AlphaQuant Adaptive Learning EA v4.0 (NEW AI Regime Filter)
24 September 2026, 16:25
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AlphaQuant Adaptive Learning EA v4.0 (NEW AI Regime Filter)
Most Expert Advisors fail because they rely on a static strategy in a dynamic market. The AlphaQuant v4.0 introduces an institutional-grade AI Regime Classifier that actively monitors market conditions and adapts its execution logic in real-time to protect your capital.Built for serious retail and proprietary trading firm accounts, this EA abandons the "holy grail" myth and focuses on mathematical capital preservation, adaptive learning, and volatility management.
🧠 Core AI Features (v4.0):
- AI Regime Classifier: Uses a lightweight matrix-based perceptron to classify the market into Trending, Ranging, or Volatile regimes on every new bar.
- Dynamic Execution: Automatically adjusts Take Profit distances, Stop Loss buffers, and Lot Sizing based on the detected market regime.
- Adaptive Learning Engine: Continuously recalculates the weighting of Fast EMA, Slow EMA, and RSI signals based on the profitability of the last 50 closed trades.
🛡️ AEGIS Risk Management Protocol:
- Stage 0 Peak-Profit Lock: Cuts maximum risk in half at early profit targets before activating the full trailing stop.
- US News Filter: Integrates directly with the MQL5 Economic Calendar to block entries or move stops to breakeven before high-impact USD events (NFP, CPI, FOMC).
- Daily Win/Loss Limits: Hard-coded circuit breakers to stop trading after reaching daily profit targets or maximum drawdown limits.
- Broker-Aware Execution: Features exponential backoff retry logic, freeze-level protection, and dynamic spread filters to prevent slippage and requotes.
⚙️ Optimization & Setup:
- 100% self-contained. No external files, DLLs, or indicators required.
- Auto-detects broker GMT offset for precise news filtering.
- Designed for ECN/STP brokers (Recommended: XAUUSD, NAS100, or Major Forex Pairs on H1 timeframe).
Get it here: AlphaQuant Adaptive Learning EA v4.0
Disclaimer: Trading foreign exchange and CFDs on margin carries a high level of risk. Past performance in backtesting does not guarantee future results. Always test on a demo account before live deployment.
