Algorithmic Trading Articles — Guides & Examples

WebSockets for MetaTrader 5 — Using the Windows API

In this article, we will use the WinHttp.dll to create a WebSocket client for MetaTrader 5 programs. The client will ultimately be implemented as a class and also tested against the Deriv.com WebSocket API.

Master MQL5 from beginner to pro (Part I): Getting started with programming

This article is an introduction to a series of articles about programming. It is assumed here that the reader has never dealt with programming before. So, this series starts from the very basics. Programming knowledge level: Absolute Beginner.

Population optimization algorithms: Intelligent Water Drops (IWD) algorithm

The article considers an interesting algorithm derived from inanimate nature - intelligent water drops (IWD) simulating the process of river bed formation. The ideas of this algorithm made it possible to significantly improve the previous leader of the rating - SDS. As usual, the new leader (modified SDSm) can be found in the attachment.

Mastering Model Interpretation: Gaining Deeper Insight From Your Machine Learning Models

Machine Learning is a complex and rewarding field for anyone of any experience. In this article we dive deep into the inner mechanisms powering the models you build, we explore the intricate world of features,predictions and impactful decisions unravelling the complexities and gaining a firm grasp of model interpretation. Learn the art of navigating tradeoffs , enhancing predictions, ranking feature importance all while ensuring robust decision making. This essential read helps you clock more performance from your machine learning models and extract more value for employing machine learning methodologies.

Integrating ML models with the Strategy Tester (Conclusion): Implementing a regression model for price prediction

This article describes the implementation of a regression model based on a decision tree. The model should predict prices of financial assets. We have already prepared the data, trained and evaluated the model, as well as adjusted and optimized it. However, it is important to note that this model is intended for study purposes only and should not be used in real trading.

In this article, we will look at the principles of creating multi-symbol, multi-period indicators. We will also see how to access the data of such indicators from Expert Advisors and other indicators. We will consider the main features of using multi-indicators in Expert Advisors and indicators and will see how to plot them through custom indicator buffers.

Cross-validation and basics of causal inference in CatBoost models, export to ONNX format

The article proposes the method of creating bots using machine learning.

Trader-friendly stop loss and take profit

Stop loss and take profit can have a significant impact on trading results. In this article, we will look at several ways to find optimal stop order values.

Data Science and Machine Learning (Part 15): SVM, A Must-Have Tool in Every Trader's Toolbox

Discover the indispensable role of Support Vector Machines (SVM) in shaping the future of trading. This comprehensive guide explores how SVM can elevate your trading strategies, enhance decision-making, and unlock new opportunities in the financial markets. Dive into the world of SVM with real-world applications, step-by-step tutorials, and expert insights. Equip yourself with the essential tool that can help you navigate the complexities of modern trading. Elevate your trading game with SVM—a must-have for every trader's toolbox.

How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 7): ZigZag with Awesome Oscillator Indicators Signal

The multi-currency expert advisor in this article is an expert advisor or automated trading that uses ZigZag indicator which are filtered with the Awesome Oscillator or filter each other's signals.

Developing an MQTT client for Metatrader 5: a TDD approach — Part 6

This article is the sixth part of a series describing our development steps of a native MQL5 client for the MQTT 5.0 protocol. In this part we comment on the main changes in our first refactoring, how we arrived at a viable blueprint for our packet-building classes, how we are building PUBLISH and PUBACK packets, and the semantics behind the PUBACK Reason Codes.

Introduction to MQL5 (Part 2): Navigating Predefined Variables, Common Functions, and Control Flow Statements

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!

Introduction to MQL5 (Part 4): Mastering Structures, Classes, and Time Functions

Unlock the secrets of MQL5 programming in our latest article! Delve into the essentials of structures, classes, and time functions, empowering your coding journey. Whether you're a beginner or an experienced developer, our guide simplifies complex concepts, providing valuable insights for mastering MQL5. Elevate your programming skills and stay ahead in the world of algorithmic trading!

Backpropagation Neural Networks using MQL5 Matrices

The article describes the theory and practice of applying the backpropagation algorithm in MQL5 using matrices. It provides ready-made classes along with script, indicator and Expert Advisor examples.

