Articles on trading system automation in MQL5
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Neural networks made easy (Part 23): Building a tool for Transfer Learning
In this series of articles, we have already mentioned Transfer Learning more than once. However, this was only mentioning. in this article, I suggest filling this gap and taking a closer look at Transfer Learning.
Price Action Analysis Toolkit Development (Part 16): Introducing Quarters Theory (II) — Intrusion Detector EA
In our previous article, we introduced a simple script called "The Quarters Drawer." Building on that foundation, we are now taking the next step by creating a monitor Expert Advisor (EA) to track these quarters and provide oversight regarding potential market reactions at these levels. Join us as we explore the process of developing a zone detection tool in this article.
News Trading Made Easy (Part 2): Risk Management
In this article, inheritance will be introduced into our previous and new code. A new database design will be implemented to provide efficiency. Additionally, a risk management class will be created to tackle volume calculations.
Neural networks made easy (Part 73): AutoBots for predicting price movements
We continue to discuss algorithms for training trajectory prediction models. In this article, we will get acquainted with a method called "AutoBots".
Volumetric neural network analysis as a key to future trends
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.
Neural networks made easy (Part 53): Reward decomposition
We have already talked more than once about the importance of correctly selecting the reward function, which we use to stimulate the desired behavior of the Agent by adding rewards or penalties for individual actions. But the question remains open about the decryption of our signals by the Agent. In this article, we will talk about reward decomposition in terms of transmitting individual signals to the trained Agent.
Design Patterns in software development and MQL5 (Part I): Creational Patterns
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.
Multilayer perceptron and backpropagation algorithm (Part 3): Integration with the Strategy Tester - Overview (I).
The multilayer perceptron is an evolution of the simple perceptron which can solve non-linear separable problems. Together with the backpropagation algorithm, this neural network can be effectively trained. In Part 3 of the Multilayer Perceptron and Backpropagation series, we'll see how to integrate this technique into the Strategy Tester. This integration will allow the use of complex data analysis aimed at making better decisions to optimize your trading strategies. In this article, we will discuss the advantages and problems of this technique.
Developing a multi-currency Expert Advisor (Part 13): Automating the second stage — selection into groups
We have already implemented the first stage of the automated optimization. We perform optimization for different symbols and timeframes according to several criteria and store information about the results of each pass in the database. Now we are going to select the best groups of parameter sets from those found at the first stage.
Developing a trading Expert Advisor from scratch (Part 23): New order system (VI)
We will make the order system more flexible. Here we will consider changes to the code that will make it more flexible, which will allow us to change position stop levels much faster.
Price Action Analysis Toolkit Development (Part 13): RSI Sentinel Tool
Price action can be effectively analyzed by identifying divergences, with technical indicators such as the RSI providing crucial confirmation signals. In the article below, we explain how automated RSI divergence analysis can identify trend continuations and reversals, thereby offering valuable insights into market sentiment.
Automating Trading Strategies in MQL5 (Part 21): Enhancing Neural Network Trading with Adaptive Learning Rates
In this article, we enhance a neural network trading strategy in MQL5 with an adaptive learning rate to boost accuracy. We design and implement this mechanism, then test its performance. The article concludes with optimization insights for algorithmic trading
Neural networks made easy (Part 20): Autoencoders
We continue to study unsupervised learning algorithms. Some readers might have questions regarding the relevance of recent publications to the topic of neural networks. In this new article, we get back to studying neural networks.
Integrate Your Own LLM into EA (Part 2): Example of Environment Deployment
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.
Trading with the MQL5 Economic Calendar (Part 6): Automating Trade Entry with News Event Analysis and Countdown Timers
In this article, we implement automated trade entry using the MQL5 Economic Calendar by applying user-defined filters and time offsets to identify qualifying news events. We compare forecast and previous values to determine whether to open a BUY or SELL trade. Dynamic countdown timers display the remaining time until news release and reset automatically after a trade.
