Event Horizon Trader

Event Horizon Trader is a cutting-edge automated trading robot built on an innovative hybrid architecture. It combines quantum principles, artificial intelligence, and a multi-level risk management system for adaptive trading on financial markets. The expert advisor is designed to operate in volatile market conditions, dynamically adapting to trending, ranging (flat), and highly volatile periods. The advisor has a test configuration for the pair: XAUUSD.

Key System Components:

1. Quantum System

   • Quantum States: Models market uncertainty through multiple probabilistic states.

   • Decoherence (QuantumDecayRate): Controls the "decay" of states, adding a stochastic element to prevent overfitting.

   • Collapse Mechanism: Randomly selects a state before each trade, simulating quantum measurement.

2. Artificial Intelligence (AI Core)

   • Dynamic Signal Weighting: The AI re-evaluates the significance of each indicator based on their recent performance.

   • Reinforcement Learning: Adjusts module weights after each trade, reinforcing the influence of successful indicators.

   • Regularization (RegularizationLambda): Prevents overfitting through L2 weight regularization.

3. Attention Mechanism

   • Multi-Timeframe Analysis: Compares the clarity of signals on the primary and secondary timeframes.

   • Adaptive Weighting: Assigns greater weight to the timeframe with clearer signals (based on RSI, ADX, MA).

4. Modular Indicator System

   • RSI (Relative Strength Index): Identifies overbought/oversold conditions.

   • ADX (Average Directional Index): Assesses trend strength.

   • Moving Averages (MA): Determines trend direction through the difference between fast and slow MAs.

   • ATR (Average True Range): Used for calculating dynamic stop-losses and take-profits.

   • Chaos Filter: Filters out signals during low-volatility periods (based on the standard deviation of returns).

5. Advanced Risk Management

   • Adaptive Position Sizing: Calculates lot size based on:

     • Current risk (% of deposit).

     • Distance to stop-loss.

     • Volatility (via ATR).

   • Kelly Criterion (Optional): Optimizes position size based on the strategy's historical performance.

   • Drawdown Protection:

     • Daily Limit (MaxDailyDrawdownPercent): Blocks trading if the drawdown limit is exceeded.

     • Auto Reset on New Day (ResetLockOnNewDay).

   • Broker Compatibility Check:

     • Auto-adjusts stop-losses to meet broker requirements (MinStopDistance, UseBrokerStopLevels).

     • Checks margin before executing a trade.

How Signal Generation Works:

1. Data Update: Reads current indicator values on two timeframes.

2. Chaos Filter: Discards signals during low volatility (Chaos < ChaosThreshold).

3. Quantum Collapse: Randomly selects a state to introduce stochasticity.

4. Timeframe Weighting: Calculates "signal clarity" on each timeframe and determines attention weights.

5. Signal Aggregation: The final signal = weighted sum of contributions from each module (RSI, ADX, MA, Chaos, Quantum).

6. Decision Making: A signal is generated when the result exceeds the AdaptiveThreshold.

Risk Management Features:

• Dynamic Risk: Increases risk after a series of profitable trades and decreases it after losing trades.

• Volatility-Adjusted Risk: Accounts for current market volatility (via ATR).

• Kelly Criterion: Calculates the optimal capital fraction for a trade based on historical win probability.

• Stop-Loss Validation: Adjusts stop-losses and take-profits according to broker requirements and the current spread.

User Instructions:

1. Broker-Specific Setup:

   • MaxLotSize: Set the maximum allowed lot.

   • MinStopDistance: Specify the minimum stop distance in points (must be > broker requirements).

   • UseBrokerStopLevels: Enable to automatically account for the broker's stop order level rules.

2. Module Selection:

   • Enable/disable indicators (UseRSI, UseADX, etc.).

   • Configure indicator weights (RSIWeight, ADXWeight, etc.).

3. Risk Management:

   • BaseRisk: Starting risk as a % of deposit (0.1–1.0% recommended).

   • MaxRisk: Maximum risk (do not exceed 5%).

   • MaxDailyDrawdownPercent: Set a daily drawdown limit (e.g., 15%).

4. Optimization:

   • Conduct backtests on historical data (2–5 years).

   • Use the built-in  OnTester()  function for automatic selection of robust strategies.

   • Adjust indicator and AI parameters for the specific instrument.

Important Notes:

• Testing: Always test on a demo account before using real funds.

• Backups: The advisor automatically saves AI weights to a file. Regularly archive the  QuantumAI_SYMBOL.txt  files.

• Overfitting: Avoid excessive optimization to historical data. Rely on the OOS validation mechanism in  OnTester() .

Conclusion:

Event Horizon Trader is a comprehensive solution for automated trading, combining modern AI approaches and quantum metaphors with practical risk management. Its strength lies in its adaptability and capital preservation features.