
Advanced resampling and selection of CatBoost models by brute-force method
This article describes one of the possible approaches to data transformation aimed at improving the generalizability of the model, and also discusses sampling and selection of CatBoost models.

Neural networks made easy (Part 21): Variational autoencoders (VAE)
In the last article, we got acquainted with the Autoencoder algorithm. Like any other algorithm, it has its advantages and disadvantages. In its original implementation, the autoenctoder is used to separate the objects from the training sample as much as possible. This time we will talk about how to deal with some of its disadvantages.

Regression models of the Scikit-learn Library and their export to ONNX
In this article, we will explore the application of regression models from the Scikit-learn package, attempt to convert them into ONNX format, and use the resultant models within MQL5 programs. Additionally, we will compare the accuracy of the original models with their ONNX versions for both float and double precision. Furthermore, we will examine the ONNX representation of regression models, aiming to provide a better understanding of their internal structure and operational principles.

Population optimization algorithms: Harmony Search (HS)
In the current article, I will study and test the most powerful optimization algorithm - harmonic search (HS) inspired by the process of finding the perfect sound harmony. So what algorithm is now the leader in our rating?

Developing a trading robot in Python (Part 3): Implementing a model-based trading algorithm
We continue the series of articles on developing a trading robot in Python and MQL5. In this article, we will create a trading algorithm in Python.


MQL4 as a Trader's Tool, or The Advanced Technical Analysis
Trading is, first of all, a calculus of probabilities. The proverb about idleness being an engine for progress reveals us the reason why all those indicators and trading systems have been developed. It comes that the major of newcomers in trading study "ready-made" trading theories. But, as luck would have it, there are some more undiscovered market secrets, and tools used in analyzing of price movements exist, basically, as those unrealized technical indicators or math and stat packages. Thanks awfully to Bill Williams for his contribution to the market movements theory. Though, perhaps, it's too early to rest on oars.

Data Science and Machine Learning (Part 07): Polynomial Regression
Unlike linear regression, polynomial regression is a flexible model aimed to perform better at tasks the linear regression model could not handle, Let's find out how to make polynomial models in MQL5 and make something positive out of it.


Timeseries in DoEasy library (part 48): Multi-period multi-symbol indicators on one buffer in a subwindow
The article considers an example of creating multi-symbol multi-period standard indicators using a single indicator buffer for construction and working in the indicator subwindow. I am going to prepare the library classes for working with standard indicators working in the program main window and having more than one buffer for displaying their data.

Data Science and Machine Learning (Part 06): Gradient Descent
The gradient descent plays a significant role in training neural networks and many machine learning algorithms. It is a quick and intelligent algorithm despite its impressive work it is still misunderstood by a lot of data scientists let's see what it is all about.

Neural networks made easy (Part 15): Data clustering using MQL5
We continue to consider the clustering method. In this article, we will create a new CKmeans class to implement one of the most common k-means clustering methods. During tests, the model managed to identify about 500 patterns.

Mastering ONNX: The Game-Changer for MQL5 Traders
Dive into the world of ONNX, the powerful open-standard format for exchanging machine learning models. Discover how leveraging ONNX can revolutionize algorithmic trading in MQL5, allowing traders to seamlessly integrate cutting-edge AI models and elevate their strategies to new heights. Uncover the secrets to cross-platform compatibility and learn how to unlock the full potential of ONNX in your MQL5 trading endeavors. Elevate your trading game with this comprehensive guide to Mastering ONNX

Price Action Analysis Toolkit Development (Part 6): Mean Reversion Signal Reaper
While some concepts may seem straightforward at first glance, bringing them to life in practice can be quite challenging. In the article below, we'll take you on a journey through our innovative approach to automating an Expert Advisor (EA) that skillfully analyzes the market using a mean reversion strategy. Join us as we unravel the intricacies of this exciting automation process.

Category Theory (Part 9): Monoid-Actions
This article continues the series on category theory implementation in MQL5. Here we continue monoid-actions as a means of transforming monoids, covered in the previous article, leading to increased applications.

Neural networks made easy (Part 25): Practicing Transfer Learning
In the last two articles, we developed a tool for creating and editing neural network models. Now it is time to evaluate the potential use of Transfer Learning technology using practical examples.

Parallel Particle Swarm Optimization
The article describes a method of fast optimization using the particle swarm algorithm. It also presents the method implementation in MQL, which is ready for use both in single-threaded mode inside an Expert Advisor and in a parallel multi-threaded mode as an add-on that runs on local tester agents.


Population optimization algorithms
This is an introductory article on optimization algorithm (OA) classification. The article attempts to create a test stand (a set of functions), which is to be used for comparing OAs and, perhaps, identifying the most universal algorithm out of all widely known ones.


MQL5 Market Results for Q2 2013
Successfully operating for 1.5 years, MQL5 Market has become the largest traders' store of trading strategies and technical indicators. It offers around 800 trading applications provided by 350 developers from around the world. Over 100.000 trading programs have already been purchased and downloaded by traders to their MetaTrader 5 terminals.


Timeseries in DoEasy library (part 47): Multi-period multi-symbol standard indicators
In this article, I will start developing the methods of working with standard indicators, which will ultimately allow creating multi-symbol multi-period standard indicators based on library classes. Besides, I will add the "Skipped bars" event to the timeseries classes and eliminate excessive load from the main program code by moving the library preparation functions to CEngine class.

