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
Library for easy and quick development of MetaTrader programs (part II). Collection of historical orders and deals
Library for easy and quick development of MetaTrader programs (part II). Collection of historical orders and deals

Library for easy and quick development of MetaTrader programs (part II). Collection of historical orders and deals

In the first part, we started creating a large cross-platform library simplifying the development of programs for MetaTrader 5 and MetaTrader 4 platforms. We created the COrder abstract object which is a base object for storing data on history orders and deals, as well as on market orders and positions. Now we will develop all the necessary objects for storing account history data in collections.
Timeseries in DoEasy library (part 35): Bar object and symbol timeseries list
Timeseries in DoEasy library (part 35): Bar object and symbol timeseries list

Timeseries in DoEasy library (part 35): Bar object and symbol timeseries list

This article starts a new series about the creation of the DoEasy library for easy and fast program development. In the current article, we will implement the library functionality for accessing and working with symbol timeseries data. We are going to create the Bar object storing the main and extended timeseries bar data, and place bar objects to the timeseries list for convenient search and sorting of the objects.
Prices and Signals in DoEasy library (Part 65): Depth of Market collection and the class for working with MQL5.com Signals
Prices and Signals in DoEasy library (Part 65): Depth of Market collection and the class for working with MQL5.com Signals

Prices and Signals in DoEasy library (Part 65): Depth of Market collection and the class for working with MQL5.com Signals

In this article, I will create the collection class of Depths of Market of all symbols and start developing the functionality for working with the MQL5.com Signals service by creating the signal object class.
MQL5-RPC. Remote Procedure Calls from MQL5: Web Service Access and XML-RPC ATC Analyzer for Fun and Profit
MQL5-RPC. Remote Procedure Calls from MQL5: Web Service Access and XML-RPC ATC Analyzer for Fun and Profit

MQL5-RPC. Remote Procedure Calls from MQL5: Web Service Access and XML-RPC ATC Analyzer for Fun and Profit

This article describes MQL5-RPC framework that enables Remote Procedure Calls from MQL5. It starts with XML-RPC basics, MQL5 implementation and follows with two real usage examples. First example is using external web service and the second one is a client to simple XML-RPC ATC 2011 Analyzer service. If you are interested on how to implement and analyze different statistics from ATC 2011 in real time, this article is just for you.
MetaTrader 4 and MetaTrader 5 Trading Signals Widgets
MetaTrader 4 and MetaTrader 5 Trading Signals Widgets

MetaTrader 4 and MetaTrader 5 Trading Signals Widgets

Recently MetaTrader 4 and MetaTrader 5 user received an opportunity to become a Signals Provider and earn additional profit. Now, you can display your trading success on your web site, blog or social network page using the new widgets. The benefits of using widgets are obvious: they increase the Signals Providers' popularity, establish their reputation as successful traders, as well as attract new Subscribers. All traders placing widgets on other web sites can enjoy these benefits.
MQL5 Cookbook: Saving Optimization Results of an Expert Advisor Based on Specified Criteria
MQL5 Cookbook: Saving Optimization Results of an Expert Advisor Based on Specified Criteria

MQL5 Cookbook: Saving Optimization Results of an Expert Advisor Based on Specified Criteria

We continue the series of articles on MQL5 programming. This time we will see how to get results of each optimization pass right during the Expert Advisor parameter optimization. The implementation will be done so as to ensure that if the conditions specified in the external parameters are met, the corresponding pass values will be written to a file. In addition to test values, we will also save the parameters that brought about such results.
Combination scalping: analyzing trades from the past to increase the performance of future trades
Combination scalping: analyzing trades from the past to increase the performance of future trades

Combination scalping: analyzing trades from the past to increase the performance of future trades

The article provides the description of the technology aimed at increasing the effectiveness of any automated trading system. It provides a brief explanation of the idea, as well as its underlying basics, possibilities and disadvantages.
preview
Finding seasonal patterns in the forex market using the CatBoost algorithm

Finding seasonal patterns in the forex market using the CatBoost algorithm

The article considers the creation of machine learning models with time filters and discusses the effectiveness of this approach. The human factor can be eliminated now by simply instructing the model to trade at a certain hour of a certain day of the week. Pattern search can be provided by a separate algorithm.
Fundamentals of Statistics
Fundamentals of Statistics

