Articles on data analysis and statistics in MQL5

icon

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
latest | best
preview
Population optimization algorithms: Bacterial Foraging Optimization (BFO)

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
Selection and navigation utility in MQL5 and MQL4: Adding "homework" tabs and saving graphical objects

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.
preview
Modified Grid-Hedge EA in MQL5 (Part I): Making a Simple Hedge EA

Modified Grid-Hedge EA in MQL5 (Part I): Making a Simple Hedge EA

We will be creating a simple hedge EA as a base for our more advanced Grid-Hedge EA, which will be a mixture of classic grid and classic hedge strategies. By the end of this article, you will know how to create a simple hedge strategy, and you will also get to know what people say about whether this strategy is truly 100% profitable.
Marvel Your MQL5 Customers with a Usable Cocktail of Technologies!
Marvel Your MQL5 Customers with a Usable Cocktail of Technologies!

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.
preview
Alan Andrews and his methods of time series analysis

Alan Andrews and his methods of time series analysis

Alan Andrews is one of the most famous "educators" of the modern world in the field of trading. His "pitchfork" is included in almost all modern quote analysis programs. But most traders do not use even a fraction of the opportunities that this tool provides. Besides, Andrews' original training course includes a description not only of the pitchfork (although it remains the main tool), but also of some other useful constructions. The article provides an insight into the marvelous chart analysis methods that Andrews taught in his original course. Beware, there will be a lot of images.
preview
Category Theory in MQL5 (Part 1)

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.
Prices in DoEasy library (part 59): Object to store data of one tick
Prices in DoEasy library (part 59): Object to store data of one tick

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.
preview
Developing a Replay System — Market simulation (Part 02): First experiments (II)

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.
preview
Timeseries in DoEasy library (part 54): Descendant classes of abstract base indicator

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.
preview
Monte Carlo Permutation Tests in MetaTrader 5

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.
preview
Developing an Expert Advisor from scratch (Part 30): CHART TRADE as an indicator?

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.
preview
Data label for time series  mining(Part 1):Make a dataset with trend markers through the EA operation chart

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!
preview
Advanced resampling and selection of CatBoost models by brute-force method

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.
Timeseries in DoEasy library (part 48): Multi-period multi-symbol indicators on one buffer in a subwindow
Timeseries in DoEasy library (part 48): Multi-period multi-symbol indicators on one buffer in a subwindow

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.
preview
The price movement model and its main provisions. (Part 3): Calculating optimal parameters of stock exchange speculations

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.
preview
Brute force approach to patterns search (Part VI): Cyclic optimization

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.
preview
Population optimization algorithms: Harmony Search (HS)

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?
preview
Category Theory (Part 9): Monoid-Actions

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.
preview
Neural networks made easy (Part 15): Data clustering using MQL5

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.
preview
Forecasting with ARIMA models in MQL5

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.
preview
Parallel Particle Swarm Optimization

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.
MQL5 Market Results for Q2 2013
MQL5 Market Results for Q2 2013

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
Timeseries in DoEasy library (part 47): Multi-period multi-symbol standard indicators

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.
preview
Neural networks made easy (Part 21): Variational autoencoders (VAE)

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

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
Trader's Statistical Cookbook: Hypotheses

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.
MQL5 Market Results for Q1 2013
MQL5 Market Results for Q1 2013

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.
preview
Developing a Replay System — Market simulation (Part 06): First improvements (I)

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.
preview
Neural networks made easy (Part 16): Practical use of clustering

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.
preview
Timeseries in DoEasy library (part 53): Abstract base indicator class

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.
preview
Population optimization algorithms: Grey Wolf Optimizer (GWO)

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.
preview
Automating Trading Strategies with Parabolic SAR Trend Strategy in MQL5: Crafting an Effective Expert Advisor

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.
preview
Data Science and Machine Learning (Part 07): Polynomial Regression

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.
MQL5 Market Turns One Year Old
MQL5 Market Turns One Year Old

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.
preview
Tips from a professional programmer (Part III): Logging. Connecting to the Seq log collection and analysis system

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.
preview
Data Science and Machine Learning (Part 06): Gradient Descent

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.
preview
Data Science and Machine Learning (Part 13): Improve your financial market analysis with Principal Component Analysis (PCA)

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
preview
Population optimization algorithms: Gravitational Search Algorithm (GSA)

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.
preview
Neural networks made easy (Part 25): Practicing Transfer Learning

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.
Who Is Who in MQL5.community?
Who Is Who in MQL5.community?

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.