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Freelance Coder Requirements for Developing the AI-Enhanced Expert Advisor
Below is a detailed outline of the requirements for hiring a freelance coder to build the described Expert Advisor (EA) for MetaTrader 5, along with the necessary skills, timeframe, indicators, and responsibilities.
Project Overview
Create a sophisticated, AI-enhanced Expert Advisor (EA) for MetaTrader 5 (MT5) that implements a trend-following strategy with dynamic scaling, advanced exit conditions, and real-time decision-making powered by AI (ChatGPT). The EA should scan multiple instruments, incorporate multiple indicators, and allow for user-defined parameters.
Required Skills
The freelancer must possess the following skills:
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MQL5 Development:
- Proficiency in writing Expert Advisors, indicators, and scripts for MetaTrader 5.
- Understanding of trade execution functions, order management, and risk management in MQL5.
- Experience with integrating technical indicators such as Moving Averages, Stochastic Oscillators, Bollinger Bands, and Heiken Ashi candles.
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API Integration:
- Familiarity with integrating external APIs using Python or similar tools.
- Experience in connecting MQL5 with external services via JSON or other formats.
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Python Development:
- Ability to write a robust Python script to act as an intermediary between MT5 and the ChatGPT API.
- Knowledge of OpenAI API usage and security best practices.
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AI Decision-Making:
- Understanding of AI-based decision-making in trading contexts.
- Ability to design workflows where AI evaluates and improves trading strategies.
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Multi-Instrument Scanning:
- Experience in building EAs that can scan and trade multiple markets simultaneously.
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Testing and Optimization:
- Knowledge of MT5 strategy testing and optimization techniques.
- Familiarity with backtesting, walk-forward analysis, and parameter optimization.
Project Deliverables
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Core Expert Advisor in MQL5:
- Implements the predefined strategy:
- Trend detection using Heiken Ashi and Hull Moving Average.
- Scaling-in conditions based on 4-day and 7-day MAs, stochastic signals, and Bollinger Bands.
- Exit rules based on ATR trailing stop, Bollinger Band touches, and Heiken Ashi reversal.
- 10–15-day maximum holding periods with cooldown after exits.
- Implements the predefined strategy:
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AI Integration:
- Connects the EA to ChatGPT for:
- Real-time decision-making when strategy conditions are ambiguous.
- Dynamic improvements to the strategy based on AI feedback.
- Connects the EA to ChatGPT for:
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Python Intermediary Script:
- Bridges MQL5 with the OpenAI API.
- Manages data exchange and ensures low-latency communication.
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Customizable Parameters:
- User-definable settings for:
- Timeframes to monitor (15-min, 30-min, 1-hour, 4-hour charts).
- Number of new positions per day.
- Lot sizes, stochastic levels, Bollinger Band settings, and cooldown periods.
- User-definable settings for:
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Multi-Instrument Functionality:
- Scans and trades multiple instruments based on the strategy.
- Includes user-selectable instruments.
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Testing and Documentation:
- Thoroughly backtest the EA and provide performance reports.
- Deliver detailed documentation for installation, configuration, and use.
Indicators to Be Used
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Heiken Ashi Candles:
- To detect trend changes (3 consecutive candles confirm the trend).(variable by user input)
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Hull Moving Average (20-day): (variable by user input)
- Used to confirm trend changes with color shifts.
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4-Day and 7-Day Simple Moving Averages (SMA):
- Defines the price range for valid scaling entries.
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Stochastic Oscillator:
- Signals scaling opportunities based on exits from the 80 or 20 levels.
- Monitored on 15-minute, 30-minute, 1-hour, and 4-hour charts.
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Bollinger Bands (20-period, 2 standard deviations)(varialble by user input):
- Used for exits between days 12–14.
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Average True Range (ATR):
- Trailing stop calculated as ATR x 3.(variable - user input)
Timeframe
- Project Duration: 4–6 weeks
- Week 1–2: Develop and test the core EA in MQL5 with predefined strategy logic.
- Week 3: Implement the Python intermediary script and integrate the ChatGPT API.
- Week 4–5: Test the AI-enhanced functionality, refine decision-making, and backtest across multiple instruments.
- Week 6: Final testing, debugging, optimization, and documentation.
Additional Requirements
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Communication:
- Regular updates on progress (e.g., weekly reports or demo builds).
- Ability to discuss and refine the strategy based on user feedback.
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Budget:
- Provide an estimated cost range, broken down by task (EA development, AI integration, testing).
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Post-Delivery Support:
- Offer a support period for bug fixes and minor adjustments after delivery.
How to Apply
Candidates should:
- Submit a portfolio of similar projects (e.g., advanced EAs, API-integrated systems).
- Demonstrate knowledge of trading strategies and AI in financial markets.
- Provide an estimated cost and timeline for the project.
- Send email to hello@seoninjas.co.za
The strategy details will be given to the successful candidate.