Creating an MQL5-Telegram Integrated Expert Advisor (Part 3): Sending Chart Screenshots with Captions from MQL5 to Telegram
In this article, we create an MQL5 Expert Advisor that encodes chart screenshots as image data and sends them to a Telegram chat via HTTP requests. By integrating photo encoding and transmission, we enhance the existing MQL5-Telegram system with visual trading insights directly within Telegram.
Neural networks made easy (Part 66): Exploration problems in offline learning
Models are trained offline using data from a prepared training dataset. While providing certain advantages, its negative side is that information about the environment is greatly compressed to the size of the training dataset. Which, in turn, limits the possibilities of exploration. In this article, we will consider a method that enables the filling of a training dataset with the most diverse data possible.
Building A Candlestick Trend Constraint Model(Part 3): Detecting changes in trends while using this system
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.
Integrate Your Own LLM into EA (Part 5): Develop and Test Trading Strategy with LLMs (III) – Adapter-Tuning
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.
Trading with the MQL5 Economic Calendar (Part 9): Elevating News Interaction with a Dynamic Scrollbar and Polished Display
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.
Neural Networks in Trading: Scene-Aware Object Detection (HyperDet3D)
We invite you to get acquainted with a new approach to detecting objects using hypernetworks. A hypernetwork generates weights for the main model, which allows taking into account the specifics of the current market situation. This approach allows us to improve forecasting accuracy by adapting the model to different trading conditions.
Advanced Variables and Data Types in MQL5
Variables and data types are very important topics not only in MQL5 programming but also in any programming language. MQL5 variables and data types can be categorized as simple and advanced ones. In this article, we will identify and learn about advanced ones because we already mentioned simple ones in a previous article.
Building A Candlestick Trend Constraint Model (Part 1): For EAs And Technical Indicators
This article is aimed at beginners and pro-MQL5 developers. It provides a piece of code to define and constrain signal-generating indicators to trends in higher timeframes. In this way, traders can enhance their strategies by incorporating a broader market perspective, leading to potentially more robust and reliable trading signals.
Price Action Analysis Toolkit Development (Part 17): TrendLoom EA Tool
As a price action observer and trader, I've noticed that when a trend is confirmed by multiple timeframes, it usually continues in that direction. What may vary is how long the trend lasts, and this depends on the type of trader you are, whether you hold positions for the long term or engage in scalping. The timeframes you choose for confirmation play a crucial role. Check out this article for a quick, automated system that helps you analyze the overall trend across different timeframes with just a button click or regular updates.
Building a Candlestick Trend Constraint Model (Part 8): Expert Advisor Development (I)
In this discussion, we will create our first Expert Advisor in MQL5 based on the indicator we made in the prior article. We will cover all the features required to make the process automatic, including risk management. This will extensively benefit the users to advance from manual execution of trades to automated systems.
Data Science and Machine Learning(Part 14): Finding Your Way in the Markets with Kohonen Maps
Are you looking for a cutting-edge approach to trading that can help you navigate complex and ever-changing markets? Look no further than Kohonen maps, an innovative form of artificial neural networks that can help you uncover hidden patterns and trends in market data. In this article, we'll explore how Kohonen maps work, and how they can be used to develop smarter, more effective trading strategies. Whether you're a seasoned trader or just starting out, you won't want to miss this exciting new approach to trading.
William Gann methods (Part II): Creating Gann Square indicator
We will create an indicator based on the Gann's Square of 9, built by squaring time and price. We will prepare the code and test the indicator in the platform on different time intervals.
Neural Networks Made Easy (Part 88): Time-Series Dense Encoder (TiDE)
In an attempt to obtain the most accurate forecasts, researchers often complicate forecasting models. Which in turn leads to increased model training and maintenance costs. Is such an increase always justified? This article introduces an algorithm that uses the simplicity and speed of linear models and demonstrates results on par with the best models with a more complex architecture.
