"""Batch 3: walk-forward details, signal validation, IC bounds.""" from __future__ import annotations import sys from pathlib import Path import numpy as np, pandas as pd, pytest PROJECT_ROOT = Path(__file__).parent.parent.parent sys.path.insert(0, str(PROJECT_ROOT)) class TestWalkForwardDetails: def test_non_datetime_returns_empty(self): from rdagent.components.backtesting.vbt_backtest import walk_forward_rolling result = walk_forward_rolling(pd.Series([1.0]), pd.Series([1.0]), leverage=1.0) assert result == {"wf_n_windows": 0} def test_wf_consistency_bounds(self): from rdagent.components.backtesting.vbt_backtest import walk_forward_rolling dates = pd.date_range("2020-01-01", "2023-12-31", freq="1min") rng = np.random.default_rng(42) close = pd.Series(1.10 + rng.normal(0, 0.0001, len(dates)).cumsum(), index=dates) signal = pd.Series(np.where(rng.normal(0, 1, len(dates)) > 0, 1.0, -1.0), index=dates) result = walk_forward_rolling(close, signal, leverage=1.0) if result["wf_n_windows"] > 0 and "wf_oos_consistency" in result: assert 0.0 <= result["wf_oos_consistency"] <= 1.0 class TestSignalValidation: def test_constant_signal_zero_trades(self): from rdagent.components.backtesting.vbt_backtest import backtest_signal dates = pd.date_range("2024-01-01", periods=500, freq="1min") close = pd.Series(1.10, index=dates) result = backtest_signal(close, pd.Series(1.0, index=dates), txn_cost_bps=0.0) assert result["n_trades"] >= 0 def test_binary_signal_range(self): from rdagent.components.backtesting.vbt_backtest import backtest_signal n = 1000 dates = pd.date_range("2024-01-01", periods=n, freq="1min") close = pd.Series(1.10 + np.random.default_rng(42).normal(0, 0.0002, n).cumsum(), index=dates) for val in [0.0, 1.0, -1.0, 2.0, -2.0]: result = backtest_signal(close, pd.Series(val, index=dates)) assert result["status"] in ("success", "failed") def test_float_signal_works(self): from rdagent.components.backtesting.vbt_backtest import backtest_signal n = 1000 dates = pd.date_range("2024-01-01", periods=n, freq="1min") close = pd.Series(1.10 + np.random.default_rng(42).normal(0, 0.0002, n).cumsum(), index=dates) signal = pd.Series(np.random.default_rng(43).normal(0, 1, n), index=dates) result = backtest_signal(close, signal) assert result["status"] in ("success", "failed") class TestBacktestFromFwdReturnsDetails: def test_ic_always_between_neg1_and_1(self): from rdagent.components.backtesting.vbt_backtest import backtest_from_forward_returns for seed in [42, 43, 44, 45, 46]: idx = pd.MultiIndex.from_arrays( [pd.date_range("2024-01-01", periods=500, freq="1min"), ["EURUSD"] * 500], names=["datetime", "instrument"], ) close = pd.Series(1.10 + np.random.default_rng(seed).normal(0, 0.0001, 500).cumsum(), index=idx) fwd = close.groupby(level="instrument").shift(-96) / close - 1 factor = pd.Series(np.random.default_rng(seed + 100).normal(0, 1, 500), index=idx) result = backtest_from_forward_returns(factor, fwd, close) if result["status"] == "success" and "ic" in result: assert -1.0 <= result["ic"] <= 1.0 def test_trades_non_negative(self): from rdagent.components.backtesting.vbt_backtest import backtest_from_forward_returns idx = pd.MultiIndex.from_arrays( [pd.date_range("2024-01-01", periods=500, freq="1min"), ["EURUSD"] * 500], names=["datetime", "instrument"], ) close = pd.Series(1.10 + np.arange(500) * 0.0001, index=idx) fwd = close.groupby(level="instrument").shift(-96) / close - 1 factor = pd.Series(np.random.default_rng(42).normal(0, 1, 500), index=idx) result = backtest_from_forward_returns(factor, fwd, close) if result["status"] == "success": assert result.get("n_trades", 0) >= 0