Fundamentals of Statistics

Every trader works using certain statistical calculations, even if being a supporter of fundamental analysis. This article walks you through the fundamentals of statistics, its basic elements and shows the importance of statistics in decision making.
Tips for Selecting a Trading Signal to Subscribe. Step-By-Step Guide
Tips for Selecting a Trading Signal to Subscribe. Step-By-Step Guide

Tips for Selecting a Trading Signal to Subscribe. Step-By-Step Guide

This step-by-step guide is dedicated to the Signals service, examination of trading signals, a system approach to the search of a required signal which would satisfy criteria of profitability, risk, trading ambitions, working on various types of accounts and financial instruments.
preview
Multilayer perceptron and backpropagation algorithm (Part II): Implementation in Python and integration with MQL5

Multilayer perceptron and backpropagation algorithm (Part II): Implementation in Python and integration with MQL5

There is a Python package available for developing integrations with MQL, which enables a plethora of opportunities such as data exploration, creation and use of machine learning models. The built in Python integration in MQL5 enables the creation of various solutions, from simple linear regression to deep learning models. Let's take a look at how to set up and prepare a development environment and how to use use some of the machine learning libraries.
Neural Networks Cheap and Cheerful - Link NeuroPro with MetaTrader 5
Neural Networks Cheap and Cheerful - Link NeuroPro with MetaTrader 5

Neural Networks Cheap and Cheerful - Link NeuroPro with MetaTrader 5

If specific neural network programs for trading seem expensive and complex or, on the contrary, too simple, try NeuroPro. It is free and contains the optimal set of functionalities for amateurs. This article will tell you how to use it in conjunction with MetaTrader 5.
Sorting methods and their visualization using MQL5
Sorting methods and their visualization using MQL5

Sorting methods and their visualization using MQL5

The Graphic.mqh library has been designed to work with graphics in MQL5. The article provides an example of its practical application and explains the idea of sorting. The general concept of sorting is described here since each type of sorting already has at least one separate article, while some of sorting types are objects of detailed studies.
Developing the symbol selection and navigation utility in MQL5 and MQL4
Developing the symbol selection and navigation utility in MQL5 and MQL4

Developing the symbol selection and navigation utility in MQL5 and MQL4

Experienced traders are well aware of the fact that most time-consuming things in trading are not opening and tracking positions but selecting symbols and looking for entry points. In this article, we will develop an EA simplifying the search for entry points on trading instruments provided by your broker.
Selection and navigation utility in MQL5 and MQL4: Adding auto search for patterns and displaying detected symbols
Selection and navigation utility in MQL5 and MQL4: Adding auto search for patterns and displaying detected symbols

Selection and navigation utility in MQL5 and MQL4: Adding auto search for patterns and displaying detected symbols

In this article, we continue expanding the features of the utility for collecting and navigating through symbols. This time, we will create new tabs displaying only the symbols that satisfy some of the necessary parameters and find out how to easily add custom tabs with the necessary sorting rules.
What is a trend and is the market structure based on trend or flat?
What is a trend and is the market structure based on trend or flat?

What is a trend and is the market structure based on trend or flat?

Traders often talk about trends and flats but very few of them really understand what a trend/flat really is and even fewer are able to clearly explain these concepts. Discussing these basic terms is often beset by a solid set of prejudices and misconceptions. However, if we want to make profit, we need to understand the mathematical and logical meaning of these concepts. In this article, I will take a closer look at the essence of trend and flat, as well as try to define whether the market structure is based on trend, flat or something else. I will also consider the most optimal strategies for making profit on trend and flat markets.
Deep Neural Networks (Part II). Working out and selecting predictors
Deep Neural Networks (Part II). Working out and selecting predictors

Deep Neural Networks (Part II). Working out and selecting predictors

The second article of the series about deep neural networks will consider the transformation and choice of predictors during the process of preparing data for training a model.
Analysis of the Main Characteristics of Time Series
Analysis of the Main Characteristics of Time Series

Analysis of the Main Characteristics of Time Series

This article introduces a class designed to give a quick preliminary estimate of characteristics of various time series. As this takes place, statistical parameters and autocorrelation function are estimated, a spectral estimation of time series is carried out and a histogram is built.
Social Trading. Can a profitable signal be made even better?
Social Trading. Can a profitable signal be made even better?

Social Trading. Can a profitable signal be made even better?

