feat: 量化引擎加固 — 新增测试 + 数据/因子/回测层优化

- 新增 finance/tests/ 6 个测试套件（agents/backtest/dao_upsert/factors/features/fundamental_lookahead） - 数据层: data_manager / dao 优化，新增 upsert 逻辑 - 因子层: 基本面因子抽象定位 _mapping、ROE/PE/PB 重构 - 回测层: vectorbt/engine 大改动（251 行），report 增强 - ML 层: features/backtest_integration 特征工程与回测优化 - CLI: agent_cli 重构 - config/settings 扩充配置项
2026-08-31 14:01:06 +08:00
parent 6acf938caf
commit 73d191b43a
28 changed files with 1418 additions and 373 deletions
@@ -0,0 +1,81 @@
+"""
+回测引擎回归测试：T+1 成交、涨跌停拒成交、report DatetimeIndex、截面组合资金切分。
+"""
+import sys
+import os
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+import numpy as np
+import pandas as pd
+import pytest
+
+vectorbt = pytest.importorskip("vectorbt")
+
+from backtest.vectorbt.engine import VectorBTEngine
+from backtest.strategies.momentum_breakout import MomentumBreakoutStrategy
+
+
+@pytest.fixture
+def price_df():
+    idx = pd.date_range('2024-01-01', '2024-06-30', freq='B').strftime('%Y%m%d')
+    close = 100 * np.cumprod(1 + np.random.default_rng(42).normal(0.0005, 0.02, len(idx)))
+    open_p = np.roll(close, 1); open_p[0] = close[0]
+    pre_close = np.roll(close, 1); pre_close[0] = close[0]
+    return pd.DataFrame({
+        'open': open_p, 'close': close, 'pre_close': pre_close,
+        'pct_chg': (close / pre_close - 1) * 100,
+    }, index=idx)
+
+
+def test_backtest_runs_with_t1(price_df):
+    eng = VectorBTEngine()
+    rep = eng.run(MomentumBreakoutStrategy(), price_df, t_plus_one=True, limit_check=True, slippage=0.0002)
+    assert not rep.equity_curve.empty
+    assert isinstance(rep.equity_curve.index, pd.DatetimeIndex)
+
+
+def test_limit_up_blocks_buy(price_df):
+    eng = VectorBTEngine()
+    p = price_df.copy()
+    i = p.index[-5]
+    p.loc[i, 'close'] = p.loc[i, 'pre_close'] * 1.099
+    p.loc[i, 'pct_chg'] = 9.9
+    entries = pd.Series(True, index=p.index)
+    exits = pd.Series(False, index=p.index)
+    eff, _ = eng._apply_limit_filters(entries, exits, p)
+    assert not bool(eff.loc[i]), "涨停日应抑制买入"
+    assert eff.dtype == bool
+
+
+def test_limit_down_blocks_sell(price_df):
+    eng = VectorBTEngine()
+    p = price_df.copy()
+    i = p.index[-7]
+    p.loc[i, 'close'] = p.loc[i, 'pre_close'] * 0.901
+    p.loc[i, 'pct_chg'] = -9.9
+    _, exf = eng._apply_limit_filters(
+        pd.Series(False, index=p.index), pd.Series(True, index=p.index), p)
+    assert not bool(exf.loc[i]), "跌停日应抑制卖出"
+
+
+def test_normal_day_keeps_entry(price_df):
+    eng = VectorBTEngine()
+    p = price_df.copy()
+    eff, _ = eng._apply_limit_filters(
+        pd.Series(True, index=p.index), pd.Series(False, index=p.index), p)
+    assert eff.sum() > 0
+
+
+def test_cross_section_investable_curve():
+    idx = pd.date_range('2024-01-01', '2024-06-30', freq='B').strftime('%Y%m%d')
+    uni = {}
+    for i in range(4):
+        c = 50 * np.cumprod(1 + np.random.default_rng(i).normal(0.0003, 0.018, len(idx)))
+        o = np.roll(c, 1); o[0] = c[0]
+        uni[f"600{i:04d}.SH"] = pd.DataFrame({'open': o, 'close': c}, index=idx)
+    eng = VectorBTEngine(initial_capital=100000)
+    rep = eng.run_cross_section(MomentumBreakoutStrategy(), uni, rebalance_freq="M")
+    assert not rep.equity_curve.empty
+    assert isinstance(rep.equity_curve.index, pd.DatetimeIndex)
+    # 组合净值可联合投资：末值与初始资本量级相当，不会因每股满额而超限
+    assert rep.equity_curve.iloc[-1] > 0