Quantization in machine learning (Part 2): Data preprocessing, table selection, training CatBoost models

The article considers the practical application of quantization in the construction of tree models. The methods for selecting quantum tables and data preprocessing are considered. No complex mathematical equations are used.

Neural networks made easy (Part 62): Using Decision Transformer in hierarchical models

In recent articles, we have seen several options for using the Decision Transformer method. The method allows analyzing not only the current state, but also the trajectory of previous states and actions performed in them. In this article, we will focus on using this method in hierarchical models.

Developing a Replay System (Part 28): Expert Advisor project — C_Mouse class (II)

When people started creating the first systems capable of computing, everything required the participation of engineers, who had to know the project very well. We are talking about the dawn of computer technology, a time when there were not even terminals for programming. As it developed and more people got interested in being able to create something, new ideas and ways of programming emerged which replaced the previous-style changing of connector positions. This is when the first terminals appeared.

Developing a Replay System (Part 27): Expert Advisor project — C_Mouse class (I)

In this article we will implement the C_Mouse class. It provides the ability to program at the highest level. However, talking about high-level or low-level programming languages is not about including obscene words or jargon in the code. It's the other way around. When we talk about high-level or low-level programming, we mean how easy or difficult the code is for other programmers to understand.

Category Theory in MQL5 (Part 23): A different look at the Double Exponential Moving Average

In this article we continue with our theme in the last of tackling everyday trading indicators viewed in a ‘new’ light. We are handling horizontal composition of natural transformations for this piece and the best indicator for this, that expands on what we just covered, is the double exponential moving average (DEMA).

Developing a Replay System (Part 30): Expert Advisor project — C_Mouse class (IV)

Today we will learn a technique that can help us a lot in different stages of our professional life as a programmer. Often it is not the platform itself that is limited, but the knowledge of the person who talks about the limitations. This article will tell you that with common sense and creativity you can make the MetaTrader 5 platform much more interesting and versatile without resorting to creating crazy programs or anything like that, and create simple yet safe and reliable code. We will use our creativity to modify existing code without deleting or adding a single line to the source code.

Benefiting from Forex market seasonality

We are all familiar with the concept of seasonality, for example, we are all accustomed to rising prices for fresh vegetables in winter or rising fuel prices during severe frosts, but few people know that similar patterns exist in the Forex market.

Developing a Replay System (Part 29): Expert Advisor project — C_Mouse class (III)

After improving the C_Mouse class, we can focus on creating a class designed to create a completely new framework fr our analysis. We will not use inheritance or polymorphism to create this new class. Instead, we will change, or better said, add new objects to the price line. That's what we will do in this article. In the next one, we will look at how to change the analysis. All this will be done without changing the code of the C_Mouse class. Well, actually, it would be easier to achieve this using inheritance or polymorphism. However, there are other methods to achieve the same result.

Modified Grid-Hedge EA in MQL5 (Part III): Optimizing Simple Hedge Strategy (I)

In this third part, we revisit the Simple Hedge and Simple Grid Expert Advisors (EAs) developed earlier. Our focus shifts to refining the Simple Hedge EA through mathematical analysis and a brute force approach, aiming for optimal strategy usage. This article delves deep into the mathematical optimization of the strategy, setting the stage for future exploration of coding-based optimization in later installments.

Neural networks made easy (Part 61): Optimism issue in offline reinforcement learning

During the offline learning, we optimize the Agent's policy based on the training sample data. The resulting strategy gives the Agent confidence in its actions. However, such optimism is not always justified and can cause increased risks during the model operation. Today we will look at one of the methods to reduce these risks.

Quantization in machine learning (Part 1): Theory, sample code, analysis of implementation in CatBoost

The article considers the theoretical application of quantization in the construction of tree models and showcases the implemented quantization methods in CatBoost. No complex mathematical equations are used.

Working with ONNX models in float16 and float8 formats

Data formats used to represent machine learning models play a crucial role in their effectiveness. In recent years, several new types of data have emerged, specifically designed for working with deep learning models. In this article, we will focus on two new data formats that have become widely adopted in modern models.