Introduction to MQL5 (Part 8): Beginner's Guide to Building Expert Advisors (II)
This article addresses common beginner questions from MQL5 forums and demonstrates practical solutions. Learn to perform essential tasks like buying and selling, obtaining candlestick prices, and managing automated trading aspects such as trade limits, trading periods, and profit/loss thresholds. Get step-by-step guidance to enhance your understanding and implementation of these concepts in MQL5.
Creating an MQL5-Telegram Integrated Expert Advisor (Part 2): Sending Signals from MQL5 to Telegram
In this article, we create an MQL5-Telegram integrated Expert Advisor that sends moving average crossover signals to Telegram. We detail the process of generating trading signals from moving average crossovers, implementing the necessary code in MQL5, and ensuring the integration works seamlessly. The result is a system that provides real-time trading alerts directly to your Telegram group chat.
Creating a Dynamic Multi-Symbol, Multi-Period Relative Strength Indicator (RSI) Indicator Dashboard in MQL5
In this article, we develop a dynamic multi-symbol, multi-period RSI indicator dashboard in MQL5, providing traders real-time RSI values across various symbols and timeframes. The dashboard features interactive buttons, real-time updates, and color-coded indicators to help traders make informed decisions.
Experiments with neural networks (Part 4): Templates
In this article, I will use experimentation and non-standard approaches to develop a profitable trading system and check whether neural networks can be of any help for traders. MetaTrader 5 as a self-sufficient tool for using neural networks in trading. Simple explanation.
Integrate Your Own LLM into EA (Part 1): Hardware and Environment Deployment
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.
Developing a multi-currency Expert Advisor (Part 17): Further preparation for real trading
Currently, our EA uses the database to obtain initialization strings for single instances of trading strategies. However, the database is quite large and contains a lot of information that is not needed for the actual EA operation. Let's try to ensure the EA's functionality without a mandatory connection to the database.
Automated exchange grid trading using stop pending orders on Moscow Exchange (MOEX)
The article considers the grid trading approach based on stop pending orders and implemented in an MQL5 Expert Advisor on the Moscow Exchange (MOEX). When trading in the market, one of the simplest strategies is a grid of orders designed to "catch" the market price.
MetaTrader 5 Machine Learning Blueprint (Part 1): Data Leakage and Timestamp Fixes
Before we can even begin to make use of ML in our trading on MetaTrader 5, it’s crucial to address one of the most overlooked pitfalls—data leakage. This article unpacks how data leakage, particularly the MetaTrader 5 timestamp trap, can distort our model's performance and lead to unreliable trading signals. By diving into the mechanics of this issue and presenting strategies to prevent it, we pave the way for building robust machine learning models that deliver trustworthy predictions in live trading environments.
Introduction to MQL5 (Part 14): A Beginner's Guide to Building Custom Indicators (III)
Learn to build a Harmonic Pattern indicator in MQL5 using chart objects. Discover how to detect swing points, apply Fibonacci retracements, and automate pattern recognition.
Brute force approach to patterns search (Part V): Fresh angle
In this article, I will show a completely different approach to algorithmic trading I ended up with after quite a long time. Of course, all this has to do with my brute force program, which has undergone a number of changes that allow it to solve several problems simultaneously. Nevertheless, the article has turned out to be more general and as simple as possible, which is why it is also suitable for those who know nothing about brute force.
Creating an MQL5-Telegram Integrated Expert Advisor (Part 6): Adding Responsive Inline Buttons
In this article, we integrate interactive inline buttons into an MQL5 Expert Advisor, allowing real-time control via Telegram. Each button press triggers specific actions and sends responses back to the user. We also modularize functions for handling Telegram messages and callback queries efficiently.
Neural networks made easy (Part 44): Learning skills with dynamics in mind
In the previous article, we introduced the DIAYN method, which offers the algorithm for learning a variety of skills. The acquired skills can be used for various tasks. But such skills can be quite unpredictable, which can make them difficult to use. In this article, we will look at an algorithm for learning predictable skills.