πŸ“Š Reports β€Ί Regime Gate

🧭 Regime Gate β€” Quant-Lab HMM & Survivor Filter

πŸ“Š Reports Hub Regime Detection πŸ€– HAL 9000
Current Market Regime Β· 3-state Gaussian HMM on SPY (quant-lab)
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Fetching the baked regime state from /api/regime-gate…
Regime confidence
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smoothed posterior P(regime | all data)
Confidence
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Days in regime
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Since
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Data
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Gate freshness
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πŸ“† Last 120 Trading Days β€” SPY, Regime-Shaded

SPY close over the last 120 trading days, with the background shaded by the HMM's decoded regime β€” green Strong Bull, red Strong Bear, amber Choppy. Long same-color runs are stable regimes; rapid flips mean the tape is transitioning.
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Compact strip view β€” each slice is one trading day:
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🎯 Strategy Styles β€” In Season vs Benched

The DynamicAllocator only deploys strategy styles that historically work in the current regime: mean-reversion in Choppy, trend + momentum in Strong Bull, defensive/cash in Strong Bear. Everything else sits on the bench until the regime turns.

βœ… Favored now

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⏸ Benched

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πŸ”Ž Per-Stock Gate Check

Type a ticker (or arrive with ?symbol=) to see whether it survived the six-filter walk-forward funnel, which styles carry its edge, and how that edge lines up with today's regime.

πŸ† Funnel Survivors β€” Validated Edges

Strategy Γ— asset pairs that passed all six walk-forward filters (OOS Sharpe, drawdown, overfit ratio, trade count, hold time, window consistency) AND the bootstrap stress test. This is the entire tradeable edge inventory across the 30-asset universe β€” everything else failed validation. Bars are colored by style; the dashed amber line is the 0.5 OOS Sharpe funnel floor every survivor had to clear.
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Full survivor detail:
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πŸ“Š Regime Occupancy β€” Full Sample

How the HMM splits the whole ~15-year SPY history across the three regimes β€” the share of trading days spent in each.
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πŸ“š Learn this system

Two companion resources for the Regime Gate: the flipbook walks the 9,000-candidate strategy funnel this page reports on, and the video is the explainer for how this system was built.

πŸ“– The 9,000 Strategy

Flipbook β€” how 9,000 candidate strategy Γ— asset combinations get distilled through the six-filter walk-forward funnel into the survivor list above.
Open flipbook β†—

🎬 Building an Institutional-Grade AI Backtester with Claude

The explainer video for how this system was built β€” the quant-lab HMM regime engine, the walk-forward funnel, and the Regime Gate you are looking at.
Watch on YouTube β†—