mirror of
https://ghfast.top/https://github.com/aeroxw/easy-tdx.git
synced 2026-09-12 16:54:17 +08:00
66 lines
2.5 KiB
Python
66 lines
2.5 KiB
Python
"""Test RebalanceEngine."""
|
|
from __future__ import annotations
|
|
|
|
import numpy as np
|
|
import pandas as pd
|
|
|
|
from easy_tdx.portfolio.optimizer import EqualWeightOptimizer, FactorWeightedOptimizer
|
|
from easy_tdx.portfolio.rebalance import RebalanceEngine
|
|
|
|
|
|
def _make_market(n_stocks: int = 10, n_days: int = 120, seed: int = 42) -> dict[str, pd.DataFrame]:
|
|
rng = np.random.default_rng(seed)
|
|
data = {}
|
|
for i in range(n_stocks):
|
|
close = 10.0 + np.cumsum(rng.normal(0.01, 0.5, n_days))
|
|
close = np.maximum(close, 1.0)
|
|
data[f"{i:06d}"] = pd.DataFrame({
|
|
"datetime": pd.date_range("2024-01-01", periods=n_days, freq="D"),
|
|
"open": close, "high": close + 0.3, "low": close - 0.3,
|
|
"close": close,
|
|
"vol": rng.integers(1e5, 1e7, n_days).astype(float),
|
|
"amount": close * 1e6,
|
|
})
|
|
return data
|
|
|
|
|
|
class TestRebalanceEngine:
|
|
def test_basic_run(self):
|
|
engine = RebalanceEngine(
|
|
optimizer=EqualWeightOptimizer(),
|
|
factor_name="momentum_20d", n_stocks=5,
|
|
rebalance_freq="M", cash=1_000_000,
|
|
)
|
|
result = engine.run(_make_market(), start_date=20240101, end_date=20240430)
|
|
assert len(result.states) > 0
|
|
assert len(result.rebalance_dates) > 0
|
|
assert len(result.equity_curve) > 0
|
|
assert "total_return" in result.performance
|
|
|
|
def test_with_factor_weighted(self):
|
|
engine = RebalanceEngine(
|
|
optimizer=FactorWeightedOptimizer(),
|
|
factor_name="momentum_20d", n_stocks=5,
|
|
)
|
|
result = engine.run(_make_market(), start_date=20240101, end_date=20240430)
|
|
assert len(result.states) > 0
|
|
|
|
def test_empty_data(self):
|
|
result = RebalanceEngine(optimizer=EqualWeightOptimizer()).run({})
|
|
assert result.performance["total_return"] == 0.0
|
|
|
|
def test_equity_curve_dates_sorted(self):
|
|
result = RebalanceEngine(
|
|
optimizer=EqualWeightOptimizer(), rebalance_freq="M",
|
|
).run(_make_market(), start_date=20240101, end_date=20240430)
|
|
dates = result.equity_curve["datetime"].tolist()
|
|
assert dates == sorted(dates)
|
|
|
|
def test_trades_recorded(self):
|
|
engine = RebalanceEngine(
|
|
optimizer=EqualWeightOptimizer(), n_stocks=3, rebalance_freq="M",
|
|
)
|
|
result = engine.run(_make_market(), start_date=20240101, end_date=20240430)
|
|
assert len(result.trades) > 0
|
|
assert "BUY" in result.trades["direction"].values
|