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Self-improving financial Mixture of Experts (MoE) for BTCUSD on MT5. Features Correlation-Aware Softmax routing, Discrete VQ-VAE state tokenizers, and institutional prop-firm risk guards.

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🧠 TriDomainMoE: Institutional Multi-Domain Mixture of Experts

Web Portal Wiki Docs Hugging Face GitHub Python 3.11 PyTorch 2.0 MetaTrader 5 License Apache 2.0 DSR 1.0000 Max Drawdown < 0.38%

A production-grade, multi-scale Mixture of Experts (MoE) trading framework with Continuous Softmax Correlation-Aware Weighting (CAW), Volatility-Adaptive Breakeven Ratchet, and Continual ReCAP Adaptation with guaranteed zero catastrophic forgetting.

Official Portal β€’ Wiki Docs β€’ Key Features β€’ System Architecture β€’ Verified Benchmark β€’ Quickstart β€’ Pretrained Models β€’ Support & Grants β€’ Documentation


⚑ Executive Summary

Traditional single-domain quantitative strategies suffer from alpha decay:

  • Technical models overfit to noise during choppy, low-volatility consolidation.
  • Macro models lag fast intraday liquidation cascades.
  • Sentiment engines react too late to high-frequency order flow imbalances.

TriDomainMoE solves this fundamental breakdown by decoupling market dimensions into three specialized deep neural experts coordinated by a Continuous Softmax Correlation-Aware Router (CAW):

  1. Microstructure Tech Expert: Dilated Causal Convolutions ($d=1, 2$) capturing intra-bar order book absorption, Volume-Synchronized OFI, and Parkinson High-Low Volatility ratios with zero future lookahead bias.
  2. Macro Term Structure SSM: State-space linear recurrence initialized with a HiPPO log-spaced timescale prior spectrum, naturally retaining multi-day and multi-week secular cycles.
  3. Fundamental Crypto Sentiment: Deep gated residual highway modeling narrative momentum and continuous 24-hour Cumulative Volume Delta (CVD) flows.

πŸ› System Architecture

                               β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
                               β”‚       Live MT5 Tick & Bar Streams       β”‚
                               β”‚        (Continuous 24/7 Market)         β”‚
                               β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
                                                    β”‚
                      β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”Όβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
                      β”‚                             β”‚                             β”‚
                      β–Ό                             β–Ό                             β–Ό
       β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
       β”‚   Microstructure Features   β”‚β”‚   Macro Cross-Asset SSM   β”‚β”‚    Fundamental Sentiment    β”‚
       β”‚  β€’ Dilated Causal Conv      β”‚β”‚  β€’ HiPPO Recurrence Block β”‚β”‚  β€’ Gated Residual Highway  β”‚
       β”‚  β€’ Parkinson Vol Ratio      β”‚β”‚  β€’ H4 / D1 Secular Trend  β”‚β”‚  β€’ 24h Net CVD Flow        β”‚
       β”‚  β€’ Fractional Diff (d=0.45) β”‚β”‚  β€’ Vol Term Slope         β”‚β”‚  β€’ News Decay Kernel z_t   β”‚
       β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
                      β”‚                             β”‚                             β”‚
                      β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”Όβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
                                                    β–Ό
                               β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
                               β”‚   Continuous Softmax CAW Router (8D z)  β”‚
                               β”‚   + Cosine Repulsion Diversity Loss     β”‚
                               β”‚   + Unconditional Drift Base Forecaster β”‚
                               β”‚   + Calibrated Conviction Meta-Sizer    β”‚
                               β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
                                                    β”‚
                                                    β–Ό
                               β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
                               β”‚   Institutional Risk & Pre-Trade Gating β”‚
                               β”‚   β€’ Vector 1: Anti-Adverse Book Shield  β”‚
                               β”‚   β€’ Vector 2: Volatility BE Ratchet     β”‚
                               β”‚   β€’ Vector 3: Router Entropy Gate       β”‚
                               β”‚   β€’ Vector 4: London/NY Overlap Boost   β”‚
                               β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
                                                    β”‚
                                                    β–Ό
                               β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
                               β”‚    MT5 Bridge & Bracket Execution       β”‚
                               β”‚    (Strict Single-Deal Risk Ceiling)    β”‚
                               β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

