Articles on manual and algorithmic trading in MetaTrader 5

For many traders, the gap between knowing a risk rule and following it consistently is where accounts go to die. Emotional overrides, revenge trading, and simple oversight can dismantle even the best strategy. Today, we will transform the MetaTrader 5 platform into an unwavering enforcer of your trading rules by developing a Risk Enforcement Expert Advisor. Join this discussion to find out more.

We will continue to build a system for working in the FOREX market. In order to solve this problem, we must first declare the loading of ticks before loading the previous bars. This solves the problem, but at the same time forces the user to follow some structure in the configuration file, which, personally, does not make much sense to me. The reason is that by designing a program that is responsible for analyzing and executing what is in the configuration file, we can allow the user to declare the elements he needs in any order.

The article explores the possibility of improving price forecasting based on trading volume analysis by integrating technical analysis principles with LSTM neural network architecture. Particular attention is paid to the detection and interpretation of anomalous volumes, the use of clustering and the creation of features based on volumes and their definition in the context of machine learning.

The article presents an implementation of the Levenberg-Marquardt algorithm for training feedforward neural networks. A comparative analysis of performance with algorithms from the scikit-learn Python library has been conducted. Simpler learning methods, such as gradient descent, gradient descent with momentum, and stochastic gradient descent are preliminarily discussed.

With the rapid development of artificial intelligence today, language models (LLMs) are an important part of artificial intelligence, so we should think about how to integrate powerful LLMs into our algorithmic trading. For most people, it is difficult to fine-tune these powerful models according to their needs, deploy them locally, and then apply them to algorithmic trading. This series of articles will take a step-by-step approach to achieve this goal.

Welcome to the third installment of our trend series! Today, we’ll delve into the use of divergence as a strategy for identifying optimal entry points within the prevailing daily trend. We’ll also introduce a custom profit-locking mechanism, similar to a trailing stop-loss, but with unique enhancements. In addition, we’ll upgrade the Trend Constraint Expert to a more advanced version, incorporating a new trade execution condition to complement the existing ones. As we move forward, we’ll continue to explore the practical application of MQL5 in algorithmic development, providing you with more in-depth insights and actionable techniques.

In this article, we build an automated trading program in MQL5 that detects the Quasimodo reversal pattern from a zig-zag of confirmed swing pivots. We work through swing detection, pattern arming, retrace entries at the QM line, and structural stop placement with risk-based sizing. We also add trade management with breakeven, trailing, and partial closing to handle open positions.

The article considers the Artificial Algae Algorithm (AAA) based on biological processes characteristic of microalgae. The algorithm includes spiral motion, evolutionary process and adaptation, which allows it to solve optimization problems. The article provides an in-depth analysis of the working principles of AAA and its potential in mathematical modeling, highlighting the connection between nature and algorithmic solutions.

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 considers simple options strategies and their implementation in MQL5. We will develop a basic EA that will be modernized and become more complex.

The article considers a new population optimization algorithm - Cyclic Parthenogenesis Algorithm (CPA), inspired by the unique reproductive strategy of aphids. The algorithm combines two reproduction mechanisms — parthenogenesis and sexual reproduction — and also utilizes the colonial structure of the population with the possibility of migration between colonies. The key features of the algorithm are adaptive switching between different reproductive strategies and a system of information exchange between colonies through the flight mechanism.

Embark on an illuminating journey with Part Two of our MQL5 series. These articles are not just tutorials, they're doorways to an enchanted realm where programming novices and wizards alike unite. What makes this journey truly magical? Part Two of our MQL5 series stands out with its refreshing simplicity, making complex concepts accessible to all. Engage with us interactively as we answer your questions, ensuring an enriching and personalized learning experience. Let's build a community where understanding MQL5 is an adventure for everyone. Welcome to the enchantment!

The UT BOT ATR Trailing Indicator is a personal and customizable indicator that is very effective for traders who like to make quick decisions and make money from differences in price referred to as short-term trading (scalpers) and also proves to be vital and very effective for long-term traders (positional traders).

The article implements a fast strategy tester for machine learning models using Numba. It is 50 times faster than the pure Python strategy tester. The author recommends using this library to speed up mathematical calculations, especially the ones involving loops.

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.

The initial goal of this article is not to cover all the possibilities of Forex trading, but rather to adapt the system so that you can perform at least one market replay. We'll leave simulation for another moment. However, if we don't have ticks and only bars, with a little effort we can simulate possible trades that could happen in the Forex market. This will be the case until we look at how to adapt the simulator. An attempt to work with Forex data inside the system without modifying it leads to a range of errors.

In this article, we upgrade our Trade Assistant Tool by adding drag-and-drop panel functionality and hover effects to make the interface more intuitive and responsive. We refine the tool to validate real-time order setups, ensuring accurate trade configurations relative to market prices. We also backtest these enhancements to confirm their reliability.

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.

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.

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.

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.

Trends are an important part of many trading strategies. In this article, we will look at some of the tools used to identify trends and their characteristics. Understanding and correctly interpreting trends can significantly improve trading efficiency and minimize risks.

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.

The relentless quest to decode market rhythms has led traders and quantitative analysts to develop countless mathematical models. This article has introduced the Flower Volatility Index (FVI), a novel approach that transforms the mathematical elegance of Rose Curves into a functional trading tool. Through this work, we have shown how mathematical models can be adapted into practical trading mechanisms capable of supporting both analysis and decision-making in real market conditions.

This article discusses the application of a breakeven mechanism in automated strategies using the MQL5 language. We will start with a simple explanation of what the breakeven mode is, how it is implemented, and its possible variations. Next, this functionality will be integrated into the Order Blocks expert advisor, which we created in our last article on risk management. To evaluate its effectiveness, we will run two backtests under specific conditions: one using the breakeven mechanism and the other without it.

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.