This MetaTrader 5 expert advisor executes a counter-trend strategy utilizing Bollinger Bands and the Slow Stochastic oscillator. Developed as part of academic research into deep learning and technical analysis, the robot incorporates Heiken Ashi filtering to identify market extensions and doji candles. It manages risk
Trading robot · MT5
AI Quantum Learning Advanced Trailing Stop
The AI Quantum Learning Advanced Trailing Stop EA is an automated trading robot for MetaTrader 5 that employs neural network structures and quantum probability calculations.
GitHub stars2
Forks0
Last update1 year ago1 Jul 2025
LicenceNone stated
Overview
AI Quantum Learning Advanced Trailing Stop monitors market patterns by analyzing price changes, volume, volatility, and indicators like RSI. The EA manages risk using fixed stop loss and take profit levels alongside an advanced trailing stop with adjustable steps. It includes an adaptive lot sizing feature that modifies position sizes based on internal performance tracking and AI confidence. The repository is minimal, lacking documentation to explain the specific logic.
- Neural network with adaptive learning rate
- Quantum probability state calculations
- Pattern analysis of RSI and momentum
- Advanced trailing stop with step adjustment
- AI-driven adaptive lot sizing
Details
Author
GBNarasimha on GitHub
Type
Trading robot
Platform
MetaTrader 5 (MQL5)
Strategy
AI / machine learning, Mean reversion
Markets
Any symbol
Timeframes
Any timeframe
Risk profile
No grid, martingale or hedging logic was found in its code or README. That says nothing about how it performs: backtest it first.
Input parameters
Read from AI Quantum Learning Advanced Trailing Stop EA.mq5. Defaults are the author's; change them in the EA's Inputs tab.
| Name | Type | Default | Description |
|---|---|---|---|
MaxSpreadPoints | double | 20 | Maximum allowed spread in points |
BaseLotSize | double | 0.10 | Base position size (will be adjusted by AI) |
MaxPositions | int | 2 | Maximum number of positions per direction |
BuyInitialStopPoints | double | 1000 | Initial stop loss for buy positions in points |
BuyTakeProfitPoints | double | 500 | Take profit for buy positions in points |
BuyTrailingStopPoints | double | 150 | Trailing stop distance for buy positions in points |
BuyTrailingStepPoints | double | 10 | Step to move buy stop loss by |
SellInitialStopPoints | double | 500 | Initial stop loss for sell positions in points |
SellTakeProfitPoints | double | 1000 | Take profit for sell positions in points |
SellTrailingStopPoints | double | 150 | Trailing stop distance for sell positions in points |
SellTrailingStepPoints | double | 10 | Step to move sell stop loss by |
EnableAILearning | bool | true | Enable AI adaptive learning |
Show all 21 inputs
| Name | Type | Default | Description |
|---|---|---|---|
EnableQuantumLogic | bool | true | Enable quantum probability calculations |
AILearningRate | double | 0.01 | Neural network learning rate |
PatternAnalysisDepth | int | 50 | Number of patterns to analyze |
QuantumCoherence | double | 0.8 | Quantum state coherence factor |
SentimentWeight | double | 0.3 | Weight of market sentiment in decisions |
MagicNumber | int | 123456 | Magic number for trade identification |
EnableBuyTrading | bool | true | Enable buy position trading |
EnableSellTrading | bool | true | Enable sell position trading |
EnableAdaptiveLotSizing | bool | true | Enable AI-driven lot size adjustment |
How to install it
- 1Download the sourceUse "Download source (.zip)" above, or clone GBNarasimha/Faild-profits-EA from GitHub, and unzip it.
- 2Open the data folderIn MetaTrader choose File, then Open Data Folder, and go to MQL5/Experts.
- 3Copy the filesCopy the .mq5 file into Experts.
- 4Compile in MetaEditorOpen the file in MetaEditor and press Compile. Fix any missing includes the compiler reports.
- 5Test before you tradeRun it in the Strategy Tester, then attach it to a demo chart and allow algorithmic trading.
Third-party code. ForexR did not write, test or endorse this EA, and the summary above was generated automatically from its README and code. ForexR lists only repositories with readable source code and never hosts files. Read the code, backtest it and use a demo account first; automated trading can lose money quickly.
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