Articles on manual and algorithmic trading in MetaTrader 5
This category features articles on all aspects of trading - from manual to fully automatic trading, from Expert Advisor ideas to trading robot creation using the MQL5 Wizard. Position management, processing of trade events and money management - these integral parts of trading are covered in theses articles.
Learn how to copy trading signals and how to provide around-the-clock operation of Expert Advisors, how to create a trading robot and how to run MetaTrader on Linux and MacOS, what social trading is and how to order a trading robot.
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Position Management: Safe Pyramiding with a Unified Stop in MQL5
This article presents CPyramidEngine, a reusable MQL5 class that adds disciplined pyramiding to any Expert Advisor with about six lines of integration. The engine enforces three constraints: strictly decreasing lot sizes, a single unified stop that advances after each add-on, and broker-level validation of every modification. It explains common failure modes in naive implementations and shows how to keep total account risk quantifiable and controlled as positions are added.
The Power of MetaTrader 5: From Step-by-Step Debugging to EX5 Protection in a Unified Environment
This article examines a comprehensive approach to developing trading algorithms: from project setup and logic debugging to protecting the finished product. We will explore MetaEditor's built-in tools, including step-by-step debugging using real ticks, performance profiling, and direct integration with C++ DLLs to speed up calculations. The article also explains how to protect intellectual property using MQL5 Cloud Protector. The application of the described techniques will transform Expert Advisor development from a chaotic search for solutions into a systematic process, significantly reducing the time required to develop a strategy.
Eagle Strategy (ES)
Eagle Strategy is an algorithm that mimics the eagle's two-phase hunting strategy: global search via Levy flights using Mantegna method, alternating with intense local exploitation using the firefly algorithm, a mathematically sound approach to balancing exploration and exploitation, and a bioinspired concept that combines two natural phenomena into a single computational method.