Population optimization algorithms: Grey Wolf Optimizer (GWO)
Let's consider one of the newest modern optimization algorithms - Grey Wolf Optimization. The original behavior on test functions makes this algorithm one of the most interesting among the ones considered earlier. This is one of the top algorithms for use in training neural networks, smooth functions with many variables.

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.


Trader's Statistical Cookbook: Hypotheses
This article considers hypothesis - one of the basic ideas of mathematical statistics. Various hypotheses are examined and verified through examples using methods of mathematical statistics. The actual data is generalized using nonparametric methods. The Statistica package and the ported ALGLIB MQL5 numerical analysis library are used for processing data.

Tips from a professional programmer (Part III): Logging. Connecting to the Seq log collection and analysis system
Implementation of the Logger class for unifying and structuring messages which are printed to the Experts log. Connection to the Seq log collection and analysis system. Monitoring log messages online.

Developing a Replay System — Market simulation (Part 06): First improvements (I)
In this article, we will begin to stabilize the entire system, without which we might not be able to proceed to the next steps.

Population optimization algorithms: Gravitational Search Algorithm (GSA)
GSA is a population optimization algorithm inspired by inanimate nature. Thanks to Newton's law of gravity implemented in the algorithm, the high reliability of modeling the interaction of physical bodies allows us to observe the enchanting dance of planetary systems and galactic clusters. In this article, I will consider one of the most interesting and original optimization algorithms. The simulator of the space objects movement is provided as well.

Timeseries in DoEasy library (part 53): Abstract base indicator class
The article considers creation of an abstract indicator which further will be used as the base class to create objects of library’s standard and custom indicators.


MQL5 Market Results for Q1 2013
Since its founding, the store of trading robots and technical indicators MQL5 Market has already attracted more than 250 developers who have published 580 products. The first quarter of 2013 has turned out to be quite successful for some MQL5 Market sellers who have managed to make handsome profit by selling their products.

Data Science and Machine Learning (Part 13): Improve your financial market analysis with Principal Component Analysis (PCA)
Revolutionize your financial market analysis with Principal Component Analysis (PCA)! Discover how this powerful technique can unlock hidden patterns in your data, uncover latent market trends, and optimize your investment strategies. In this article, we explore how PCA can provide a new lens for analyzing complex financial data, revealing insights that would be missed by traditional approaches. Find out how applying PCA to financial market data can give you a competitive edge and help you stay ahead of the curve


MQL5 Market Turns One Year Old
One year has passed since the launch of sales in MQL5 Market. It was a year of hard work, which turned the new service into the largest store of trading robots and technical indicators for MetaTrader 5 platform.

Data Science and Machine Learning (Part 21): Unlocking Neural Networks, Optimization algorithms demystified
Dive into the heart of neural networks as we demystify the optimization algorithms used inside the neural network. In this article, discover the key techniques that unlock the full potential of neural networks, propelling your models to new heights of accuracy and efficiency.

Population optimization algorithms: Fish School Search (FSS)
Fish School Search (FSS) is a new optimization algorithm inspired by the behavior of fish in a school, most of which (up to 80%) swim in an organized community of relatives. It has been proven that fish aggregations play an important role in the efficiency of foraging and protection from predators.


Who Is Who in MQL5.community?
The MQL5.com website remembers all of you quite well! How many of your threads are epic, how popular your articles are and how often your programs in the Code Base are downloaded – this is only a small part of what is remembered at MQL5.com. Your achievements are available in your profile, but what about the overall picture? In this article we will show the general picture of all MQL5.community members achievements.

Implementing the Janus factor in MQL5
Gary Anderson developed a method of market analysis based on a theory he dubbed the Janus Factor. The theory describes a set of indicators that can be used to reveal trends and assess market risk. In this article we will implement these tools in mql5.

Developing a robot in Python and MQL5 (Part 1): Data preprocessing
Developing a trading robot based on machine learning: A detailed guide. The first article in the series deals with collecting and preparing data and features. The project is implemented using the Python programming language and libraries, as well as the MetaTrader 5 platform.

MQL5 Wizard Techniques you should know (Part 09): Pairing K-Means Clustering with Fractal Waves
K-Means clustering takes the approach to grouping data points as a process that’s initially focused on the macro view of a data set that uses random generated cluster centroids before zooming in and adjusting these centroids to accurately represent the data set. We will look at this and exploit a few of its use cases.

Developing a Replay System — Market simulation (Part 20): FOREX (I)
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.

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 a trading Expert Advisor from scratch (Part 17): Accessing data on the web (III)
In this article we continue considering how to obtain data from the web and to use it in an Expert Advisor. This time we will proceed to developing an alternative system.

Filtering and feature extraction in the frequency domain
In this article we explore the application of digital filters on time series represented in the frequency domain so as to extract unique features that may be useful to prediction models.

Neural networks made easy (Part 18): Association rules
As a continuation of this series of articles, let's consider another type of problems within unsupervised learning methods: mining association rules. This problem type was first used in retail, namely supermarkets, to analyze market baskets. In this article, we will talk about the applicability of such algorithms in trading.

Developing a Replay System — Market simulation (Part 04): adjusting the settings (II)
Let's continue creating the system and controls. Without the ability to control the service, it is difficult to move forward and improve the system.