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.

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Data Science and Machine Learning (Part 05): Decision Trees

Decision trees imitate the way humans think to classify data, let's see how to build a tree and use them to classify and predict some data. The main goal of the decision trees algorithm is to separate

MQL5 Wizard techniques you should know (Part 01): Regression Analysis

Todays trader is a philomath who is almost always (either consciously or not...) looking up new ideas, trying them out, choosing to modify them or discard them; an exploratory process that should cost

Data Science and Machine Learning (Part 04): Predicting Current Stock Market Crash

In this article I am going to attempt to use our logistic model to predict the stock market crash based upon the fundamentals of the US economy, the NETFLIX and APPLE are the stocks we are going to

Data Science and Machine Learning part 03: Matrix Regressions

This time our models are being made by matrices, which allows flexibility while it allows us to make powerful models that can handle not only five independent variables but also many variables as long

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

Data Science and Machine Learning (Part 02): Logistic Regression

Data Classification is a crucial thing for an algo trader and a programmer. In this article, we are going to focus on one of classification logistic algorithms that can probability help us identify

Mathematics in trading: Sharpe and Sortino ratios

Return on investments is the most obvious indicator which investors and novice traders use for the analysis of trading efficiency. Professional traders use more reliable tools to analyze strategies

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

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

Visual evaluation of optimization results

In this article, we will consider how to build graphs of all optimization passes and to select the optimal custom criterion. We will also see how to create a desired solution with little MQL5

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

Combinatorics and probability for trading (Part V): Curve analysis

In this article, I decided to conduct a study related to the possibility of reducing multiple states to double-state systems. The main purpose of the article is to analyze and to come to useful

Combinatorics and probability for trading (Part IV): Bernoulli Logic

In this article, I decided to highlight the well-known Bernoulli scheme and to show how it can be used to describe trading-related data arrays. All this will then be used to create a self-adapting

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

Programming a Deep Neural Network from Scratch using MQL Language

This article aims to teach the reader how to make a Deep Neural Network from scratch using the MQL4/5 language

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

Combinatorics and probability theory for trading (Part II): Universal fractal

In this article, we will continue to study fractals and will pay special attention to summarizing all the material. To do this, I will try to bring all earlier developments into a compact form which

Bid/Ask spread analysis in MetaTrader 5

An indicator to report your brokers Bid/Ask spread levels. Now we can use MT5s tick data to analyze what the historic true average Bid/Ask spread actually have recently been. You shouldn't need to

Combinatorics and probability theory for trading (Part I): The basics

In this series of article, we will try to find a practical application of probability theory to describe trading and pricing processes. In the first article, we will look into the basics of

Patterns with Examples (Part I): Multiple Top

This is the first article in a series related to reversal patterns in the framework of algorithmic trading. We will begin with the most interesting pattern family, which originate from the Double Top

Better Programmer (Part 02): Stop doing these 5 things to become a successful MQL5 programmer

This is the must read article for anyone wanting to improve their programming career. This article series is aimed at making you the best programmer you can possibly be, no matter how experienced you

Cluster analysis (Part I): Mastering the slope of indicator lines

Cluster analysis is one of the most important elements of artificial intelligence. In this article, I attempt applying the cluster analysis of the indicator slope to get threshold values for

Other classes in DoEasy library (Part 72): Tracking and recording chart object parameters in the collection

In this article, I will complete working with chart object classes and their collection. I will also implement auto tracking of changes in chart properties and their windows, as well as saving new

Other classes in DoEasy library (Part 71): Chart object collection events

In this article, I will create the functionality for tracking some chart object events — adding/removing symbol charts and chart subwindows, as well as adding/removing/changing indicators in chart

Other classes in DoEasy library (Part 70): Expanding functionality and auto updating the chart object collection

In this article, I will expand the functionality of chart objects and arrange navigation through charts, creation of screenshots, as well as saving and applying templates to charts. Also, I will

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

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

Other classes in DoEasy library (Part 68): Chart window object class and indicator object classes in the chart window

In this article, I will continue the development of the chart object class. I will add the list of chart window objects featuring the lists of available indicators

Other classes in DoEasy library (Part 66): Signals collection class

In this article, I will create the signal collection class of the Signals service with the functions for managing signals. Besides, I will improve the Depth of Market snapshot object class

Prices and Signals in DoEasy library (Part 65): Depth of Market collection and the class for working with 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 Signals service by creating the signal

Prices in DoEasy library (Part 64): Depth of Market, classes of DOM snapshot and snapshot series objects

In this article, I will create two classes (the class of DOM snapshot object and the class of DOM snapshot series object) and test creation of the DOM data series

Machine learning in Grid and Martingale trading systems. Would you bet on it?

This article describes the machine learning technique applied to grid and martingale trading. Surprisingly, this approach has little to no coverage in the global network. After reading the article

Self-adapting algorithm (Part IV): Additional functionality and tests

I continue filling the algorithm with the minimum necessary functionality and testing the results. The profitability is quite low but the articles demonstrate the model of the fully automated

Prices in DoEasy library (part 63): Depth of Market and its abstract request class

In the article, I will start developing the functionality for working with the Depth of Market. I will also create the class of the Depth of Market abstract order object and its descendants

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

Prices in DoEasy library (part 62): Updating tick series in real time, preparation for working with Depth of Market

In this article, I will implement updating tick data in real time and prepare the symbol object class for working with Depth of Market (DOM itself is to be implemented in the next article)

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

Prices in DoEasy library (part 60): Series list of symbol tick data

In this article, I will create the list for storing tick data of a single symbol and check its creation and retrieval of required data in an EA. Tick data lists that are individual for each used

Self-adapting algorithm (Part III): Abandoning optimization

It is impossible to get a truly stable algorithm if we use optimization based on historical data to select parameters. A stable algorithm should be aware of what parameters are needed when working on

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