Adriano
15cb6b37aa
Pipeline AST -> compile_strategy -> BacktestEngine -> Sharpe/DSR/DD. Caso zero-trade ritorna report tutto-zero. n_trials_dsr correzione multiple-testing parametrizzata via init. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
49 lines
1.6 KiB
Python
49 lines
1.6 KiB
Python
import numpy as np
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import pandas as pd
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import pytest
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from multi_swarm.agents.falsification import FalsificationAgent, FalsificationReport
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from multi_swarm.protocol.parser import parse_strategy
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@pytest.fixture
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def trending_ohlcv() -> pd.DataFrame:
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idx = pd.date_range("2024-01-01", periods=500, freq="1h", tz="UTC")
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close = 100 + np.cumsum(np.random.RandomState(0).normal(0.01, 1.0, 500))
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return pd.DataFrame(
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{
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"open": close,
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"high": close + 0.5,
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"low": close - 0.5,
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"close": close,
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"volume": 1.0,
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},
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index=idx,
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)
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def test_falsification_returns_report(trending_ohlcv: pd.DataFrame) -> None:
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src = (
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"(strategy "
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"(when (gt (indicator rsi 14) 70.0) (entry-short)) "
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"(when (lt (indicator rsi 14) 30.0) (entry-long)))"
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)
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ast = parse_strategy(src)
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agent = FalsificationAgent(fees_bp=5.0, n_trials_dsr=20)
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report = agent.evaluate(ast, trending_ohlcv)
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assert isinstance(report, FalsificationReport)
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assert isinstance(report.sharpe, float)
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assert isinstance(report.dsr, float)
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assert 0.0 <= report.dsr <= 1.0
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assert isinstance(report.max_drawdown, float)
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assert isinstance(report.n_trades, int)
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def test_falsification_zero_trades_returns_zero_metrics(trending_ohlcv: pd.DataFrame) -> None:
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src = "(strategy (when (gt (feature close) 1e9) (entry-long)))"
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ast = parse_strategy(src)
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agent = FalsificationAgent(fees_bp=5.0, n_trials_dsr=20)
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report = agent.evaluate(ast, trending_ohlcv)
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assert report.n_trades == 0
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assert report.sharpe == 0.0
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