is None
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class TestStopExitRate:
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def test_basic(self):
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from libs.backtest.metrics import compute_stop_exit_rate
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trades = [
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_make_trade(100, ExitReason.TARGET),
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_make_trade(-50, ExitReason.STOP),
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_make_trade(-30, ExitReason.STOP),
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]
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assert compute_stop_exit_rate(trades) == pytest.approx(2 / 3)
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def test_trailing_counts_as_stop(self):
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from libs.backtest.metrics import compute_stop_exit_rate
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trades = [
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_make_trade(50, ExitReason.TRAILING),
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]
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assert compute_stop_exit_rate(trades) == pytest.approx(1.0)
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class TestMonthlyWinRate:
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def test_basic(self):
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from libs.backtest.metrics import compute_monthly_win_rate
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trades = [
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_make_trade(100, exit_date=dt.date(2026, 1, 15)),
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_make_trade(200, exit_date=dt.date(2026, 1, 20)),
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_make_trade(-50, exit_date=dt.date(2026, 2, 10)),
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]
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# Jan: +300 = win, Feb: -50 = loss → 1/2 = 0.5
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mwr = compute_monthly_win_rate(trades)
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assert mwr == pytest.approx(0.5)
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class TestBuildMetricsBundle:
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def test_builds_with_trades_and_curve(self):
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from libs.backtest.metrics import build_metrics_bundle
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trades = [
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_make_trade(100, ExitReason.TARGET, r_multiple=2.0),
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_make_trade(-50, ExitReason.STOP, r_multiple=-1.0),
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]
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curve = [
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_make_equity_state(dt.date(2026, 1, 5), 100_000),
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_make_equity_state(dt.date(2026, 1, 10), 105_000),
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]
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m = build_metrics_bundle(trades, curve)
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assert m.trade_count == 2
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assert m.win_rate == pytest.approx(0.5)
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assert m.total_return_pct == pytest.approx(5.0)
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def test_empty_trades(self):
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from libs.backtest.metrics import build_metrics_bundle
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m = build_metrics_bundle([], [])
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assert m.trade_count == 0
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assert m.win_rate is None
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