AItify Aegis Quant
- Experts
- Version: 1.0
- Activations: 20
AItify Aegis Quant is an advanced quantitative trading system that utilizes a multi-model ensemble approach. Instead of relying on a single technical indicator or basic logic, it processes market data through thirty distinct mathematical algorithms. This allows the system to achieve a highly reliable consensus before making any trading decisions, offering a true institutional-grade architecture for your portfolio.
Advantages and Features
- Machine Learning Ensemble: The engine uses thirty unique analytical models, including Support Vector Machines, Random Forests, and Recurrent Neural Networks, to calculate directional probability.
- Dynamic Risk Management: The system actively adapts lot sizes based on the exact confidence score of the combined signals. High probability setups receive optimal scaling, while uncertain conditions are filtered out.
- Advanced Capital Protection: AItify Aegis Quant includes ten different money management models, including Value at Risk and the Kelly Criterion. This ensures portfolio exposure is strictly controlled at all times.
- Built-in Safety Failsafes: The system dynamically adjusts stop loss levels based on current market volatility and broker spread levels to ensure reliable and compliant execution.
- Portfolio Monitoring: When running on multiple charts, the internal risk manager monitors the total combined account exposure and intelligently halts new trades if maximum risk thresholds are reached.
Inputs and Parameters
Risk Management
- Fixed Lot Size: The static lot volume used if the money management mode is set to fixed.
- Risk % per Trade: The percentage of the account balance to risk on a single setup.
- Max Daily Loss %: The maximum allowed equity drawdown per day before trading is automatically halted.
- Stop Loss (Points): The baseline distance for the initial stop loss.
- Magic Number: A unique identifier for the trades managed by this expert advisor.
Money Management Mode
- Select sizing algorithm: Choose between ten allocation models including Fixed Lot, Risk Percentage, Dynamic Signal Scoring, Kelly Criterion, and Value at Risk.
AI Engine Settings
- Signal Strength Threshold: The minimum confidence consensus required (from 0.0 to 1.0) for the engine to execute a trade.
- Data Lookback Period: The number of historical bars the algorithms analyze for immediate feature processing.
- In-Sample Data %: The portion of historical data reserved for continuous internal calibration.
