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Zaniva Trade

MQL5 Experten Skripte Forex Debugging eines Roboters/Indikators Python Stocks Futures

Spezifikation

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

Bewerbungen

1
Entwickler 1
Bewertung
(19)
Projekte
22
23%
Schlichtung
5
40% / 60%
Frist nicht eingehalten
2
9%
Arbeitet
2
Entwickler 2
Bewertung
(16)
Projekte
35
23%
Schlichtung
4
0% / 50%
Frist nicht eingehalten
2
6%
Arbeitet
3
Entwickler 3
Bewertung
(7)
Projekte
6
33%
Schlichtung
7
0% / 71%
Frist nicht eingehalten
0
Frei
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