62 lines
1.9 KiB
Python
62 lines
1.9 KiB
Python
from backtesting import engine, statistics
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def test_moving_block_bootstrap_is_deterministic_and_handles_constant_series():
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first = statistics.moving_block_bootstrap_ci(
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[12.5] * 120,
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block_size=15,
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n_resamples=200,
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seed=7,
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)
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second = statistics.moving_block_bootstrap_ci(
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[12.5] * 120,
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block_size=15,
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n_resamples=200,
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seed=7,
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)
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assert first == second
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assert first == {"estimate": 12.5, "ci_low": 12.5, "ci_high": 12.5, "n": 120}
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def test_summarize_returns_reports_observations_and_block_bootstrap_interval():
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summary = statistics.summarize_returns(
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[10.0, -5.0, 20.0, -10.0],
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block_size=2,
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n_resamples=200,
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seed=3,
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)
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assert summary["n"] == 4
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assert summary["mean"] == 3.75
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assert summary["median"] == 2.5
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assert summary["win_rate"] == 50.0
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assert summary["mean_ci_low"] <= summary["mean"] <= summary["mean_ci_high"]
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def test_backtest_brackets_publish_bootstrap_confidence_intervals():
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stats = {}
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engine._add_return_statistics(stats, "90d", [10.0, -5.0, 20.0, -10.0])
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assert stats["avg_90d"] == 3.75
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assert stats["median_90d"] == 2.5
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assert stats["win_rate_90d"] == 50.0
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assert stats["avg_90d_ci_low"] <= stats["avg_90d"] <= stats["avg_90d_ci_high"]
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def test_long_horizon_returns_use_a_matching_dependence_block(monkeypatch):
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observed = {}
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def fake_summary(values, *, block_size, n_resamples):
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observed.update(block_size=block_size, n_resamples=n_resamples)
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return {
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"mean": 1.0, "median": 1.0, "win_rate": 100.0,
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"mean_ci_low": 0.5, "mean_ci_high": 1.5, "n": len(values),
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}
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monkeypatch.setattr(engine, "summarize_returns", fake_summary)
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engine._add_return_statistics({}, "365d", [1.0] * 500)
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assert observed == {"block_size": 365, "n_resamples": 400}
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