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How to Order a Trading Robot in MQL5 and MQL4
See a sample Requirements Specification to order a robot
New orders in the category:
30+ USD
30+ USD
200 - 300 USD
Specification
Strategy Overview
The trading robot will implement an AI-powered trend-following strategy that confirms trades on the 4-hour time frame and executes entries on the 15-minute time frame.
Key Components
1. Trend Confirmation (4-hour time frame):
- Use a machine learning algorithm to analyze market trends and confirm trade directions.
- Integrate with technical indicators (e.g., MA, RSI, Bollinger Bands) for trend validation.
2. Entry Signals (15-minute time frame):
- Use a combination of technical indicators and AI-driven analysis to generate entry signals.
- Enter long positions when the AI model predicts an upward trend.
- Enter short positions when the AI model predicts a downward trend.
3. Stop Loss (SL) and Take Profit (TP) based on ETR (Expected Trading Range):
- Calculate the ETR based on historical price movements and AI-driven analysis.
- Set SL and TP levels according to the ETR.
4. Grid Strategy:
- Implement a dynamic grid system that adjusts to market conditions.
- Use AI to optimize grid size, spacing, and order placement.
5. Martingale Strategy:
- Implement a dynamic martingale system that adjusts position sizes based on AI-driven risk assessment.
- Use AI to optimize martingale multiplier and risk management.
AI-Powered Dashboard
1. Design Inspiration: Reference the Forex Gold Investor EA dashboard design.
2. Features:
- Real-time market analysis and trend predictions.
- Trade signal generation and execution.
- Dynamic grid and martingale system management.
- Risk management and position sizing.
- Performance metrics and analytics.
Technical Requirements
1. MQL5 programming: Develop the trading robot using MQL5.
2. Machine Learning Integration: Integrate a machine learning library (e.g., TensorFlow, PyTorch) or use MQL5's built-in AI capabilities.
3. Dashboard Design: Create a user-friendly and interactive dashboard with real-time data visualization.
Deliverables
1. MQL5 code: Provide the complete MQL5 code for the trading robot.
2. AI model: Deliver the trained AI model and any necessary libraries or frameworks.
3. Dashboard: Provide a fully functional dashboard with real-time market analysis and trading capabilities.
4. Documentation: Document the strategy's logic, parameters, and risk management features.
Development Considerations
1. Back testing: Perform thorough back testing to ensure the strategy's effectiveness.
2. Risk Management: Implement robust risk management features to protect against market volatility.
3. Scalability: Ensure the dashboard and trading robot can handle high volumes of data and trades
Responded
1
Rating
Projects
22
23%
Arbitration
5
40%
/
60%
Overdue
2
9%
Working
2
Rating
Projects
35
23%
Arbitration
4
0%
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50%
Overdue
2
6%
Working
3
Rating
Projects
6
33%
Arbitration
7
0%
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71%
Overdue
0
Free
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