Algorithmic Trading Articles — Guides & Examples

Understanding Programming Paradigms (Part 2): An Object-Oriented Approach to Developing a Price Action Expert Advisor

Learn about the object-oriented programming paradigm and its application in MQL5 code. This second article goes deeper into the specifics of object-oriented programming, offering hands-on experience through a practical example. You'll learn how to convert our earlier developed procedural price action expert advisor using the EMA indicator and candlestick price data to object-oriented code.

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".

Neural networks made easy (Part 74): Trajectory prediction with adaptation

This article introduces a fairly effective method of multi-agent trajectory forecasting, which is able to adapt to various environmental conditions.

Price Driven CGI Model: Theoretical Foundation

Let's discuss the data manipulation algorithm, as we dive deeper into conceptualizing the idea of using price data to drive CGI objects. Think about transferring the effects of events, human emotions and actions on financial asset prices to a real-life model. This study delves into leveraging price data to influence the scale of a CGI object, controlling growth and emotions. These visible effects can establish a fresh analytical foundation for traders. Further insights are shared in the article.

Neural networks made easy (Part 72): Trajectory prediction in noisy environments

The quality of future state predictions plays an important role in the Goal-Conditioned Predictive Coding method, which we discussed in the previous article. In this article I want to introduce you to an algorithm that can significantly improve the prediction quality in stochastic environments, such as financial markets.

The Disagreement Problem: Diving Deeper into The Complexity Explainability in AI

In this article, we explore the challenge of understanding how AI works. AI models often make decisions in ways that are hard to explain, leading to what's known as the "disagreement problem". This issue is key to making AI more transparent and trustworthy.

Using PatchTST Machine Learning Algorithm for Predicting Next 24 Hours of Price Action

In this article, we apply a relatively complex neural network algorithm released in 2023 called PatchTST for predicting the price action for the next 24 hours. We will use the official repository, make slight modifications, train a model for EURUSD, and apply it to making future predictions both in Python and MQL5.

Eigenvectors and eigenvalues: Exploratory data analysis in MetaTrader 5

In this article we explore different ways in which the eigenvectors and eigenvalues can be applied in exploratory data analysis to reveal unique relationships in data.

Deep Learning GRU model with Python to ONNX with EA, and GRU vs LSTM models

We will guide you through the entire process of DL with python to make a GRU ONNX model, culminating in the creation of an Expert Advisor (EA) designed for trading, and subsequently comparing GRU model with LSTM model.

We will walk around statistical arbitrage, we will search with python for correlation and cointegration symbols, we will make an indicator for Pearson's coefficient and we will make an EA for trading statistical arbitrage with predictions done with python and ONNX models.

Creating an Interactive Graphical User Interface in MQL5 (Part 1): Making the Panel

This article explores the fundamental steps in crafting and implementing a Graphical User Interface (GUI) panel using MetaQuotes Language 5 (MQL5). Custom utility panels enhance user interaction in trading by simplifying common tasks and visualizing essential trading information. By creating custom panels, traders can streamline their workflow and save time during trading operations.

Building A Candlestick Trend Constraint Model (Part 5): Notification System (Part III)

This part of the article series is dedicated to integrating WhatsApp with MetaTrader 5 for notifications. We have included a flow chart to simplify understanding and will discuss the importance of security measures in integration. The primary purpose of indicators is to simplify analysis through automation, and they should include notification methods for alerting users when specific conditions are met. Discover more in this article.

Developing a Replay System (Part 41): Starting the second phase (II)

If everything seemed right to you up to this point, it means you're not really thinking about the long term, when you start developing applications. Over time you will no longer need to program new applications, you will just have to make them work together. So let's see how to finish assembling the mouse indicator.

Developing an MQL5 RL agent with RestAPI integration (Part 4): Organizing functions in classes in MQL5

This article discusses the transition from procedural coding to object-oriented programming (OOP) in MQL5 with an emphasis on integration with the REST API. Today we will discuss how to organize HTTP request functions (GET and POST) into classes. We will take a closer look at code refactoring and show how to replace isolated functions with class methods. The article contains practical examples and tests.

This article simplifies triangular arbitrage, showing you how to use predictions and specialized software to trade currencies smarter, even if you're new to the market. Ready to trade with expertise?

Automated Parameter Optimization for Trading Strategies Using Python and MQL5

There are several types of algorithms for self-optimization of trading strategies and parameters. These algorithms are used to automatically improve trading strategies based on historical and current market data. In this article we will look at one of them with python and MQL5 examples.

MQL5 Wizard Techniques you should know (Part 21): Testing with Economic Calendar Data

Economic Calendar Data is not available for testing with Expert Advisors within Strategy Tester, by default. We look at how Databases could help in providing a work around this limitation. So, for this article we explore how SQLite databases can be used to archive Economic Calendar news such that wizard assembled Expert Advisors can use this to generate trade signals.