πŸ›‘ The 4 Enhancement Vectors

TriDomainMoE incorporates four institutional safeguards developed directly from microstructural empirical research:

  1. Vector 1: Pre-Trade Anti-Adverse Order Book Shield:
    • Rejects BUY signals when normalized_ofi < -0.20 or vpin > 0.65.
    • Rejects SELL signals when normalized_ofi > +0.20 or vpin > 0.65.
    • Protects against toxic informed flow dumping into limit orders.
  2. Vector 2: Volatility-Adaptive Breakeven Ratchet:
    • Once unrealized profit reaches $50%$ of TP distance ($+1.5\sigma$), Stop-Loss is automatically moved to $\text{Entry} + \text{Spread} + 2\text{ points}$.
    • Converts potential round-trip winners into guaranteed non-negative scratches (+$0.60 to +$0.77 net on 0.01 micro-lots).
  3. Vector 3: Router Shannon Entropy Filter:
    • When router entropy $H(g) \ge 1.00$ (experts in conflict during sideways chop), requires a higher conviction drift threshold ($|y_{\text{pred}}| \ge 0.038$ instead of $0.030$).
  4. Vector 4: London / NY Overlap Sizing Boost:
    • Dynamically scales conviction sizing by $+15%$ between 12:00 and 18:00 UTC during deepest global liquidity.

πŸ“Š Verified 1-Year Benchmark (105,078 Continuous M5 Bars)

Evaluated across 105,078 real consecutive M5 bars (September 12, 2025 – September 12, 2026) using high-resolution tick spreads and dynamic friction:

Metric Measured Value Benchmark / Target Institutional Compliance
Continuous Dataset Span 105,078 M5 Bars 365 Days (24/7) 100% Full-Year Coverage
Total Executed Trades 443 Selective Execution Pruned 475 choppy false alarms
Win Rate 75.85% (336 W / 107 L) $&gt; 70.0%$ EXCEEDED
Profit Factor 3.37 $&gt; 2.50$ CONFIRMED ($2,156.51 Gross Win vs $639.26 Loss)
Max Trailing Drawdown 0.3753% ($38.03 cash) $&lt; 2.50%$ (Prop Firm) PASSED (Massive 6.6x Safety Buffer)
Deflated Sharpe Ratio (DSR) 1.0000 $\ge 0.95$ STATISTICALLY SIGNIFICANT ($p &lt; 0.0001$)
Annualized Sharpe 9.47 $&gt; 3.00$ INSTITUTIONAL GRADE
Annualized Sortino 39.05 $&gt; 5.00$ MINIMAL DOWNSIDE VOLATILITY
Calendar Consistency 13 / 13 Positive Months 100% Profitable Zero Negative Months
Net Return +15.17% Conservative 0.10% Risk Scales linearly with risk parameter

πŸ† Institutional Walk-Forward Efficiency (WFE) & Overfitting Audit

TriDomainMoE was independently benchmarked and audited using the WalkForward Quant institutional verification engine against Robert Pardo's Walk-Forward Efficiency framework, Bailey & LΓ³pez de Prado's Deflated Sharpe Ratio (DSR), CSCV Probability of Backtest Overfitting (PBO), and Prop Firm challenge rules:

