Codes
Project Template Generator for MetaTrader 5
This script serves as a practical example of how developers can programmatically work with files using MQL5. One of its key objectives is to demonstrate effective project file organization, which is essential for developers working on large-scale systems or aiming to create portable, self-contained
Telegram integration made easy for MetaTrader 5
The goal is to make the function readily available for any Telegram integration task in MQL5 development. By adding this file to your CodeBase, you can simply include it in your Expert Advisors and call the function directly from the included module. This eliminates the need to redevelop the code
Articles
How to Test and Customize Built-in MQL5 Programs: Custom BullishBearish MeetingLines Stoch Expert Advisor for MetaTrader 5
We demonstrate a practical customization path for a built-in MetaTrader 5 EA using BullishBearish MeetingLines Stoch. The workflow covers baseline testing in the Strategy Tester, parameter optimization, and code-level changes. Two modifications are implemented: exposing Stochastic thresholds as
The MQL5 Standard Library Explorer (Part 14): Building a Dynamic Hedge EA with the ALGLIB Port (ap.mqh) for MetaTrader 5
This article introduces ap.mqh, the ALGLIB port for MQL5, and demonstrates its use in multi‑asset workflows that require robust linear algebra. It covers why built-in indicators fall short, then implements polynomial regression, a rolling correlation matrix indicator, and an adaptive hedge ratio
Overcoming Accessibility Problems in MQL5 Trading Tools (Part VI): Neural Command Integration for MetaTrader 5
This article demonstrates a working prototype integrating Brain-Computer Interface technology with MetaTrader 5, proving thought-based trading is feasible at the software level. A Python Flask server simulates neural command generation, communicating with an MQL5 Expert Advisor via JSON-over-HTTP
The MQL5 Standard Library Explorer (Part 13): Implementing the Math Solvers Library in Trading for MetaTrader 5
We present a complete workflow for adaptive filtering in MQL5 using the CNlEq Levenberg–Marquardt–like solver. The EA fits a VAMAC model—two EWMAs with an ATR‑based scaling—by supplying residuals and a Jacobian through CNlEq's reverse‑communication loop, with optional numerical or analytical
How to Detect and Normalize Chart Objects in MQL5 (Part 3): Alerting and Automated Trading from Manually Drawn Objects for MetaTrader 5
This article extends the chart‑object detector into a modular monitoring and execution layer. It defines objective interaction rules (touch, cross, breakout) for trendlines, Fibonacci levels, channels, rectangles, and pitchforks, then routes events through an interaction detector, alert manager, and
Overcoming Accessibility Problems in MQL5 Trading Tools (Part V): Gesture-Based Trading With Computer Vision for MetaTrader 5
This article shows how to build a hands-free trading workflow for MetaTrader 5 by translating webcam-tracked hand gestures into MQL5 trade commands. We cover the architecture (MediaPipe/OpenCV in Python plus an MQL5 EA), gesture-to-action mapping, and interprocess communication via Global Variables
How to Detect and Normalize Chart Objects in MQL5 (Part 2): Collecting and Structuring Data from Complex Analytical Objects for MetaTrader 5
Manually drawn analytical object tools like Fibonacci tools, and Andrews Pitchforks are invisible to automated trading logic. This article extends a base detector to extract anchor points, level arrays, and geometric offsets from complex objects. You will implement a reusable collector that
How to Detect and Normalize Chart Objects in MQL5 (Part 1): Building a Chart Object Detection Engine for MetaTrader 5
This article addresses the interpretative gap between visual chart objects and algorithmic execution. You will build a systematic detector that iterates over all chart objects, identifies analytical types, and normalises their geometric data (time and price coordinates) into a structured
Overcoming Accessibility Problems in MQL5 Trading Tools (Part IV): Remote voice trading for MetaTrader 5
Learn a practical way to execute MetaTrader 5 trades from Telegram voice notes using a Python middleware and an MQL5 EA acting as an HTTP client. The article covers architecture, WebRequest polling, in-memory queuing, JSON parsing with null-terminator stripping, and a constrained command grammar
The MQL5 Standard Library Explorer (Part 12): Multi-Timeframe Composite-Score Dashboard for MetaTrader 5
The article implements CMultiTimeframeMatrix, a reusable dashboard that maps symbols vs. timeframes and displays a numeric, colour‑coded score. The score combines trend, momentum, and volatility, updates by timer, and respects performance constraints. You will learn how to build the UI with
Forum
What could the trading world become if EAs and custom indicators were able to run on mobile platforms?
In my opinion, I believe this could result in higher trading activity and increased EA sales for developers due to the large number of mobile users. According to some research on Google: 95.8% use mobile phones to access the internet. By comparison, almost 62.9% use laptops or desktops (Source