Overview
This prompt aims to guide developers in creating a profitable trading bot for Gold using MQL5. Programmers and traders will benefit from structured strategies and insights into effective trading techniques.
Prompt Overview
Purpose: This trading bot aims to capitalize on short-term price movements in Gold (XAUUSD) using aggressive strategies.
Audience: Designed for traders seeking automated solutions to enhance their trading performance in volatile markets.
Distinctive Feature: It incorporates advanced technical indicators and dynamic risk management techniques for optimized trading decisions.
Outcome: The bot aims to achieve a high win rate and profitability through precise entry and exit signals.
Quick Specs
- Media: Text
- Use case: Compliance Review, Content Creation, Editing & Refinement
- Techniques: Few-Shot Prompting, Prompt Templates, Retrieval-Augmented Generation
- Models: ChatGPT, Claude, Gemini AI
- Estimated time: 10-20 minutes
- Skill level: Intermediate
Variables to Fill
- [X] – X
- [Y] – Y
- [$Z] – $z
- [timeframe] – Timeframe
Example Variables Block
- [X]: 150 trades
- [Y]: 75%
- [$Z]: $5000
- [timeframe]: 6 months
The Prompt
Design an aggressive trading bot in MQL5 for trading Gold (XAUUSD) that achieves a high win rate by capitalizing on short-term price movements using scalping and breakout strategies.
**Focus on:**
– Incorporating technical indicators such as:
– Moving Averages
– RSI
– MACD
– Generating precise entry and exit signals.
– Implementing advanced risk management techniques to minimize losses and maximize profits.
– Adapting dynamically to changing market volatility through position sizing and trade adjustments.
**Follow these steps:**
1. Conduct market analysis to identify key support and resistance levels for XAUUSD.
2. Define explicit entry and exit rules based on indicator signals.
3. Determine optimal position sizing, factoring in account equity and risk tolerance.
4. Backtest the bot extensively using historical data and refine it to improve the win rate.
5. Set up real-time monitoring and alerts to track trade performance and adjust strategies as required.
**Output Requirements:**
– Provide the complete MQL5 bot code with detailed comments explaining each function and logic block.
– Include a comprehensive summary of the trading strategy, highlighting backtesting performance metrics such as:
– Number of trades
– Win rate
– Overall profitability
**Ensure compliance with:**
– MetaTrader platform guidelines.
– Account for slippage and spread effects during aggressive trading in the profitability calculations.
**Code Structure:**
– The code should be modular to allow easy future adjustments for diverse market conditions.
**Output Format:**
– Full MQL5 source code with thorough inline comments.
– Trading strategy summary report including backtest results and key performance statistics.
**Examples:**
“`mql5
int OnInit() {
// Initialize indicators and variables
}
void OnTick() {
// Implement trade logic based on indicators
}
double CalculateRisk() {
// Return optimal lot size based on risk management
}
“`
**Summary:**
“The bot executed [X] trades achieving a win rate of [Y]% and a profit of [$Z] over [timeframe] of backtesting.”
Screenshot Examples
How to Use This Prompt
- [TECH_INDICATORS]: Moving Averages, RSI, MACD usage.
- [ENTRY_EXIT_RULES]: Defined rules for trade execution.
- [POSITION_SIZING]: Optimal lot size based on risk.
- [BACKTESTING]: Extensive testing with historical data.
- [TRADE_MONITORING]: Real-time performance tracking alerts.
- [RISK_MANAGEMENT]: Techniques to minimize losses.
- [MARKET_ANALYSIS]: Identifying support and resistance levels.
- [PROFITABILITY_METRICS]: Win rate and profit statistics.
Tips for Best Results
- Market Analysis: Identify key support and resistance levels for XAUUSD to inform trading decisions.
- Entry/Exit Rules: Define clear rules based on Moving Averages, RSI, and MACD signals for precise trade execution.
- Risk Management: Implement advanced techniques to calculate position sizes based on account equity and risk tolerance.
- Backtesting: Conduct extensive backtests to refine the bot, focusing on metrics like win rate and overall profitability.
FAQ
- What indicators should be used for the trading bot?
Use Moving Averages, RSI, and MACD to generate entry and exit signals. - How can the bot minimize losses effectively?
Implement advanced risk management techniques, including optimal position sizing based on account equity. - What is essential for adapting to market volatility?
Dynamically adjust position sizing and trade strategies based on real-time market conditions. - What performance metrics should be included in the summary report?
Include number of trades, win rate, and overall profitability from backtesting results.
Compliance and Best Practices
- Best Practice: Review AI output for accuracy and relevance before use.
- Privacy: Avoid sharing personal, financial, or confidential data in prompts.
- Platform Policy: Your use of AI tools must comply with their terms and your local laws.
Revision History
- Version 1.0 (February 2026): Initial release.