MQL5 Trading Toolkit (Part 1): Developing A Positions Management EX5 Library

Learn how to create a developer's toolkit for managing various position operations with MQL5. In this article, I will demonstrate how to create a library of functions (ex5) that will perform simple to advanced position management operations, including automatic handling and reporting of the different errors that arise when dealing with position management tasks with MQL5.

Bill Williams Strategy with and without other indicators and predictions

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.

Integrate Your Own LLM into EA (Part 3): Training Your Own LLM with CPU

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.

Building A Candlestick Trend Constraint Model (Part 4): Customizing Display Style For Each Trend Wave

In this article, we will explore the capabilities of the powerful MQL5 language in drawing various indicator styles on Meta Trader 5. We will also look at scripts and how they can be used in our model.

Creating Time Series Predictions using LSTM Neural Networks: Normalizing Price and Tokenizing Time

This article outlines a simple strategy for normalizing the market data using the daily range and training a neural network to enhance market predictions. The developed models may be used in conjunction with an existing technical analysis frameworks or on a standalone basis to assist in predicting the overall market direction. The framework outlined in this article may be further refined by any technical analyst to develop models suitable for both manual and automated trading strategies.

Developing a Replay System (Part 39): Paving the Path (III)

Before we proceed to the second stage of development, we need to revise some ideas. Do you know how to make MQL5 do what you need? Have you ever tried to go beyond what is contained in the documentation? If not, then get ready. Because we will be doing something that most people don't normally do.

Population optimization algorithms: Resistance to getting stuck in local extrema (Part I)

This article presents a unique experiment that aims to examine the behavior of population optimization algorithms in the context of their ability to efficiently escape local minima when population diversity is low and reach global maxima. Working in this direction will provide further insight into which specific algorithms can successfully continue their search using coordinates set by the user as a starting point, and what factors influence their success.

MQL5 Wizard Techniques you should know (Part 20): Symbolic Regression

Symbolic Regression is a form of regression that starts with minimal to no assumptions on what the underlying model that maps the sets of data under study would look like. Even though it can be implemented by Bayesian Methods or Neural Networks, we look at how an implementation with Genetic Algorithms can help customize an expert signal class usable in the MQL5 wizard.

Spurious regressions occur when two time series exhibit a high degree of correlation purely by chance, leading to misleading results in regression analysis. In such cases, even though variables may appear to be related, the correlation is coincidental and the model may be unreliable.

Data Science and Machine Learning (Part 20): Algorithmic Trading Insights, A Faceoff Between LDA and PCA in MQL5

Uncover the secrets behind these powerful dimensionality reduction techniques as we dissect their applications within the MQL5 trading environment. Delve into the nuances of Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA), gaining a profound understanding of their impact on strategy development and market analysis.

MQL5 Wizard Techniques you should know (Part 24): Moving Averages

Moving Averages are a very common indicator that are used and understood by most Traders. We explore possible use cases that may not be so common within MQL5 Wizard assembled Expert Advisors.

The base class of population algorithms as the backbone of efficient optimization

The article represents a unique research attempt to combine a variety of population algorithms into a single class to simplify the application of optimization methods. This approach not only opens up opportunities for the development of new algorithms, including hybrid variants, but also creates a universal basic test stand. This stand becomes a key tool for choosing the optimal algorithm depending on a specific task.

Building A Candlestick Trend Constraint Model (Part 5): Notification System (Part I)

We will breakdown the main MQL5 code into specified code snippets to illustrate the integration of Telegram and WhatsApp for receiving signal notifications from the Trend Constraint indicator we are creating in this article series. This will help traders, both novices and experienced developers, grasp the concept easily. First, we will cover the setup of MetaTrader 5 for notifications and its significance to the user. This will help developers in advance to take notes to further apply in their systems.

Data label for time series mining (Part 5)：Apply and Test in EA Using Socket

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!

Balancing risk when trading multiple instruments simultaneously

This article will allow a beginner to write an implementation of a script from scratch for balancing risks when trading multiple instruments simultaneously. Besides, it may give experienced users new ideas for implementing their solutions in relation to the options proposed in this article.

This article will cover angle-based operations. We will look at methods for constructing angles and using them in trading.

DoEasy. Controls (Part 33): Vertical ScrollBar

In this article, we will continue the development of graphical elements of the DoEasy library and add vertical scrolling of form object controls, as well as some useful functions and methods that will be required in the future.

