DeepNero Institutional AI Core MT5
- Эксперты
-
Paranchai Tensit
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Contact info:
+Profile: https://www.mql5.com/en/users/paran1615 - Версия: 7.0
- Активации: 20
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DeepNero Institutional AI Core MT5 (Market Edition)
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DeepNero Institutional AI Core MT5 represents the apex of quantitative retail trading. Engineered explicitly for high-net-worth portfolio management, this expert advisor bypasses conventional retail indicators entirely. Operating on a strict 'Quant-Grade' framework, it mathematically dissects real-time tick volume, bid-ask micro-imbalances, and institutional order flow blocks. This guarantees that your capital is exposed to the market only during high-conviction, major liquidity sweeps.
Behind the Scenes: The DeepNero AI Laboratory
Institutional performance requires institutional maintenance. Our backend engineers run extreme Walk-Forward Matrix validations across decades of tick data, identifying shifting global Macroeconomic Regimes. These massive optimization profiles are completely processed on our proprietary servers. As the user, you simply run the refined .EX5 file. When the market permanently mutates, we autonomously recalibrate the core algorithms and deliver immediate performance patches to your device natively through MQL5.
Key Features:
- Quant-Grade Order Flow Tracking: Detects smart money accumulation and distribution before retail breakouts occur.
- Total Risk Isolation System: Implements dynamic statistical stop-losses designed to prevent catastrophic 'black swan' liquidations.
- Institutional Spread Protection: Actively monitors broker spread dilation in milliseconds, rejecting entries during toxic manipulative spread widening.
- Timeframe: H1
- Currency pairs: EURUSD, XAUUSD, BTCUSD & US30
- Initial deposit: $100 or $500 up
- It is recommended to use a low spread ECN Broker, 1:500 leverage
- Using every tick or real ticks data in backtest with 100% modeling quality
Parameters:
- Risk Management
- Order Magic Number, 808080
- Lot Management Mode, fixlot
- Flagship Lot Size, 0.05
- Percentage Risk, 1.0
- Institutional AI Core
- Signal Threshold, 0.60
- ONNX File Name, "train_brain_institutional"
- EnableEmbeddedInTester false; // [Backtest] Set true to use embedded AI model in Strategy Tester
- Prediction Horizon, AUTO
- Regime Confidence, 95%
-News Gating
- Enable Market Filter, true
- Buffer Before News, 45 Min
- Buffer After News, 90 Min
- Filter High-Impact, true
- Filter Medium-Impact, true
- Filter Low-Impact, true
- NLP Sentiment Core
- Enable Sentiment AI, true
- Data Update Rate, 30 Min
- Session Design
- Trading Start Hour, 0
- Trading End Hour, 24
- Dashboard HUD
- UI Scale Setting, X-Large
- Health Display, Enabled