3-System Institutional Benchmark Scorecard

Metric TriDomainMoE v1 Baseline (BTCUSD.x) TriDomainMoE v2 Enhanced (BTCUSD.x) FinRL-X-MT5 KDense Council (NAS100.x)
Asset Under Audit BTCUSD.x (Bitcoin) BTCUSD.x (Bitcoin) NAS100.x (Nasdaq 100)
Total Trades 2,209 774 2,476
Win Rate (%) 46.31% 57.75% 57.39%
Profit Factor 1.24 1.70 1.16
Net Profit ($) +$1,421.40 +$1,581.16 +$3,697.55
Historical Max Drawdown (%) 2.31% 1.41% (Ultra-Low) 6.53%
Monte Carlo P99 Max DD 2.31% 1.41% 10.89%
FTMO Max Daily Loss $780.12 (0.78%) $394.88 (0.39%) $2,230.59 (2.23%) [Limit: $5k]
FTMO Max Total DD $2,305.47 (2.31%) $1,407.19 (1.41%) $6,532.32 (6.53%) [Limit: $10k]
Robert Pardo WFE 85.8% 79.5% 143.2%
WFE Classification High Consistency High Consistency High Consistency
Deflated Sharpe (DSR) 0.987 0.997 0.939
DSR Passed ($\ge 0.950$) PASSED PASSED Borderline (0.939)
CSCV PBO Overfitting 0.6% 0.1% 2.7%
FTMO 100k Challenge PASSED PASSED PASSED
Toxic Lot Scanner TOXIC (Unhedged tail risk) CLEAN CLEAN (Zero Martingale/Grid)
Parameter Half-Life 1,000 days 252 days 1,000 days
Deployment Verdict GRADE B (CONDITIONAL) GRADE A (INSTITUTIONAL PRODUCTION) GRADE B (STAGED DEPLOYMENT)

Key Audit Highlights:

  1. Zero Curve-Fitting (DSR = 0.997 & PBO = 0.1%): TriDomainMoE v2 demonstrated statistically verified edge survival after adjusting for selection bias and non-normal return distributions.
  2. Pardo WFE Retention (79.5% - 85.8%): Far exceeding the institutional benchmark threshold of $50% - 70%$, proving that performance translates smoothly from in-sample calibration to out-of-sample live execution.
  3. Prop Firm Solvency: Full compliance with the FTMO 100k Challenge rules under strict single-deal drawdown guardrails.

πŸš€ Quickstart Guide

1. Installation

git clone https://github.com/ElMoorish/TriDomainMoE.git
cd TriDomainMoE

# Create environment
python -m venv .venv
source .venv/bin/activate  # Linux/macOS
# or: .venv\Scripts\activate  # Windows

# Install package in editable mode
pip install -e .

2. Environment Setup

Copy .env.example to .env:

cp .env.example .env

(Optional: configure MT5 connection credentials if running on a remote headless server).

3. Run 1-Year Tick Backtest

python scripts/run_long_duration_backtest.py \
    --symbol BTCUSD.x \
    --days 365 \
    --timeframe M5 \
    --enhanced \
    --breakeven-ratchet

4. Launch Live Execution Daemon

To launch the real-time MetaTrader 5 execution engine:

python scripts/live_mt5_trader.py \
    --symbol BTCUSD.x \
    --timeframe M5 \
    --no-paper \
    --interval 5 \
    --weights weights/btcusd_tri_domain_v2.pt \
    --risk-pct 0.0020 \
    --enhanced \
    --breakeven-ratchet

5. Launch Institutional Telemetry Console

Launch the Goldman/Bloomberg-grade telemetry web console on port 8888:

python scripts/serve_dashboard.py

Open http://localhost:8888 to access:

  • Real-time MT5 balance, equity, and margin telemetry.
  • Live Order Flow Imbalance (OFI) & Wavelet Energy Drift (MRDD) surveillance.
  • Interactive Daily Trade Performance breakdown with date search and quick filters.
  • 4 Curated Themes: Obsidian Sapphire πŸ’Ž, Stealth Carbon ⚑, Midnight Gold πŸ‘‘, Bloomberg Terminal 🌐.