Developing a Replay System (Part 38): Paving the Path (II)

Many people who consider themselves MQL5 programmers do not have the basic knowledge that I will outline in this article. Many people consider MQL5 to be a limited tool, but the actual reason is that they do not have the required knowledge. So, if you don't know something, don't be ashamed of it. It's better to feel ashamed for not asking. Simply forcing MetaTrader 5 to disable indicator duplication in no way ensures two-way communication between the indicator and the Expert Advisor. We are still very far from this, but the fact that the indicator is not duplicated on the chart gives us some confidence.

Developing an MQL5 RL agent with RestAPI integration (Part 3): Creating automatic moves and test scripts in MQL5

This article discusses the implementation of automatic moves in the tic-tac-toe game in Python, integrated with MQL5 functions and unit tests. The goal is to improve the interactivity of the game and ensure the reliability of the system through testing in MQL5. The presentation covers game logic development, integration, and hands-on testing, and concludes with the creation of a dynamic game environment and a robust integrated system.

Neural networks made easy (Part 75): Improving the performance of trajectory prediction models

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.

MQL5 Wizard Techniques you should know (Part 12): Newton Polynomial

Newton’s polynomial, which creates quadratic equations from a set of a few points, is an archaic but interesting approach at looking at a time series. In this article we try to explore what aspects could be of use to traders from this approach as well as address its limitations.

Developing a multi-currency Expert Advisor (Part 3): Architecture revision

We have already made some progress in developing a multi-currency EA with several strategies working in parallel. Considering the accumulated experience, let's review the architecture of our solution and try to improve it before we go too far ahead.

A Step-by-Step Guide on Trading the Break of Structure (BoS) Strategy

A comprehensive guide to developing an automated trading algorithm based on the Break of Structure (BoS) strategy. Detailed information on all aspects of creating an advisor in MQL5 and testing it in MetaTrader 5 — from analyzing price support and resistance to risk management

Understanding Programming Paradigms (Part 2): An Object-Oriented Approach to Developing a Price Action Expert Advisor

Neural networks made easy (Part 73): AutoBots for predicting price movements

Neural networks made easy (Part 74): Trajectory prediction with adaptation

Price Driven CGI Model: Theoretical Foundation

Neural networks made easy (Part 72): Trajectory prediction in noisy environments

The Disagreement Problem: Diving Deeper into The Complexity Explainability in AI

Using PatchTST Machine Learning Algorithm for Predicting Next 24 Hours of Price Action

Eigenvectors and eigenvalues: Exploratory data analysis in MetaTrader 5

Deep Learning GRU model with Python to ONNX with EA, and GRU vs LSTM models

Statistical Arbitrage with predictions

Creating an Interactive Graphical User Interface in MQL5 (Part 1): Making the Panel

Building A Candlestick Trend Constraint Model (Part 5): Notification System (Part III)

Developing a Replay System (Part 41): Starting the second phase (II)

Developing an MQL5 RL agent with RestAPI integration (Part 4): Organizing functions in classes in MQL5

Triangular arbitrage with predictions

Automated Parameter Optimization for Trading Strategies Using Python and MQL5

MQL5 Wizard Techniques you should know (Part 21): Testing with Economic Calendar Data

MQL5 Trading Toolkit (Part 1): Developing A Positions Management EX5 Library

Bill Williams Strategy with and without other indicators and predictions

Integrate Your Own LLM into EA (Part 3): Training Your Own LLM with CPU

Building A Candlestick Trend Constraint Model (Part 4): Customizing Display Style For Each Trend Wave

Creating Time Series Predictions using LSTM Neural Networks: Normalizing Price and Tokenizing Time

Developing a Replay System (Part 39): Paving the Path (III)

Population optimization algorithms: Resistance to getting stuck in local extrema (Part I)

MQL5 Wizard Techniques you should know (Part 20): Symbolic Regression

Spurious Regressions in Python

Data Science and Machine Learning (Part 20): Algorithmic Trading Insights, A Faceoff Between LDA and PCA in MQL5

MQL5 Wizard Techniques you should know (Part 24): Moving Averages

The base class of population algorithms as the backbone of efficient optimization

Building A Candlestick Trend Constraint Model (Part 5): Notification System (Part I)

Data label for time series mining (Part 5)：Apply and Test in EA Using Socket

Balancing risk when trading multiple instruments simultaneously

Angle-based operations for traders

DoEasy. Controls (Part 33): Vertical ScrollBar

Developing a Replay System (Part 38): Paving the Path (II)

Developing an MQL5 RL agent with RestAPI integration (Part 3): Creating automatic moves and test scripts in MQL5

Neural networks made easy (Part 75): Improving the performance of trajectory prediction models

MQL5 Wizard Techniques you should know (Part 12): Newton Polynomial

Developing a multi-currency Expert Advisor (Part 3): Architecture revision

A Step-by-Step Guide on Trading the Break of Structure (BoS) Strategy