MQL5 Programming Articles

Enhancing the MQL5 GUI panel with dynamic features can significantly improve the trading experience for users. By incorporating interactive elements, hover effects, and real-time data updates, the panel becomes a powerful tool for modern traders.

This series of articles introduces several time series labeling methods, which can create data that meets most artificial intelligence models, and targeted data labeling according to needs can make the trained artificial intelligence model more in line with the expected design, improve the accuracy of our model, and even help the model make a qualitative leap!

Determining market direction can be straightforward, but knowing when to enter can be challenging. As part of the series titled "Price Action Analysis Toolkit Development", I am excited to introduce another tool that provides entry points, take profit levels, and stop loss placements. To achieve this, we have utilized the MQL5 programming language. Let’s delve into each step in this article.

There are methods that can be used to solve many problems that can be repeated. Once understand how to use these methods it can be very helpful to create your software effectively and apply the concept of DRY ((Do not Repeat Yourself). In this context, the topic of Design Patterns will serve very well because they are patterns that provide solutions to well-described and repeated problems.

Monitoring manually drawn trendlines requires constant chart observation, which can cause important price interactions to be missed. This article develops a trendline monitoring Expert Advisor that synchronizes manually drawn trendlines with automated monitoring logic in MQL5, generating alerts when price approaches, touches, or breaks a monitored line.

The ADX is another relatively popular technical indicator used by some traders to gauge the strength of a prevalent trend. Acting as a combination of two other indicators, it presents as an oscillator whose patterns we explore in this article with the help of MQL5 wizard assembly and its support classes.

We continue to study unsupervised learning algorithms. This time I suggest that we discuss the features of autoencoders when applied to recurrent model training.

We introduce the Multi-Agent Self-Adaptive Portfolio Optimization Framework (MASAAT), which combines attention mechanisms and time series analysis. MASAAT generates a set of agents that analyze price series and directional changes, enabling the identification of significant fluctuations in asset prices at different levels of detail.

Whenever we consider reinforcement learning methods, we are faced with the issue of efficiently exploring the environment. Solving this issue often leads to complication of the algorithm and training of additional models. In this article, we will look at an alternative approach to solving this problem.

The flow of the market is determined by the forces between bulls and bears. There are specific levels that the market respects due to the forces acting on them. Fibonacci and VWAP levels are especially powerful in influencing market behavior. Join me in this article as we explore a strategy based on VWAP and Fibonacci levels for signal generation.

In this article, we enhance the MQL5 Economic Calendar with a dynamic scrollbar for intuitive news navigation. We ensure seamless event display and efficient updates. We validate the responsive scrollbar and polished dashboard through testing.

The article presents a new metaheuristic optimization Circle Search Algorithm (CSA) based on the geometric properties of a circle. The algorithm uses the principle of moving points along tangents to find the optimal solution, combining the phases of global exploration and local exploitation.

The Fibonacci retracement tool is an essential component of price action analysis, providing critical levels for potential market reactions. However, its effectiveness is often limited by the need for continuous human monitoring, which can lead to missed setups. In this part of our series, we introduce a tool that synchronizes and actively monitors manually drawn Fibonacci levels using MQL5, combining discretionary insight with automated oversight.

Trading strategies may be challenging to improve because we often don’t fully understand what the strategy is doing wrong. In this discussion, we introduce linear system identification, a branch of control theory. Linear feedback systems can learn from data to identify a system’s errors and guide its behavior toward intended outcomes. While these methods may not provide fully interpretable explanations, they are far more valuable than having no control system at all. Let’s explore linear system identification and observe how it may help us as algorithmic traders to maintain control over our trading applications.

The Attraos framework integrates chaos theory into long-term time series forecasting, treating them as projections of multidimensional chaotic dynamic systems. Exploiting attractor invariance, the model uses phase space reconstruction and dynamic multi-resolution memory to preserve historical structures.

In this article, we develop a gauge-style RSI indicator in MQL5 that visualizes Relative Strength Index values on a circular scale with a dynamic needle, color-coded ranges for overbought and oversold levels, and customizable legends. We utilize the Canvas class to draw elements like arcs, ticks, and pies, ensuring smooth updates on new RSI data.