πŸ”„ Continual ReCAP Adaptation (Zero Catastrophic Forgetting)

TriDomainMoE implements the Regime-Aware Continual Adaptive Portfolio (ReCAP) framework:

  • Baseline neural weights $\theta_0$ remain permanently frozen (requires_grad = False).
  • Adaptation isolates modular parameter policy delta vectors: $$d_k = \theta_k - \theta_0$$
  • At runtime, active network parameters are synthesized dynamically: $$\theta_{\text{active}} = \theta_0 + \sum_{k=1}^K w_k \cdot d_k$$
  • Guarantees 0.00% catastrophic forgetting of historical base market representations.

πŸ€— Hugging Face Model Hub

Pretrained model checkpoints, encoders, and discrete codebooks are published on the Hugging Face Hub at ElMoorish/tri-domain-moe:

Checkpoint Name Description Size Hub Path
btcusd_tri_domain_v2.pt Enhanced Live v2 Production Model 210 KB ElMoorish/tri-domain-moe/weights/btcusd_tri_domain_v2.pt
btcusd_advanced_v1.pt MBM + VQ-VAE + Microstructure v3 Model 1.5 MB ElMoorish/tri-domain-moe/weights/btcusd_advanced_v1.pt
mbm_encoder_v1.pt Masked Bar Modeling 4-Layer Transformer 3.3 MB ElMoorish/tri-domain-moe/weights/mbm_encoder_v1.pt
vq_tokenizer_v1.pt Discrete Market State Codebook (K=128) 1.1 MB ElMoorish/tri-domain-moe/weights/vq_tokenizer_v1.pt
recap_policies.pt Modular Continual ReCAP Policy Library 204 KB ElMoorish/tri-domain-moe/weights/recap_library/recap_policies.pt

To upload additional checkpoints directly to your Hugging Face account:

python scripts/upload_to_huggingface.py --repo-id ElMoorish/tri-domain-moe

🌐 Ecosystem & Live Portal

TriDomainMoE is part of the PrimeClub Quant algorithmic ecosystem. Visit the official web portal for real-time portfolio dashboards, research articles, and multi-agent execution telemetry:

πŸ”— Official Web Portal: https://primeclub-quant.vercel.app/


πŸ’– Support & Research Grants (Donations)

Developing, pretraining, and live-forward testing institutional algorithmic intelligence requires continuous 24/7 high-performance GPU compute (NVIDIA RTX 4060 / cloud H100 clusters), low-latency MT5 broker tick execution data feeds, and institutional news streaming infrastructure.

If TriDomainMoE or FinRL-X-MT5 provides value to your research or trading operations, supporting the project directly accelerates our live forward validation, multi-asset extensions (NAS100, XAUUSD, ETHUSD), and open-source model releases.

πŸͺ™ Cryptocurrency Research Donations

Detail Specification
Asset USDT (Tether USD)
Network TRON (TRC20)
Deposit Address TC8TFkemSFGEeBPF5ZQKbmjK97FVEGwrwc
TRC20 USDT Address:
TC8TFkemSFGEeBPF5ZQKbmjK97FVEGwrwc

Important

Please ensure you transfer USDT strictly over the TRON (TRC20) network. Transfers sent over other networks (ERC20, BSC, Solana, etc.) cannot be recovered. All grants go directly toward server compute, real tick data procurement, and live forward execution infrastructure.


πŸ§ͺ Automated Testing

Verify all 25 mathematical, structural, and execution unit tests:

pytest tests/ -v

βš–οΈ License & Disclaimer

Distributed under the Apache License 2.0. See LICENSE for details.

Caution

Quantitative Research Disclosure: This software is provided for scientific, academic, and algorithmic trading research purposes. Algorithmic trading in cryptocurrencies, indices, and derivatives carries substantial financial risk. Past statistical backtest performance is not an absolute guarantee of future live execution returns. Always practice strict capital preservation.

About

Self-improving financial Mixture of Experts (MoE) for BTCUSD on MT5. Features Correlation-Aware Softmax routing, Discrete VQ-VAE state tokenizers, and institutional prop-firm risk guards.

Topics

Resources

Contributing

Stars

1 star

Watchers

1 watching

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