# VIOLET Finding — The Sizing-Modulation Layer vs. the Capital-Under-Utilization Result **Status:** Finding / caveat, 2026-06-13. Separate doc by operator request. Qualifies (does NOT overturn) the [[blue_margin_envelope_study]] and constrains the `VIOLET_STUDY_SPEC__BASE_FRACTION_SIZING.md` (#3) and any pre-V4 sizing work. ## TL;DR The newly-isolated downstream **sizing-modulation layer** (SC-haircut / ACB / OB-cascade / "gold" — the organs that ride along ACBv6) does **not** counter the margin study: that study used **actual recorded notionals**, which are already post-modulation. But it **sharpens** what "under-utilized capital" means, and makes the modulation layer a **required** pre-execution component for VIOLET — not optional. ## 1. Why the margin study is NOT contradicted The margin/viability study computed `our_leverage = entry_price·quantity / capital_before` from `dolphin.trade_events` — i.e. from the **notionals BLUE actually traded**, haircuts and boosts already baked in. The modulation is therefore *inside* the measured numbers, not a missed factor. Conclusions stand on the as-traded data: - max realized `our_leverage` ≈ **1.81** - **100%** of trades margin-feasible at **2×** exchange leverage - **+$47k** clean deduped edge ## 2. How recorded leverage decomposes (the discovery) Recorded conviction `leverage` is **NOT** the base bet-sizer output alone: ``` recorded_leverage(trade) = base_sizer(vel_div) ± modulation(SC, ACB, OB, gold) ``` - **base_sizer(vel_div)** — cubic-convex strength³ curve; VIOLET's V3a `VioletBetSizer` reproduces it (validated on binned MEDIANS: vd −0.03→0.83, −0.04→2.78, −0.05→9.0 with max_leverage=9 / thr −0.02 / extreme −0.05 / convexity 3). - **modulation** — mostly **downward haircuts** (mins far below the median per vel_div bin), with some upward boosts to the 9 cap. This is the per-trade scatter that drops exact per-trade parity to ~34% while the median curve matches. ## 3. The sharpening (this is the load-bearing part) The study's **median wallet utilization was ~6.8%** (`our_leverage` p50 ≈ 0.068). That low median is **largely the haircut layer at work** — BLUE deliberately sized most trades far below the base curve. The **max 1.81** is the *un-haircut, base-saturated* tail. Consequences: 1. **Margin feasibility is robust** even if the haircuts are later dropped: the study's worst case (1.81) already equals the base-saturated value, and 2× covers it. Sizing at full base does not break margin. 2. **"Under-utilized ⇒ free ROI" is now GUARDED.** Much of the idle ~93% is **not waste** — it is the modulation layer **deliberately de-risking** (cutting size on lower-conviction / higher-risk setups). It is risk knowledge encoded as size. ## 4. Binding implications - **#3 base-fraction study MUST NOT read the 6.8% median as free headroom.** A large part of it is risk-management. Any base-fraction increase must be evaluated *with* the modulation layer modeled, conditioned on the regime-robustness work — never by naively reclaiming the idle capital. - **The modulation layer is REQUIRED before live execution (V4).** VIOLET running the **base sizer alone** would size *bigger than BLUE did* on exactly the trades BLUE chose to haircut → utilization jumps from ~7% median toward the base, and **realized risk/return diverges from the recorded +$47k** (more variance, possibly worse risk-adjusted). Median-curve base parity (V3d) is necessary but **not sufficient** for faithful BLUE replication. - **New deferred task (pre-V4):** wrap the SC-haircut / ACB / OB-cascade / "gold" modulation organs as a VIOLET sizing-modulation layer on top of the base `VioletBetSizer`, with its own per-trade parity gate vs recorded `leverage`. ## 5. Related [[blue_margin_envelope_study]] · [[violet_v3_alpha_doctrine]] (#9 keystone, #11 parity finding) · `VIOLET_STUDY_SPEC__BASE_FRACTION_SIZING.md` · `prod/clean_arch/violet/alpha_wrappers.py` (base sizer) · live organs in `prod/nautilus_event_trader.py` (`_apply_sc_entry_size_multiplier`, `_record_sc_haircut`, `AdaptiveCircuitBreaker`).