Articles on trading system automation in MQL5

In this article, we'll complete our series about how to design a trading system based on the most popular technical indicator. We'll learn how to create a trading system based on the Alligator indicator.

By using special data types 'matrix' and 'vector', it is possible to create code which is very close to mathematical notation. With these methods, you can avoid the need to create nested loops or to mind correct indexing of arrays in calculations. Therefore, the use of matrix and vector methods increases the reliability and speed in developing complex programs.

Presenting the RSI Deep Three Move Trading Technique in MetaTrader 5. This article is based on a new series of studies that showcase a few trading techniques based on the RSI, a technical analysis indicator used to measure the strength and momentum of a security, such as a stock, currency, or commodity.

In this article, we will consider some of the essential points you should pay attention to when purchasing an Expert Advisor. We will also look for ways to increase profit, to spend money wisely, and to earn from this spending. Also, after reading the article, you will see that it is possible to earn even using simple and free products.

Enhance your market analysis with the MQL5-native Candlestick Probability EA, a lightweight tool that transforms raw price bars into real-time, instrument-specific probability insights. It classifies Pinbars, Engulfing, and Doji patterns at bar close, uses ATR-aware filtering, and optional breakout confirmation. The EA calculates raw and volume-weighted follow-through percentages, helping you understand each pattern's typical outcome on specific symbols and timeframes. On-chart markers, a compact dashboard, and interactive toggles allow easy validation and focus. Export detailed CSV logs for offline testing. Use it to develop probability profiles, optimize strategies, and turn pattern recognition into a measurable edge.

We will be creating a simple hedge EA as a base for our more advanced Grid-Hedge EA, which will be a mixture of classic grid and classic hedge strategies. By the end of this article, you will know how to create a simple hedge strategy, and you will also get to know what people say about whether this strategy is truly 100% profitable.

Welcome to a new article in our series about learning how to design a trading system by the most popular technical indicator here is a new article about learning how to design a trading system by Bear's Power technical indicator.

Python is a well-known and popular programming language with many features, especially in the fields of finance, data science, Artificial Intelligence, and Machine Learning. Python is a powerful tool that can be useful in trading as well. MQL5 allows us to use this powerful language as an integration to get our objectives done effectively. In this article, we will share how we can use Python as an integration in MQL5 after learning some basic information about Python.

In this article, we will complete our series about the Design Patterns topic, we mentioned that there are three types of design patterns creational, structural, and behavioral. We will complete the remaining patterns of the behavioral type which can help set the method of interaction between objects in a way that makes our code clean.

In this article, we build an Expert Advisor in MQL5 for the Asian Breakout Strategy by calculating the session's high and low and applying trend filtering with a moving average. We implement dynamic object styling, user-defined time inputs, and robust risk management. Finally, we demonstrate backtesting and optimization techniques to refine the program.

Combinations of strategies may offer better opportunities. We can combine indicators or patterns together, or even better, indicators with patterns, so that we get an extra confirmation factor. Moving averages help us confirm and ride the trend. They are the most known technical indicators and this is because of their simplicity and their proven track record of adding value to analyses.

The article considers the creation of machine learning models with time filters and discusses the effectiveness of this approach. The human factor can be eliminated now by simply instructing the model to trade at a certain hour of a certain day of the week. Pattern search can be provided by a separate algorithm.

The new article from our series about designing a trading system based on the most popular technical indicators considers a new technical indicator - the Money Flow Index (MFI). We will learn it in detail and develop a simple trading system by means of MQL5 to execute it in MetaTrader 5.

We have previously considered the mechanism of self-attention in neural networks. In practice, modern neural network architectures use several parallel self-attention threads to find various dependencies between the elements of a sequence. Let us consider the implementation of such an approach and evaluate its impact on the overall network performance.

A monitoring of the current state of a trade account implies controlling open positions and orders. Before a trade signal becomes a deal, it should be sent from the client terminal as a request to the trade server, where it will be placed in the order queue awaiting to be processed. Accepting of a request by the trade server, deleting it as it expires or conducting a deal on its basis - all those actions are followed by trade events; and the trade server informs the terminal about them.

Many people love them but a few understand the whole operations behind Neural Networks. In this article I will try to explain everything that goes behind closed doors of a feed-forward multi-layer perception in plain English.

This MetaTrader 5 Expert Advisor implements a Scalping OrderFlow strategy with advanced risk management. It uses multiple technical indicators to identify trading opportunities based on order flow imbalances. Backtesting shows potential profitability but highlights the need for further optimization, especially in risk management and trade outcome ratios. Suitable for experienced traders, it requires thorough testing and understanding before live deployment.

In this article, we create a supply and demand trading system in MQL5 that identifies supply and demand zones through consolidation ranges, validates them with impulsive moves, and trades retests with trend confirmation and customizable risk parameters. The system visualizes zones with dynamic labels and colors, supporting trailing stops for risk management.

In this article, we create an Expert Advisor (EA) in MQL5 to send messages to Telegram using a bot. We set up the necessary parameters, including the bot's API token and chat ID, and then perform an HTTP POST request to deliver the messages. Later, we handle the response to ensure successful delivery and troubleshoot any issues that arise in case of failure. This ensures we send messages from MQL5 to Telegram via the created bot.

In this article, we create an MQL5 Expert Advisor based on the Daily Range Breakout strategy. We cover the strategy’s key concepts, design the EA blueprint, and implement the breakout logic in MQL5. In the end, we explore techniques for backtesting and optimizing the EA to maximize its effectiveness.

My strategy is based on the classic trading fundamentals and the refinement of indicators that are widely used in all types of markets. This is a ready-made tool allowing you to follow the proposed new profitable trading strategy.