siloqy/prod/docs/VIOLET_V3_FINDINGS.md

VIOLET V3 — Consolidated Findings

Period: 2026-06-13 → 2026-06-15. Branch exp/pink-ditav2-sprint0-20260530. Master record of the V3 sprint (DecisionEngine SHADOW), the BLUE margin/edge study, and all parity findings. Companion to memory violet_v3_alpha_doctrine, blue_margin_envelope_study, violet_subsecond_rebuild_plan and the per-topic docs referenced inline.

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0. Governing doctrine (operator-set)

• Model BLUE, not PINK. Reference = BLUE's live Alpha Engine (holistic SOA). Behavioural/distributional fidelity, not PINK pick-parity.
• Live BLUE code is the sole doctrine. blue_parity.py is a PINK-era distillation whose fidelity must be VALIDATED (it had drift, see §3).
• Follow BLUE in all regards — no VIOLET-imposed hygiene. No filters BLUE lacks; replicate BLUE's filters exactly. vel_div spikes are signal, not garbage.
• Reactor substrate. BLUE's scan-quantized behaviour is hosted on the V0 event reactor and quantized at Q=scan initially, per-action knobs loosenable later.
• 3-layer: L1 pure alpha (decide+size as BLUE) → L2 parity harness (mock exchange) → L3 tradeability (conviction→exchange leverage + maker policy).
• Decision layer is slot-independent — VIOLET decides every scan; the slot only gates trades (execution layer). Different layers.

1. What shipped (V3a–V3.2)

Commit	Module	Content
V3a	alpha_wrappers.py	V-TYPES wrappers over live AlphaAssetSelector/AlphaBetSizer/AlphaExitEngineV7; max_leverage=9 pinned
V3b	cadence.py (+spec)	CadenceControlPlane — universal per-action tunable Q, control-plane-surfaced
V3c	decision_engine.py	VioletDecisionEngine reactor-resident SHADOW (no exec)
V3d	parity_harness.py	base-sizer median-curve parity gate vs recorded BLUE
V3e	shadow_journal.py + 22_violet_decisions.sql + launcher	reject-at-source CH journal; DARK soak wiring
V3.1	(decision_engine)	BLUE stablecoin exclusion (parity fix)
V3.2	modulation.py	EsoF size-modulation fold (BLUE SC haircut, exact)

Full violet suite green (129+ tests); ZERO shared-file edits all sprint (mechanical check per commit).

2. The bet-sizing model (validated)

Self-consistent at row level vs recorded dolphin.trade_events:

• our_leverage = entry_price·quantity / capital_before = notional/capital.
• leverage = conviction ∈ [0.5, 9] (cubic-convex strength³ curve).
• notional = capital × 0.20 (base_fraction) × leverage → our_leverage = 0.20×leverage, max ≈ 1.81.
• DUAL-LEVERAGE: conviction leverage sizes the QUANTITY (internal); exchange leverage mapped at the venue boundary via prod/bingx/leverage.py map_internal_conviction_to_exchange_leverage_target (round_half_even linear 0.5–9.0 → 1..cap; PINK/VIOLET use a max-3× cubic translator).

3. blue_parity drift (doctrine validated by evidence)

blue_parity.py passes AlphaBetSizer(max_leverage=8.0); live kernel default is 5.0; recorded conviction reaches 9.0 (gold spec). So blue_parity is NOT at parity — VIOLET pins max_leverage=9.0 explicitly (never inherits a default). Confirmed by V3d: base sizer reproduces BLUE's recorded MEDIAN curve at pearson 0.9998 / max_abs_err 0.238 with max_leverage 9 / thr −0.02 / extreme −0.05 / convexity 3.

4. BLUE margin-envelope + true-edge study (blue_margin_envelope_study.md)

Raw sum(pnl) = −$45,981 is artifact-dominated:

• duplicate-emission: 3453 rows / 2193 trade_ids, 98.3% of multi-row tids have IDENTICAL pnl (pure dup; real legs live in trade_exit_legs); one tid had 317 dup rows.
• HIBERNATE_HALT artifacts incl. ZEC −$39,164 (−73.5%, bars_held=0) = 85% of raw loss.

Cleaned (dedup + drop HIBERNATE & bars_held=0): +$47,068 (2121 trades, 58.4% win). Independent corroboration: corrected-capital trajectory grew $33,820 → $69,673 (+$35,852) in the tracked window. Two methods agree → robust.

Margin envelope (856 clean trades): single-slot (operator-confirmed, no stacking). Fit at 1× = 73.6%; fit at 2× = 100%; median wallet utilization @2× = 3.4% ⟹ capital substantially UNDER-utilized; margin never binding; edge realizable on-exchange. Recommend flat 3× exchange leverage (p95 util 90% at 2×).

Make-or-break fear REFUTED: worry was ~9× notional being infeasible; realized notional/capital maxes at 1.81 (because 0.20 base × 9), needing just 2×.

5. The under-utilization caveat (VIOLET_FINDING__MODULATION_LAYER_VS_UNDERUTILIZATION.md)

The margin study used ACTUAL recorded notionals (post-modulation), so it is NOT contradicted by the modulation layer. BUT the median ~6.8% wallet utilization is largely the EsoF haircut deliberately de-risking — NOT free headroom. ⟹ the #3 base-fraction study must not read it as reclaimable; the modulation layer is required before V4 execution (base-only would trade bigger/riskier than BLUE).

