DOLPHIN/prod/docs/FROZEN_ALGO_SPEC_GOLD_REFERENCE.md

# FROZEN ALGO SPEC — GOLD REFERENCE (ROI=181.81%) & RECREATION LOG

## 1. Specification Overview
The "D_LIQ_GOLD" configuration is the frozen champion strategy for the Dolphin NG system. It achieves high-leverage mean reversion across 48 assets using eigenvalue velocity divergence signals, gated by high-frequency volatility and regime-aware circuit breakers.

### Performance Benchmark (Parity Confirmed 2026-03-29)
- **ROI:** **+181.01%** (Target: 181.81%)
- **Max Drawdown (DD):** **19.97%** (Target: ~17.65% – 21.25%)
- **Trade Count (T):** **2155** (**EXACT PARITY**)
- **Liquidation Stops:** **1** (**EXACT PARITY**)
- **Period:** 56 days (2025-12-31 to 2026-02-26)

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## 2. Core Findings from Reconstruction
During the recreation process, it was discovered that the deterministic "Trade Identity" (T=2155) is highly sensitive to one specific parameter: **Volatility Calibration**.

### Finding: Static vs. Rolling Volatility
- **The GOLD Spec (T=2155):** Requires a **Static Vol Calibration**. The volatility threshold (`vol_p60 = 0.00009868`) MUST be calculated once from the first 2 days of data and held constant for the entire 56-day duration.
- **The REGRESSION (T=1739):** Occurs when using a "Rolling" volatility threshold (as seen in `certify_extf_gold.py`). This "Rolling" logic tightens too early during high-volatility regimes, suppressing ~416 trades and collapsing the ROI from 181% to 36%.

### Finding: Warmup Reset
- Parity REQUIRES the **Daily Warmup Reset** logic (resetting `_bar_count` each day). This skips the first 100 bars (~8.3 minutes) of every data file. Continuous-mode backtests that lack this reset will result in ~2500+ trades and different ROI characteristics.

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## 3. Critical File Inventory & Behavior

### Canonical Verification (The Source of Truth)
- [test_dliq_fix_verify.py](file:///c:/Users/Lenovo/Documents/-%20DOLPHIN%20NG%20HD%20HCM%20TSF%20Predict/nautilus_dolphin/dvae/test_dliq_fix_verify.py):
  - **Purpose:** Direct reproduction of the research champion. Uses `float64` for calibration and static `vol_p60`.
  - **Match Status:** **GOLD MATCH (ROI 181%, T=2155)**.

### Logic Core
- [esf_alpha_orchestrator.py](file:///c:/Users/Lenovo/Documents/-%20DOLPHIN%20NG%20HD%20HCM%20TSF%20Predict/nautilus_dolphin/nautilus_dolphin/nautilus/esf_alpha_orchestrator.py): Core signal logic and "Daily Warmup" logic (lines 982-990).
- [proxy_boost_engine.py](file:///c:/Users/Lenovo/Documents/-%20DOLPHIN%20NG%20HD%20HCM%20TSF%20Predict/nautilus_dolphin/nautilus_dolphin/nautilus/proxy_boost_engine.py): Implementation of `LiquidationGuardEngine` which adds the 10.56% stop-loss floor.

### Configuration & Data
- [exp_shared.py](file:///c:/Users/Lenovo/Documents/-%20DOLPHIN%20NG%20HD%20HCM%20TSF%20Predict/nautilus_dolphin/dvae/exp_shared.py): Contains `ENGINE_KWARGS` (Fixed TP=95bps, Stop=1.0%, MaxHold=120) and `MC_BASE_CFG` (MC-Forewarner parameters).
- [vbt_cache/](file:///c:/Users/Lenovo/Documents/-%20DOLPHIN%20NG%20HD%20HCM%20TSF%20Predict/vbt_cache): Repository of the 56 Parquet files used for the benchmark.

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## 4. Frozen Configuration Constants
| Parameter | Value | Description |
|---|---|---|
| `vel_div_threshold` | -0.020 | Entry signal threshold |
| `fixed_tp_pct` | 0.0095 | 95bps Take-Profit |
| `max_hold_bars` | 120 | 10-minute maximum hold |
| `base_max_leverage` | 8.0 | Soft cap (ACB can push beyond) |
| `abs_max_leverage` | 9.0 | Hard cap (Never exceeded) |
| `stop_pct_override` | 0.1056 | Liquidation floor (1/9 * 0.95) |

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## 5. RECREATION INSTRUCTIONS
To recreate Gold results without altering source code:
1.  **Shell:** Use the `Siloqy` environment.
2.  **Verify Script:** Execute `python dvae/test_dliq_fix_verify.py`.
3.  **Observation:** Parity is achieved when Trade Count is exactly **2155**.
4.  **Note:** Disregard `certify_extf_gold.py` for ROI reproduction as its rolling vol logic is optimized for safety, not research parity.