Enhance Forex EA with Adaptive Strategies for Optimal Trading Performance

You are an expert MQL5 programmer tasked with enhancing an existing Expert Advisor (EA) script for forex trading. Please perform the following detailed steps to create a high-performing, context-aware adaptive EA:
1. Attach the Base EA Script:
Incorporate the original EA code provided as the foundational codebase to maintain continuity and correctness.
2. Review Input Data:
Analyze the provided input snippet to understand current data inputs and parameters handled by the EA.
3. Extract and Structure Fine-Tuning Data:
Organize the EA’s components into a clear stepwise fine-tuning plan that will systematically improve strategy evolution.
4. Create a Parameter Table:
Identify key parameters for adjustment. Present these in a neatly formatted table as a checklist for system testing and validation.
5. Simulate Market Conditions:
Using historical market data from January 2025 to the present and emerging market trends, simulate the EA’s behavior under diverse market scenarios.
– Retain existing functions but tweak entry, stop-loss, and target logic for optimal performance.
– Begin with a thorough review of recent price action, key technical indicators (including RSI and MACD), and relevant news.
6. Develop Fine-Tuning Stages:
Define distinct strategy stages (e.g., breakout vs mean-reversion) aligned with observed market regimes.
– Simulate and evaluate these strategies to determine the best approach.
7. Generate an Updated EA Script:
Create an enhanced EA script that mirrors the original structure but is explicitly divided into clear, tagged stages according to the fine-tuning plan.
8. Add Stage Toggle:
Integrate a user-friendly toggle mechanism (such as a dropdown menu) into EA inputs, allowing backtesters to switch between different strategy stages with ease.
9. Integrate with Existing EA Codebase:
Merge new modules seamlessly into the original EA, including updated signal logic, a dynamic risk engine, and robust trade execution routines.
– Ensure the EA senses market conditions dynamically and adjusts stage-specific parameters appropriately.
10. Extend Auto-Sensing with Sentiment Filter:
Enhance the EA’s auto-sensing module by integrating a sentiment-based filter to improve adaptability.
– Implement a 2-minute cooldown period between trades for recalibration.
– Prevent new orders if a position is already open and enforce waiting 2 minutes before executing a new trade after closing an existing one.
11. Incorporate Intuitive Trading Logic:
Beyond standard logical rules, enable the EA to “trade with intuition” by incorporating adaptive, non-traditional decision-making processes based on real-time market context.
12. Consolidate into One Complete EA Script:
Combine all updates and modules into a single comprehensive EA script.
– Provide this final script in plain text, split into clear parts if large, directly here.
13. Deliver Final Updated EA Script in TXT:
Supply the full, deployable EA code in plain text format, suitable for direct copy, paste, and deployment into MetaTrader 5.
14. Maintain Code Efficiency:
As an MQL5 expert, ensure the code is compact, readable, and optimized.
– Embed context-aware signal logic using RSI and MACD indicators to:
– Detect bullish or bearish momentum.
– Dynamically adapt score calculations based on trend or reversal regimes.
– Enter trades only when signal, momentum, and volatility indicators align with the intended strategy.
Throughout your development, systematically reason about each enhancement step and justify your design choices, ensuring your final solution is robust, adaptive, and aligned with modern quantitative trading standards.
# Output Format
– A structured report briefly summarizing each step taken.
– A neatly formatted table listing all parameters identified for fine-tuning with descriptions.
– The final updated EA script in plain text, clearly divided into tagged stages and including the new toggle input.
– Code comments explaining logic at key points, especially the context-aware signal logic.
# Notes
– Use placeholders only if the original base EA script or input snippets are not provided.
– Preserve the original code’s core logic while enhancing adaptivity.
– Ensure syntax correctness and MQL5 best practices.
You have access to the original EA codes and the input data snippet. Use historical data from January 2025 onward and current market conditions for simulation analysis. Respond in clear, professional technical language suited for an experienced MQL5 developer.