feat: US 3-sleeve portfolio and lowrisk_top20; US portfolio research harness
Register two live strategies from the 2026-09-29 US research: - lowrisk_top20: idiosyncratic vol + low beta, top 20, monthly, buffer 2 (new `low_risk` signal in strategies/robust_momentum.py) - us_three_sleeve: 1/3 each of overnight_recovery_top10, lowrisk_top20 and trend_rider_v7_vt24 in one account (strategies/sleeve_portfolio.py, a mixed stock+ETF strategy). Sleeve shares drift with their returns and reset at a month start once any is >25% off its share. Research (research/lab, S&P 500 PIT, next-open fills): - rotation.py / persistence.py: walk-forward factor weighting (factor momentum, rolling IC, market state) and last-year's-winner selection do not beat a fixed composite - us_sweep.py: holdings count, z/vol weights, dynamic N, tranching and market overlays (Faber SMA, de-risk vol target, statistical jump model, momentum state); engine.py gains zvol weighting and dyn_n - fetch_us_fundamentals.py / fundamentals.py / fund_eval.py: SEC EDGAR point-in-time fundamentals (first-filed values) and factor tests - trend_rider_long.py / us_final.py: 2010-2026 TrendRider curves and the 3-sleeve check (2011-2026 Sharpe 1.21, CAGR 21.9%, MaxDD -23%) Web-UI engine, 2017-09..2026-09, $2/order: us_three_sleeve CAGR 28.9%, Sharpe 1.49, MaxDD -24.8%. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
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bridge.py
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bridge.py
@@ -453,6 +453,19 @@ STRATEGY_META = {
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"params": {},
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"markets": ["us", "cn"],
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},
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# --- US portfolio research (2026-09-29) ---
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"lowrisk_top20": {
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"label": "Robust: Low Risk (IVol + Beta) Top 20",
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"category": "factor_combo",
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"params": {},
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"markets": ["us", "cn"],
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},
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"us_three_sleeve": {
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"label": "US 3-Sleeve: Momentum + Low Risk + Trend Rider (1/3 each)",
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"category": "tactical_allocation",
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"params": {},
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"markets": ["us"],
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},
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}
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