Learn how to import and use EX5 libraries in your MQL5 code or projects. In this continuation article, we will expand the EX5 library by adding more position management functions to the existing library and creating two Expert Advisors. The first example will use the Variable Index Dynamic Average Technical Indicator to develop a trailing stop trading strategy expert advisor, while the second example will utilize a trade panel to monitor, open, close, and modify positions. These two examples will demonstrate how to use and implement the upgraded EX5 position management library.

Todays trader is a philomath who is almost always looking up new ideas, trying them out, choosing to modify them or discard them; an exploratory process that should cost a fair amount of diligence. These series of articles will proposition that the MQL5 wizard should be a mainstay for traders in this effort.

In this article we will complete the development of a simulator for our system. The main goal here will be to configure the algorithm discussed in the previous article. This algorithm aims to create a RANDOM WALK movement. Therefore, to understand today's material, it is necessary to understand the content of previous articles. If you have not followed the development of the simulator, I advise you to read this sequence from the very beginning. Otherwise, you may get confused about what will be explained here.

The article continues the review of the PrintFormat() function. We will briefly look at formatting strings using StringFormat() and their further use in the program. We will also write templates to display symbol data in the terminal journal. The article will be useful for both beginners and experienced developers.

In this article, we will make the system more reliable to ensure a robust and secure use. One of the ways to achieve the desired robustness is to try to re-use the code as much as possible so that it is constantly tested in different cases. But this is only one of the ways. Another one is to use OOP.

In this article, we will focus on visually styling the graphical user interface (GUI) of our Trading Administrator Panel using MQL5. We’ll explore various techniques and features available in MQL5 that allow for customization and optimization of the interface, ensuring it meets the needs of traders while maintaining an attractive aesthetic.

The models we create are becoming larger and more complex. This increases the costs of not only their training as well as operation. However, the time required to make a decision is often critical. In this regard, let us consider methods for optimizing model performance without loss of quality.

The Enhanced Trend Confirmation Technique combines price action, volume analysis, and machine learning to identify genuine market movements. It requires both price breakouts and volume surges (50% above average) for trade validation, while using an LSTM neural network for additional confirmation. The system employs ATR-based position sizing and dynamic risk management, making it adaptable to various market conditions while filtering out false signals.

This article explores how economic news releases, investor behavior, and various factors can influence market trend reversals. It includes a video explanation and proceeds by incorporating MQL5 code into our program to detect trend reversals, alert us, and take appropriate actions based on market conditions. This builds upon previous articles in the series.

In this series of articles, we discuss how we can build Expert Advisors capable of autonomously adjusting themselves to dynamic market conditions. In today's article, we will attempt to tune a deep neural network to Deriv's synthetic markets.

Today, we take another step forward by integrating an external news API as the source of headlines for our News Headline EA. In this phase, we’ll explore various news sources—both established and emerging—and learn how to access their APIs effectively. We'll also cover methods for parsing the retrieved data into a format optimized for display within our Expert Advisor. Join the discussion as we explore the benefits of accessing news headlines and the economic calendar directly on the chart, all within a compact, non-intrusive interface.

The article presents a detailed description of the shuffled frog-leaping (SFL) algorithm and its capabilities in solving optimization problems. The SFL algorithm is inspired by the behavior of frogs in their natural environment and offers a new approach to function optimization. The SFL algorithm is an efficient and flexible tool capable of processing a variety of data types and achieving optimal solutions.

Learn how to build a complete Kagi-based trading Expert Advisor in MQL5, from signal construction to order execution, visual markers, and a three-stage trailing stop. Includes full code, testing results, and a downloadable set file.

Points of support and resistance are critical levels that signal potential trend reversals and continuations. Although identifying these levels can be challenging, once you pinpoint them, you’re well-prepared to navigate the market. For further assistance, check out the Quarters Drawer tool featured in this article, it will help you identify both primary and minor support and resistance levels.