Articles on data analysis and statistics in MQL5
Articles on mathematical models and laws of probability are interesting for many traders. Mathematics is the basis of technical indicators, and statistics is required to analyze trading results and develop strategies.
Read about the fuzzy logic, digital filters, market profile, Kohonen maps, neural gas and many other tools that can be used for trading.
Add a new article
You are missing trading opportunities:
- Free trading apps
- Over 8,000 signals for copying
- Economic news for exploring financial markets
Registration
Log in
You agree to website policy and terms of use
If you do not have an account, please register
Brute force approach to patterns search (Part VI): Cyclic optimization
In this article I will show the first part of the improvements that allowed me not only to close the entire automation chain for MetaTrader 4 and 5 trading, but also to do something much more interesting. From now on, this solution allows me to fully automate both creating EAs and optimization, as well as to minimize labor costs for finding effective trading configurations.
Mountain or Iceberg charts
How do you like the idea of adding a new chart type to the MetaTrader 5 platform? Some people say it lacks a few things that other platforms offer. But the truth is, MetaTrader 5 is a very practical platform as it allows you to do things that can't be done (or at least can't be done easily) in many other platforms.
Price Action Analysis Toolkit Development (Part 25): Dual EMA Fractal Breaker
Price action is a fundamental approach for identifying profitable trading setups. However, manually monitoring price movements and patterns can be challenging and time-consuming. To address this, we are developing tools that analyze price action automatically, providing timely signals whenever potential opportunities are detected. This article introduces a robust tool that leverages fractal breakouts alongside EMA 14 and EMA 200 to generate reliable trading signals, helping traders make informed decisions with greater confidence.
Other classes in DoEasy library (Part 69): Chart object collection class
With this article, I start the development of the chart object collection class. The class will store the collection list of chart objects with their subwindows and indicators providing the ability to work with any selected charts and their subwindows or with a list of several charts at once.
Neural networks made easy (Part 19): Association rules using MQL5
We continue considering association rules. In the previous article, we have discussed theoretical aspect of this type of problem. In this article, I will show the implementation of the FP Growth method using MQL5. We will also test the implemented solution using real data.
Timeseries in DoEasy library (part 44): Collection class of indicator buffer objects
The article deals with creating a collection class of indicator buffer objects. I am going to test the ability to create and work with any number of buffers for indicators (the maximum number of buffers that can be created in MQL indicators is 512).
Prices in DoEasy library (part 61): Collection of symbol tick series
Since a program may use different symbols in its work, a separate list should be created for each of them. In this article, I will combine such lists into a tick data collection. In fact, this will be a regular list based on the class of dynamic array of pointers to instances of CObject class and its descendants of the Standard library.
The price movement model and its main provisions. (Part 3): Calculating optimal parameters of stock exchange speculations
Within the framework of the engineering approach developed by the author based on the probability theory, the conditions for opening a profitable position are found and the optimal (profit-maximizing) take profit and stop loss values are calculated.
Monte Carlo Permutation Tests in MetaTrader 5
In this article we take a look at how we can conduct permutation tests based on shuffled tick data on any expert advisor using only Metatrader 5.
Population optimization algorithms: Bacterial Foraging Optimization (BFO)
E. coli bacterium foraging strategy inspired scientists to create the BFO optimization algorithm. The algorithm contains original ideas and promising approaches to optimization and is worthy of further study.
Selection and navigation utility in MQL5 and MQL4: Adding "homework" tabs and saving graphical objects
In this article, we are going to expand the capabilities of the previously created utility by adding tabs for selecting the symbols we need. We will also learn how to save graphical objects we have created on the specific symbol chart, so that we do not have to constantly create them again. Besides, we will find out how to work only with symbols that have been preliminarily selected using a specific website.
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.
Automating Trading Strategies with Parabolic SAR Trend Strategy in MQL5: Crafting an Effective Expert Advisor
In this article, we will automate the trading strategies with Parabolic SAR Strategy in MQL5: Crafting an Effective Expert Advisor. The EA will make trades based on trends identified by the Parabolic SAR indicator.
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.
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 in MQL5 (Part 1)
Category Theory is a diverse and expanding branch of Mathematics which as of yet is relatively uncovered in the MQL community. These series of articles look to introduce and examine some of its concepts with the overall goal of establishing an open library that attracts comments and discussion while hopefully furthering the use of this remarkable field in Traders' strategy development.
Marvel Your MQL5 Customers with a Usable Cocktail of Technologies!
MQL5 provides programmers with a very complete set of functions and object-oriented API thanks to which they can do everything they want within the MetaTrader environment. However, Web Technology is an extremely versatile tool nowadays that may come to the rescue in some situations when you need to do something very specific, want to marvel your customers with something different or simply you do not have enough time to master a specific part of MT5 Standard Library. Today's exercise walks you through a practical example about how you can manage your development time at the same time as you also create an amazing tech cocktail.
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
Forecasting with ARIMA models in MQL5
In this article we continue the development of the CArima class for building ARIMA models by adding intuitive methods that enable forecasting.
Developing a Replay System — Market simulation (Part 02): First experiments (II)
This time, let's try a different approach to achieve the 1 minute goal. However, this task is not as simple as one might think.
Prices in DoEasy library (part 59): Object to store data of one tick
From this article on, start creating library functionality to work with price data. Today, create an object class which will store all price data which arrived with yet another tick.
Data label for time series mining(Part 1)：Make a dataset with trend markers through the EA operation chart
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!
Neural networks made easy (Part 16): Practical use of clustering
In the previous article, we have created a class for data clustering. In this article, I want to share variants of the possible application of obtained results in solving practical trading tasks.
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.
Developing an Expert Advisor from scratch (Part 30): CHART TRADE as an indicator?
Today we are going to use Chart Trade again, but this time it will be an on-chart indicator which may or may not be present on the chart.
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.
Timeseries in DoEasy library (part 54): Descendant classes of abstract base indicator
The article considers creation of classes of descendant objects of base abstract indicator. Such objects will provide access to features of creating indicator EAs, collecting and getting data value statistics of various indicators and prices. Also, create indicator object collection from which getting access to properties and data of each indicator created in the program will be possible.
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.
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?
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.
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.
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.
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.
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.
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.
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.
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.