Articles with MQL5 programming examples

This article explores the development of an ensemble algorithmic trading strategy for the EURUSD market that combines the Bollinger Bands and the Relative Strength Indicator (RSI). Initial rule-based strategies produced high-quality signals but suffered from low trade frequency and limited profitability. Multiple iterations of the strategy were evaluated, revealing flaws in our understanding of the market, increased noise, and degraded performance. By appropriately employing statistical learning algorithms, shifting the modeling target to technical indicators, applying proper scaling, and combining machine learning forecasts with classical trading rules, the final strategy achieved significantly improved profitability and trade frequency while maintaining acceptable signal quality.

Today we will update the functionality of the indicator system for the first time. In the previous article within the "Multiple indicators on one chart" we considered the basic code which allows using more than one indicator in a chart subwindow. But what was presented was just the starting base of a much larger system.

DRAKON is a visual programming language designed to simplify interaction between specialists from different fields (biologists, physicists, engineers...) with programmers in Russian space projects (for example, in the Buran reusable spacecraft project). In this article, I will talk about how DRAKON makes the creation of algorithms accessible and intuitive, even if you have never encountered code, and also how it is easier for customers to explain their thoughts when ordering trading robots, and for programmers to make fewer mistakes in complex functions.

News trading can be complicated and overwhelming, in this article we will go through steps to obtain news data. Additionally we will learn about the MQL5 Economic Calendar and what it has to offer.

Today we are going to use Chart Trade again, but this time it will be an on-chart indicator which may or may not be present on the chart.

In this article, we will introduce Sentiment Analysis and ONNX Models with Python to be used in an EA. One script runs a trained ONNX model from TensorFlow for deep learning predictions, while another fetches news headlines and quantifies sentiment using AI.

MQL5 offers endless opportunities to develop automated trading systems tailored to your preferences. Did you know it can even perform complex mathematical calculations? In this article, we introduce the Japanese Heikin-Ashi technique as an automated trading strategy.

Join us in our discussion today as we look for an algorithmic procedure to minimize the total number of times we get stopped out of winning trades. The problem we faced is significantly challenging, and most solutions given in community discussions lack set and fixed rules. Our algorithmic approach to solving the problem increased the profitability of our trades and reduced our average loss per trade. However, there are further advancements to be made to completely filter out all trades that will be stopped out, our solution is a good first step for anyone to try.

The article discusses the possibilities of handling databases based on the SQLite engine. The CDatabase class has been formed for convenience and efficient use of OOP principles. It is subsequently involved in the creation and management of the database of macroeconomic events. The article provides the examples of using multiple methods of the CDatabase class.

There is still one task which our order system is not up to, but we will FINALLY figure it out. The MetaTrader 5 provides a system of tickets which allows creating and correcting order values. The idea is to have an Expert Advisor that would make the same ticket system faster and more efficient.

The alignment of higher-timeframe liquidity structures with lower-timeframe reversal patterns can greatly influence both the likelihood and direction of the next price movement. By integrating structural liquidity zones from higher timeframes with precise reversal confirmations on lower timeframes, traders can improve entry timing and overall trade quality. This article demonstrates how to reinforce liquidity-based trading strategies through higher-timeframe structural confirmation—and how to implement this approach effectively using MQL5.

In this article, we will take a look to one the famous strategies of Bill Williams, and discuss it, and try to improve the strategy with other indicators and with predictions.

This article walks the reader through a reimagined version of the classical Bollinger Band breakout strategy. It identifies key weaknesses in the original approach, such as its well-known susceptibility to false breakouts. The article aims to introduce a possible solution: the Double Bollinger Band trading strategy. This relatively lesser known approach supplements the weaknesses of the classical version and offers a more dynamic perspective on financial markets. It helps us overcome the old limitations defined by the original rules, providing traders with a stronger and more adaptive framework.

Built on lower-timeframe market structure, and then orchestrated on the higher-timeframe, this indicator detects swing extremes where price becomes statistically vulnerable to reversal. It visualizes overextension and pullback zones, offering early insight into mean-reversion behavior.

In this article, we will review the structure of the indicator buffer in multi-symbol, multi-period indicators and organize the display of colored buffers of these indicators on the chart.

Cycles are of great importance in our lives. Day and night, seasons, days of the week and many other cycles of different nature are present in the life of any person. In this article, we will consider cycles in financial markets.

We present a slanted trendline breakout tool that relies on three‑swing validation to generate objective, price‑action signals. The system automates swing detection, trendline construction, and breakout confirmation using crossing logic to reduce noise and standardize execution. The article explains the strategy rules, shows the MQL5 implementation, and reviews testing results; the tool is intended for analysis and signal confirmation, not automated trading.

This indicator acts as a discipline enforcer by tracking account equity, profit/loss, and drawdown in real-time while displaying a performance dashboard. It can help traders stay consistent, avoid overtrading, and comply with prop-firm challenge rules.

Geometric patterns offer traders a concise way to interpret price action. Many analysts draw trend lines, rectangles, and other shapes by hand, and then base trading decisions on the formations they see. In this article, we explore an automated alternative: harnessing MQL5 to detect and analyze the most popular geometric patterns. We’ll break down the methodology, discuss implementation details, and highlight how automated pattern recognition can sharpen a trader's market insights.

In this article we will discuss in detail how to write a risk manager class for manual trading from scratch. This class can also be used as a base class for inheritance by algorithmic traders who use automated programs.

GSA is a population optimization algorithm inspired by inanimate nature. Thanks to Newton's law of gravity implemented in the algorithm, the high reliability of modeling the interaction of physical bodies allows us to observe the enchanting dance of planetary systems and galactic clusters. In this article, I will consider one of the most interesting and original optimization algorithms. The simulator of the space objects movement is provided as well.

Learn how to develop and implement a comprehensive pending orders EX5 library in your MQL5 code or projects. This article will show you how to create an extensive pending orders management EX5 library and guide you through importing and implementing it by building a trading panel or graphical user interface (GUI). The expert advisor orders panel will allow users to open, monitor, and delete pending orders associated with a specified magic number directly from the graphical interface on the chart window.