feat: us_momentum_qqq_trend; alpha-vs-QQQ research across new data sources

Register us_momentum_qqq_trend: half overnight_recovery_top10, half a QQQ
trend sleeve (strategies/qqq_trend.py: 200-day switch times a 30% vol target,
held as TQQQ + SHY). Mixed stock+ETF, US only (extra tickers QQQ, SHY, TQQQ).

Research (research/lab/): alpha against QQQ with a 2006-16 design / 2017-26
holdout split (alpha.py, qqq_scan.py, beat_qqq.py); leverage and drawdown
frontier (levered_book.py, us_target50.py); synthetic 3x ETFs from 1990 and
TrendRider/QQQ-trend stress tests (fetch_long_history.py, letf_history.py,
vol_trend.py); short-horizon sleeves, diversifiers, industry momentum,
earnings-announcement returns; new point-in-time data sources: SEC Form 4
insider trades (fetch_insider.py, insider.py), 10-K/10-Q text similarity,
8-K earnings dates and SIC codes (fetch_lazy_prices.py, lazy_prices.py), and
an S&P 400/600 universe from iShares holdings (fetch_us_mid.py, panel_mid.py).

Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>

tests/test_sleeve_portfolio.py

@@ -10,8 +10,9 @@ import pandas as pd
 import trader
 from strategies.permanent import ETF_UNIVERSE
 from strategies.robust_momentum import RobustMomentumStrategy
+from strategies.qqq_trend import QQQVolTrend
 from strategies.sleeve_portfolio import (SleevePortfolioStrategy, decisions, drifting_shares,
-                                         us_three_sleeve)
+                                         us_momentum_qqq_trend, us_three_sleeve)
 
 
 def _bars(n_days: int = 520, n_stocks: int = 30, seed: int = 1) -> dict[str, pd.DataFrame]:
@@ -89,5 +90,51 @@ class SleevePortfolioTests(unittest.TestCase):
         self.assertEqual(trader.strategy_fields("us_three_sleeve"), ("close", "open"))
 
 
+def _qqq_bars(n_days: int = 520, drift: float = 0.0005, seed: int = 2) -> dict[str, pd.DataFrame]:
+    """Stocks plus the combo's ETFs only (its live universe: S&P 500 + QQQ, TQQQ, SHY)."""
+    other = [c for c in ETF_UNIVERSE if c not in ("TQQQ", "SHY")]
+    bars = {f: b.drop(columns=other) for f, b in _bars(n_days, seed=seed).items()}
+    rng = np.random.default_rng(seed + 1)
+    idx = bars["close"].index
+    q = pd.Series(100 * np.exp(np.cumsum(rng.normal(drift, 0.012, n_days))), index=idx)
+    for f in bars:
+        bars[f]["QQQ"] = q if f == "close" else q.shift(1).bfill()
+    return bars
+
+
+class QQQTrendTests(unittest.TestCase):
+    def test_weights_on_a_day_ignore_that_day_and_later_closes(self):
+        close = _qqq_bars()["close"]
+        base = QQQVolTrend().generate_signals(close)
+        shocked = close.copy()
+        cut = close.index[400]
+        shocked.loc[cut:, "QQQ"] *= 0.5
+        pd.testing.assert_frame_equal(base.loc[:cut], QQQVolTrend().generate_signals(shocked).loc[:cut])
+
+    def test_out_below_the_average_and_capped_above_it(self):
+        up = _qqq_bars(drift=0.002)["close"]
+        down = _qqq_bars(drift=-0.002)["close"]
+        w_up = QQQVolTrend(cap=1.5).generate_signals(up).iloc[260:]
+        w_down = QQQVolTrend().generate_signals(down).iloc[260:]
+        self.assertLessEqual(w_up["TQQQ"].max(), 0.5 + 1e-12)
+        self.assertGreater(w_up["TQQQ"].mean(), 0.3)
+        np.testing.assert_allclose(w_up[["TQQQ", "SHY"]].sum(axis=1), 1.0)
+        self.assertLess(w_down["TQQQ"].mean(), 0.05)
+
+    def test_momentum_qqq_trend_is_a_us_mixed_strategy(self):
+        self.assertIsInstance(trader.STRATEGY_REGISTRY["us_momentum_qqq_trend"](), SleevePortfolioStrategy)
+        self.assertEqual(set(trader.strategy_extra_tickers("us_momentum_qqq_trend")), {"QQQ", "SHY", "TQQQ"})
+        self.assertFalse(trader.strategy_supports_market("us_momentum_qqq_trend", "cn"))
+        bars = _qqq_bars()
+        strat = us_momentum_qqq_trend()
+        w = strat.generate_signals(bars)
+        self.assertLessEqual(w.sum(axis=1).max(), 1.0 + 1e-9)
+        stocks = [c for c in w.columns if c[1:].isdigit()]
+        self.assertLessEqual(int((w[stocks].iloc[-1] > 0).sum()), 10)
+        self.assertGreater(w[["TQQQ", "SHY"]].iloc[-1].sum(), 0.3)
+        days = bars["close"].index[-2:]
+        pd.testing.assert_frame_equal(trader.bar_session_weights(strat, bars, days), w.loc[days])
+
+
 if __name__ == "__main__":
     unittest.main()