initial: import DOLPHIN baseline 2026-04-21 from dolphinng5_predict working tree

Includes core prod + GREEN/BLUE subsystems:
- prod/ (BLUE harness, configs, scripts, docs)
- nautilus_dolphin/ (GREEN Nautilus-native impl + dvae/ preserved)
- adaptive_exit/ (AEM engine + models/bucket_assignments.pkl)
- Observability/ (EsoF advisor, TUI, dashboards)
- external_factors/ (EsoF producer)
- mc_forewarning_qlabs_fork/ (MC regime/envelope)

Excludes runtime caches, logs, backups, and reproducible artifacts per .gitignore.

nautilus_dolphin/Tail_Stats_FINAL_TEST.md

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+Prompt: Definitive Convex Hazard Validation for Micro-Entropy (v50)
+You are to rigorously test whether extreme micro-entropy (v50_lambda_max_velocity) represents a true convex hazard zone that justifies nonlinear leverage tapering.
+The goal is not correlation. The goal is economic exploitability.
+Follow these steps precisely.
+1️⃣ Data Requirements
+Use:
+Entire available historical dataset, use the fast vbt backtesting engine.
+Same production trading engine
+Same 6.0x leverage ceiling
+No modification to signal logic
+T-1 precursor alignment only (strict shift)
+Define:
+Daily return
+Tail event = bottom 10% of daily returns (fixed percentile, global)
+2️⃣ Core Conditional Hazard Curve
+Compute:
+Baseline:
+Copy code
+
+P(Tail)
+Then for v50 (T-1):
+For thresholds:
+75th percentile
+85th percentile
+90th percentile
+95th percentile
+97.5th percentile
+99th percentile
+Compute:
+Copy code
+
+P(Tail | v50 > threshold)
+Also record:
+Number of days above threshold
+Number of tail days inside threshold
+95% confidence interval (Wilson or exact binomial)
+Output full hazard curve.
+We are looking for nonlinear convex acceleration, not linear drift.
+3️⃣ Economic Viability Test (CRITICAL)
+For each threshold:
+Compute:
+Mean return on spike days
+Mean return on non-spike days
+Median return
+Standard deviation
+Contribution of spike days to total CAGR
+Then simulate:
+Scenario A: Static 6.0x (baseline)
+Scenario B: 6.0x with taper when v50 > threshold
+(e.g., reduce leverage to 5.0x or apply 0.8 multiplier)
+Run:
+Median CAGR
+5th percentile CAGR
+P(>40% DD)
+Median max DD
+Terminal wealth distribution (Monte Carlo, 1,000+ paths)
+If tapering:
+Reduces DD materially
+Does not reduce median CAGR significantly
+Improves 5th percentile CAGR
+→ Hazard is economically real.
+If CAGR drops more than DD improves, → It is volatility clustering, not exploitable convexity.
+4️⃣ Stability / Overfit Check
+Split data:
+First 50%
+Second 50%
+Compute hazard curve independently.
+If convexity disappears out-of-sample, discard hypothesis.
+Then run rolling 60-day window hazard estimation. Check consistency of lift.
+5️⃣ Interaction Test
+Test whether hazard strengthens when:
+Copy code
+
+v50 > 95th AND cross_corr > 95th
+Compute:
+P(Tail | joint condition)
+If joint hazard > 50% with low frequency, this may justify stronger taper.
+If not, keep taper mild.
+6️⃣ Randomization Sanity Check
+Shuffle daily returns (destroy temporal relation). Recompute hazard curve.
+If similar convexity appears in shuffled data, your signal is statistical artifact.
+7️⃣ Decision Criteria
+Micro-entropy qualifies as a true convex hazard zone only if:
+P(Tail | >95th) ≥ 2.5× baseline
+Convex acceleration visible between 90 → 95 → 97.5
+Spike frequency ≤ 8% of days
+Taper improves 5th percentile CAGR
+Out-of-sample lift persists
+If any of these fail, reject hypothesis.
+8️⃣ Final Output
+Produce:
+Hazard curve table
+Economic impact table
+Out-of-sample comparison
+Monte Carlo comparison
+Final verdict:
+True convex hazard
+Weak clustering
+Statistical artifact
+No narrative.
+Only statistical and economic evidence.