Most subscribers choose a trade signal by the beauty of the balance curve and by the number of subscribers. This is why many today's providers care of beautiful statistics rather than of real signal quality, often playing with lot sizes and artificially reducing the balance curve to an ideal appearance. This paper deals with the reliability criteria and the methods a provider may use to enhance its signal quality. An exemplary analysis of a specific signal history is presented, as well as methods that would help a provider to make it more profitable and less risky.
preview
Neural networks made easy (Part 2): Network training and testing

Neural networks made easy (Part 2): Network training and testing

In this second article, we will continue to study neural networks and will consider an example of using our created CNet class in Expert Advisors. We will work with two neural network models, which show similar results both in terms of training time and prediction accuracy.
Naive Bayes classifier for signals of a set of indicators
Naive Bayes classifier for signals of a set of indicators

Naive Bayes classifier for signals of a set of indicators

The article analyzes the application of the Bayes' formula for increasing the reliability of trading systems by means of using signals from multiple independent indicators. Theoretical calculations are verified with a simple universal EA, configured to work with arbitrary indicators.
preview
OpenAI's ChatGPT features within the framework of MQL4 and MQL5 development

OpenAI's ChatGPT features within the framework of MQL4 and MQL5 development

In this article, we will fiddle around ChatGPT from OpenAI in order to understand its capabilities in terms of reducing the time and labor intensity of developing Expert Advisors, indicators and scripts. I will quickly navigate you through this technology and try to show you how to use it correctly for programming in MQL4 and MQL5.
Bi-Directional Trading and Hedging of Positions in MetaTrader 5 Using the HedgeTerminal API, Part 2
Bi-Directional Trading and Hedging of Positions in MetaTrader 5 Using the HedgeTerminal API, Part 2

Bi-Directional Trading and Hedging of Positions in MetaTrader 5 Using the HedgeTerminal API, Part 2

This article describes a new approach to hedging of positions and draws the line in the debates between users of MetaTrader 4 and MetaTrader 5 about this matter. It is a continuation of the first part: "Bi-Directional Trading and Hedging of Positions in MetaTrader 5 Using the HedgeTerminal Panel, Part 1". In the second part, we discuss integration of custom Expert Advisors with HedgeTerminalAPI, which is a special visualization library designed for bi-directional trading in a comfortable software environment providing tools for convenient position management.
Risk Evaluation in the Sequence of Deals with One Asset
Risk Evaluation in the Sequence of Deals with One Asset

Risk Evaluation in the Sequence of Deals with One Asset

This article describes the use of methods of the theory of probability and mathematical statistics in the analysis of trading systems.
preview
Neural networks made easy (Part 10): Multi-Head Attention

Neural networks made easy (Part 10): Multi-Head Attention

We have previously considered the mechanism of self-attention in neural networks. In practice, modern neural network architectures use several parallel self-attention threads to find various dependencies between the elements of a sequence. Let us consider the implementation of such an approach and evaluate its impact on the overall network performance.
preview
An Analysis of Why Expert Advisors Fail

An Analysis of Why Expert Advisors Fail

This article presents an analysis of currency data to better understand why expert advisors can have good performance in some regions of time and poor performance in other regions of time.
preview
The correct way to choose an Expert Advisor from the Market

The correct way to choose an Expert Advisor from the Market

In this article, we will consider some of the essential points you should pay attention to when purchasing an Expert Advisor. We will also look for ways to increase profit, to spend money wisely, and to earn from this spending. Also, after reading the article, you will see that it is possible to earn even using simple and free products.
Statistical Carry Trade Strategy
Statistical Carry Trade Strategy

Statistical Carry Trade Strategy

An algorithm of statistical protection of open positive swap positions from unwanted price movements. This article features a variant of the carry trade protection strategy that allows to compensate for potential risk of the price movement in the direction opposite to that of the open position.
preview
Neural networks made easy (Part 11): A take on GPT

Neural networks made easy (Part 11): A take on GPT

Perhaps one of the most advanced models among currently existing language neural networks is GPT-3, the maximal variant of which contains 175 billion parameters. Of course, we are not going to create such a monster on our home PCs. However, we can view which architectural solutions can be used in our work and how we can benefit from them.
Universal Regression Model for Market Price Prediction
Universal Regression Model for Market Price Prediction

