Gahow Wang
24663ebd35
Add tests for trend rider (integration, robustness, v4), US combo sweep, and US fundamentals modules.
92 lines
3.0 KiB
Python
92 lines
3.0 KiB
Python
import unittest
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import numpy as np
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import pandas as pd
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from research import trend_rider_robustness as robustness
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class TrendRiderRobustnessTests(unittest.TestCase):
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def test_evaluate_weights_reports_core_risk_metrics(self):
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dates = pd.bdate_range("2024-01-01", periods=6)
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prices = pd.DataFrame(
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{
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"AAA": [100, 110, 105, 120, 118, 130],
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"BBB": [50, 49, 51, 50, 52, 53],
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},
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index=dates,
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)
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weights = pd.DataFrame(
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{
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"AAA": [0, 1, 1, 0, 0, 1],
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"BBB": [0, 0, 0, 1, 1, 0],
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},
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index=dates,
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)
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result = robustness.evaluate_weights("synthetic", weights, prices, transaction_cost=0.001)
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self.assertEqual(result.name, "synthetic")
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self.assertGreater(result.final_multiple, 1.0)
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self.assertLessEqual(result.max_drawdown, 0.0)
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self.assertGreater(result.switches, 0)
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self.assertGreater(result.avg_daily_turnover, 0.0)
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def test_parameter_sweep_returns_rankable_rows(self):
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dates = pd.bdate_range("2023-01-02", periods=320)
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trend = np.linspace(100, 180, len(dates))
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prices = pd.DataFrame(
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{
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"SPY": trend,
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"TQQQ": trend * 1.5,
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"UPRO": trend * 1.4,
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"GLD": np.linspace(100, 105, len(dates)),
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"DBC": np.linspace(90, 95, len(dates)),
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},
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index=dates,
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)
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sweep = robustness.parameter_sweep(
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prices,
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variants=[
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{"vol_enter": 0.14, "dd_stop": 0.05, "peak_enter": 0.02, "mom_lookback": 63},
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{"vol_enter": 0.16, "dd_stop": 0.07, "peak_enter": 0.03, "mom_lookback": 84},
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],
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start="2023-01-02",
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)
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self.assertEqual(len(sweep), 2)
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self.assertIn("cagr", sweep.columns)
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self.assertIn("max_drawdown", sweep.columns)
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self.assertTrue(sweep["cagr"].notna().all())
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def test_candidate_weights_include_v4_and_market_benchmarks(self):
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dates = pd.bdate_range("2023-01-02", periods=320)
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trend = np.linspace(100, 180, len(dates))
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prices = pd.DataFrame(
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{
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"SPY": trend,
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"QQQ": trend * 1.1,
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"SSO": trend * 1.5,
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"QLD": trend * 1.6,
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"UPRO": trend * 2.0,
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"TQQQ": trend * 2.2,
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"SHY": np.linspace(100, 103, len(dates)),
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"IEF": np.linspace(100, 104, len(dates)),
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"TLT": np.linspace(100, 105, len(dates)),
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"GLD": np.linspace(100, 115, len(dates)),
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"DBC": np.linspace(90, 105, len(dates)),
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},
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index=dates,
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)
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candidates = robustness.candidate_weights(prices)
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self.assertIn("TrendRiderV4", candidates)
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self.assertIn("SPY Buy&Hold", candidates)
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self.assertIn("QQQ Buy&Hold", candidates)
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if __name__ == "__main__":
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unittest.main()
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