Experiments with neural networks (Part 7): Passing indicators

Examples of passing indicators to a perceptron. The article describes general concepts and showcases the simplest ready-made Expert Advisor followed by the results of its optimization and forward test.

Neural networks made easy (Part 60): Online Decision Transformer (ODT)

The last two articles were devoted to the Decision Transformer method, which models action sequences in the context of an autoregressive model of desired rewards. In this article, we will look at another optimization algorithm for this method.

Population optimization algorithms: Mind Evolutionary Computation (MEC) algorithm

The article considers the algorithm of the MEC family called the simple mind evolutionary computation algorithm (Simple MEC, SMEC). The algorithm is distinguished by the beauty of its idea and ease of implementation.

Developing an MQTT client for Metatrader 5: a TDD approach — Part 4

This article is the fourth part of a series describing our development steps of a native MQL5 client for the MQTT protocol. In this part, we describe what MQTT v5.0 Properties are, their semantics, how we are reading some of them, and provide a brief example of how Properties can be used to extend the protocol.

Developing a Replay System (Part 26): Expert Advisor project — C_Terminal class

We can now start creating an Expert Advisor for use in the replay/simulation system. However, we need something improved, not a random solution. Despite this, we should not be intimidated by the initial complexity. It's important to start somewhere, otherwise we end up ruminating about the difficulty of a task without even trying to overcome it. That's what programming is all about: overcoming obstacles through learning, testing, and extensive research.

Developing a Replay System — Market simulation (Part 25): Preparing for the next phase

In this article, we complete the first phase of developing our replay and simulation system. Dear reader, with this achievement I confirm that the system has reached an advanced level, paving the way for the introduction of new functionality. The goal is to enrich the system even further, turning it into a powerful tool for research and development of market analysis.

Developing a Replay System — Market simulation (Part 23): FOREX (IV)

Now the creation occurs at the same point where we converted ticks into bars. This way, if something goes wrong during the conversion process, we will immediately notice the error. This is because the same code that places 1-minute bars on the chart during fast forwarding is also used for the positioning system to place bars during normal performance. In other words, the code that is responsible for this task is not duplicated anywhere else. This way we get a much better system for both maintenance and improvement.

Neural networks are easy (Part 59): Dichotomy of Control (DoC)

In the previous article, we got acquainted with the Decision Transformer. But the complex stochastic environment of the foreign exchange market did not allow us to fully implement the potential of the presented method. In this article, I will introduce an algorithm that is aimed at improving the performance of algorithms in stochastic environments.

Developing a Replay System — Market simulation (Part 22): FOREX (III)

Although this is the third article on this topic, I must explain for those who have not yet understood the difference between the stock market and the foreign exchange market: the big difference is that in the Forex there is no, or rather, we are not given information about some points that actually occurred during the course of trading.

Population optimization algorithms: Stochastic Diffusion Search (SDS)

The article discusses Stochastic Diffusion Search (SDS), which is a very powerful and efficient optimization algorithm based on the principles of random walk. The algorithm allows finding optimal solutions in complex multidimensional spaces, while featuring a high speed of convergence and the ability to avoid local extrema.

Developing a Replay System — Market simulation (Part 21): FOREX (II)

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.

Ready-made templates for including indicators to Expert Advisors (Part 1): Oscillators

The article considers standard indicators from the oscillator category. We will create ready-to-use templates for their use in EAs - declaring and setting parameters, indicator initialization and deinitialization, as well as receiving data and signals from indicator buffers in EAs.

Neural networks made easy (Part 58): Decision Transformer (DT)

We continue to explore reinforcement learning methods. In this article, I will focus on a slightly different algorithm that considers the Agent’s policy in the paradigm of constructing a sequence of actions.

Making a dashboard to display data in indicators and EAs

In this article, we will create a dashboard class to be used in indicators and EAs. This is an introductory article in a small series of articles with templates for including and using standard indicators in Expert Advisors. I will start by creating a panel similar to the MetaTrader 5 data window.