Universal Regression Model for Market Price Prediction

The market price is formed out of a stable balance between demand and supply which, in turn, depend on a variety of economic, political and psychological factors. Differences in nature as well as causes of influence of these factors make it difficult to directly consider all the components. This article sets forth an attempt to predict the market price on the basis of an elaborated regression model.
Library for easy and quick development of MetaTrader programs (part XVI): Symbol collection events
Library for easy and quick development of MetaTrader programs (part XVI): Symbol collection events

Library for easy and quick development of MetaTrader programs (part XVI): Symbol collection events

In this article, we will create a new base class of all library objects adding the event functionality to all its descendants and develop the class for tracking symbol collection events based on the new base class. We will also change account and account event classes for developing the new base object functionality.
Applying OLAP in trading (part 2): Visualizing the interactive multidimensional data analysis results
Applying OLAP in trading (part 2): Visualizing the interactive multidimensional data analysis results

Applying OLAP in trading (part 2): Visualizing the interactive multidimensional data analysis results

In this article, we consider the creation of an interactive graphical interface for an MQL program, which is designed for the processing of account history and trading reports using OLAP techniques. To obtain a visual result, we will use maximizable and scalable windows, an adaptive layout of rubber controls and a new control for displaying diagrams. To provide the visualization functionality, we will implement a GUI with the selection of variables along coordinate axes, as well as with the selection of aggregate functions, diagram types and sorting options.
preview
Data Science and Machine Learning — Neural Network (Part 02): Feed forward NN Architectures Design

Data Science and Machine Learning — Neural Network (Part 02): Feed forward NN Architectures Design

There are minor things to cover on the feed-forward neural network before we are through, the design being one of them. Let's see how we can build and design a flexible neural network to our inputs, the number of hidden layers, and the nodes for each of the network.
preview
Data Science and Machine Learning (Part 01): Linear Regression

Data Science and Machine Learning (Part 01): Linear Regression

It's time for us as traders to train our systems and ourselves to make decisions based on what number says. Not on our eyes, and what our guts make us believe, this is where the world is heading so, let us move perpendicular to the direction of the wave.
Combinatorics and probability theory for trading (Part III): The first mathematical model
Combinatorics and probability theory for trading (Part III): The first mathematical model

Combinatorics and probability theory for trading (Part III): The first mathematical model

A logical continuation of the earlier discussed topic would be the development of multifunctional mathematical models for trading tasks. In this article, I will describe the entire process related to the development of the first mathematical model describing fractals, from scratch. This model should become an important building block and be multifunctional and universal. It will build up our theoretical basis for further development of this idea.
preview
Risk and capital management using Expert Advisors

Risk and capital management using Expert Advisors

This article is about what you can not see in a backtest report, what you should expect using automated trading software, how to manage your money if you are using expert advisors, and how to cover a significant loss to remain in the trading activity when you are using automated procedures.
Visualizing trading strategy optimization in MetaTrader 5
Visualizing trading strategy optimization in MetaTrader 5

Visualizing trading strategy optimization in MetaTrader 5

The article implements an MQL application with a graphical interface for extended visualization of the optimization process. The graphical interface applies the last version of EasyAndFast library. Many users may ask why they need graphical interfaces in MQL applications. This article demonstrates one of multiple cases where they can be useful for traders.
MQL Parsing by Means of MQL
MQL Parsing by Means of MQL

MQL Parsing by Means of MQL

The article describes a preprocessor, a scanner, and a parser to be used in parsing the MQL-based source codes. MQL implementation is attached.
Library for easy and quick development of MetaTrader programs (part X): Compatibility with MQL4 - Events of opening a position and activating pending orders
Library for easy and quick development of MetaTrader programs (part X): Compatibility with MQL4 - Events of opening a position and activating pending orders

Library for easy and quick development of MetaTrader programs (part X): Compatibility with MQL4 - Events of opening a position and activating pending orders

In the previous articles, we started creating a large cross-platform library simplifying the development of programs for MetaTrader 5 and MetaTrader 4 platforms. In the ninth part, we started improving the library classes for working with MQL4. Here we will continue improving the library to ensure its full compatibility with MQL4.
preview
Neural networks made easy (Part 8): Attention mechanisms

Neural networks made easy (Part 8): Attention mechanisms

In previous articles, we have already tested various options for organizing neural networks. We also considered convolutional networks borrowed from image processing algorithms. In this article, I suggest considering Attention Mechanisms, the appearance of which gave impetus to the development of language models.