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MQL5 Lot Size Calculation: Risk-Based EA Volume Formula and Code

MQL5 Lot Size Calculation: Risk-Based EA Volume Formula and Code

MQL5 SetIndexBuffer Guide: Fix Indicators Not Displaying on Charts

MQL5 SetIndexBuffer Guide: Fix Indicators Not Displaying on Charts

MQL5 State Machine EA: How to Build Stable Expert Advisor Logic

MQL5 State Machine EA: How to Build Stable Expert Advisor Logic

MQL5 iStochastic Guide: CopyBuffer, Parameters, EA Logic, and Troubleshooting

MQL5 iStochastic Guide: CopyBuffer, Parameters, EA Logic, and Troubleshooting

MQL5 MqlTradeRequest Guide: OrderSend, OrderCheck, and Trade Request Fields

MQL5 MqlTradeRequest Guide: OrderSend, OrderCheck, and Trade Request Fields

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sqlite-mql5 EA Design: Using SQLite for State Logs, Order Checks, and Backtesting

Key Takeaway The important point in a sqlite-mql5 design is to use SQLite for EA state management, validation logs, and trade history storage, not as a replacement for trading signals.In MQL5, the mos […]

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MQL5 Machine Learning Trading EA: Model Scores, Filters, and Backtesting

Conclusion of This Article The purpose of designing machine-learning-trading in MQL5 is to break trading decisions into verifiable features and scores, instead of relying on subjective conditional log […]

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MQL5 Python Backtesting Workflow: EA Design, Validation, and Forward Testing

Key Takeaway The purpose of using Python in an MQL5 backtesting workflow is to make analysis, aggregation, and signal comparison easier outside MetaTrader 5, especially when those details are hard to […]

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MQL5 Python Data Analysis EA Design: Safe Architecture for Trading Automation

Key Takeaway When you include Python-based data analysis in MQL5 EA design, the most important point is to separate the roles of MQL5 and Python.The MQL5 EA should handle price retrieval, pre-trade ch […]

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MT5 Python API Guide: Connection, Order Checks, and Automated Trading Basics

Key Takeaway The MT5 Python API is an integration method for connecting Python to the MetaTrader 5 terminal so you can retrieve price data, get symbol information, check positions, and send orders.Unl […]

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MQL5 Python Integration EA Design: Safe Architecture, Checks, and Testing

Key Takeaway When designing an integration between MQL5 and Python, it is important to separate the responsibilities of the MQL5 side and the Python side instead of putting every decision inside the E […]

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MQL5 EA Speed Optimization: Reduce OnTick Load and Improve Stability

Conclusion The purpose of speeding up an MQL5 EA is to reduce unnecessary work inside OnTick and keep order decisions, position management, and logging stable.When improving EA performance, first revi […]

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MQL5 Multi-Thread Optimization EA Design Guide for Stable Backtesting

Key Takeaway MQL5 multi-thread optimization is a design topic for distributing EA parameter testing across multiple tester agents.If speed is the only goal, results can become unstable because of diff […]

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MQL5 Indicator Performance Optimization: OnCalculate, prev_calculated, and CopyBuffer

Key Takeaway The basic way to improve MQL5 indicator performance is to update only the required range instead of recalculating every bar on every run.In a custom indicator, prev_calculated in OnCalcul […]

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MQL5 Memory Management for EAs: Handles, CopyBuffer, Arrays, and Live Trading Stability

Key Takeaway In MQL5 memory management, it is important to organize indicator handles, dynamic arrays, historical data, log output, and state variables clearly.EAs run on every tick, so repeatedly cre […]

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