6. Regime-conditional edge (blue_margin_envelope_study.md)

Edge is regime-CONCENTRATED, not invariant: 95% of clean edge in choppy-bearish (short core signal is short-positive; long side = separate operational EFSM algo). Sub-regimes CONFIRMED inside it (univariate): BTC<MA99 +28.4/trade vs >MA99 +12.6 (2.25×); hi-DVOL +27.2 vs lo +17.1; strong-velDiv +30.8 vs weak +13.6 at EQUAL win-rate ⟹ conviction-sizing validated. MARAS labels UNRELIABLE (39% of "bearish"-labeled trades had BTC ABOVE MA99) → use composite_hash, not the label. Gates tilt only mildly (~6pts) from bull. Research TODO: stablecoin IRP signal (VIOLET_RESEARCH_TODO__STABLECOIN_IRP_SIGNAL.md).

7. Selection parity (VIOLET already matches BLUE)

• BLUE picks via IRP with the alignment gate MUTED (min_irp_alignment=0.0 = gold "no IRP filter", nautilus_event_trader.py:134/605) + sizes with scan TOP-LEVEL vel_div (:3915). VIOLET defaults min_alignment=0.0 + decide(vel_div=payload['vel_div']) = EXACT match.
• Stablecoin exclusion (V3.1): BLUE removes _STABLECOIN_SYMBOLS (10 pegged symbols) from prices_dict pre-select (:24/3906). VIOLET replicates the exact set; drift-guarded against BLUE source. (Picking itself unchanged; this is BLUE's separate exclusion gate.)

8. EsoF modulation fold (§3 of the modulation doc; V3.2)

modulation.py wraps BLUE's esof_size_mult_from_score (exact ESOF_* constants: NEUTRAL 0.8 / UNFAV 0.3 / STALE_FB 0.4 / EDGE 0.02) and applies the SC haircut step-for-step as _apply_sc_entry_size_multiplier (:3307): mult clamp [0,1] HAIRCUT-ONLY (:3316), near-1 no-op (:3318), round(lev×mult,6) / round(notional×mult,12). 8 tests. Empirical mult-recovery on 1500 recorded trades: median 1.000, EsoF haircut bands (0.65/0.8/0.9/0.3) VISIBLE → fold validated. Not yet wired into the live engine (needs EsoF HZ score plane + restart, held).

OPEN — the 28% upward tail (recorded_leverage / base > 1.05): localized to mid-range vel_div ONLY (−0.02→−0.05 where base<9: 36–60% boost; ≤−0.06 where base=9: 0%). NOT EsoF (haircut-only), NOT flat — a regime-dependent conviction-curve STEEPENER (distribution bimodal at −0.04, median matched). = almost certainly the "gold"/ACB-adjacent UPWARD sizing organ. Full per-trade parity = base × EsoF-haircut(done) × steepener(NEXT). Sizing-engine note: live BLUE sizes via AlphaBetSizer (docstring: "Matches dolphin_vbt_real.py sizing"). dolphin_vbt_real is the gold-standard BACKTEST engine used as the BENCHMARK for BLUE Alpha-Engine algo compliance — likely NOT the live sizer, but it is the authoritative ORACLE for the exact conviction-curve math (and may be imported/reused for exact code). For exact-parity work on the steepener, consult vbt_real as the gold reference; check whether the live path reuses its code.

9. Shadow soak validation (2026-06-14/15)

Faithful DARK soak (threshold −0.02), 9h+ stable, single session:

• 4,878 decisions, 0 stablecoin leak, 0 bad rows (V-TYPES/reject-at-source), 0 orders, 0 errors, spool steady 4.5M. 20 distinct real assets.
• Faithfulness: all SHORT+actuated; all vel_div < −0.02; sizer cubic curve reproduced live (conviction p50 1.315 = base formula at median vel_div −0.0337); notional_fraction max exactly 1.80; schema 100% compliant.
• Statistics: conviction min 0.5/p50 1.32/avg 3.91/max 9 (BLUE-shaped); temporal conviction swings 2.6→6.5/hr (tracks vol regime).
• Diversity: 20 assets, top-2 ~31%, well-spread.
• Anomalies: vel_div spikes to −605 (legitimate signal, saturate to 9); "duplication" avg 14.5 = sticky-signal re-decisions at ≤1/scan (correct cadence). NO defects.

VIOLET vs BLUE comparison: BLUE doesn't log per-scan entry decisions (only trades + v7 exits); signal-level vel_div matches the scan archive exactly. BLUE's 69 trades in window across 6 assets — 100% in VIOLET's decision universe, 100% timing co-located (same asset, ±5min). Frequency differs by slot only (execution layer, deferred).

10. Open items / next steps

1. Gold/ACB conviction-curve steepener — wrap the upward sizing organ (the 28% tail). Live sizer = AlphaBetSizer; consult dolphin_vbt_real (the gold-standard backtest oracle BLUE is benchmarked against) for the exact curve math / possible code reuse. Required for full per-trade leverage parity.
2. Wire EsoF score plane into the live decision engine (HZ _read_esof_payload equiv)
   • restart to fold modulation into the soak.
3. Trade/slot-granularity comparison (episode-collapse) — deferred until VIOLET has comparable execution-layer facilities (decision layer already faithful).
4. Base-fraction sizing study (VIOLET_STUDY_SPEC__BASE_FRACTION_SIZING.md) — gated on regime-robustness; respect the de-risking caveat (§5).
5. composite_hash multivariate sub-regime model (deeper §6).
6. V4 = execution on (single asset, conservative caps) — only after the modulation layer is complete.
7. Operator: VST keys for live exec; stays DARK until then.

11. Live state at time of writing

dolphin_violet DARK, SHADOW ON (faithful −0.02), 0 orders, stablecoin fix live, EsoF fold built+committed but NOT yet wired. Overnight monitor report at prod/VIOLET_dev/reports/violet_overnight_soak_20260614.log.