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
Forex Arbitrage Trading: Relationship Assessment Panel

Forex Arbitrage Trading: Relationship Assessment Panel

This article presents the development of an arbitrage analysis panel in MQL5. How to get fair exchange rates on Forex in different ways? Create an indicator to obtain deviations of market prices from fair exchange rates, as well as to assess the benefits of arbitrage ways of exchanging one currency for another (as in triangular arbitrage).
preview
Market Simulation (Part 16): Sockets (X)

Market Simulation (Part 16): Sockets (X)

We are close to completing this challenge. However, before we begin, I want you to try to understand these two articles—this one and the previous one. That way, you will truly understand the next article, in which I will cover exclusively the part related to MQL5 programming. But I will also try to make it understandable. If you do not understand these last two articles, it will be difficult for you to understand the next one, because the material accumulates. The more things there are to do, the more you need to create and understand in order to achieve the goal.
preview
Creating Custom Indicators in MQL5 (Part 7): Hybrid Time Price Opportunity (TPO) Market Profiles for Session Analysis

Creating Custom Indicators in MQL5 (Part 7): Hybrid Time Price Opportunity (TPO) Market Profiles for Session Analysis

In this article, we develop a custom indicator in MQL5 for hybrid Time Price Opportunity (TPO) market profiles, supporting multiple session timeframes such as intraday, daily, weekly, monthly, and fixed periods with timezone adjustments. The indicator quantizes prices into a grid, tracks session data including highs, lows, opens, and closes, and calculates key elements like the point of control and value area based on TPO counts. It renders profiles visually on the chart with customizable colors for TPO letters, single prints, value areas, POC, and close markers, enabling detailed session analysis
preview
Causal analysis of time series using transfer entropy

Causal analysis of time series using transfer entropy

In this article, we discuss how statistical causality can be applied to identify predictive variables. We will explore the link between causality and transfer entropy, as well as present MQL5 code for detecting directional transfers of information between two variables.
preview
Developing a Replay System (Part 46): Chart Trade Project (V)

Developing a Replay System (Part 46): Chart Trade Project (V)

Tired of wasting time searching for that very file that you application needs in order to work? How about including everything in the executable? This way you won't have to search for the things. I know that many people use this form of distribution and storage, but there is a much more suitable way. At least as far as the distribution of executable files and their storage is concerned. The method that will be presented here can be very useful, since you can use MetaTrader 5 itself as an excellent assistant, as well as MQL5. Furthermore, it is not that difficult to understand.
preview
Market Simulation (Part 04): Creating the C_Orders Class (I)

Market Simulation (Part 04): Creating the C_Orders Class (I)

In this article, we will start creating the C_Orders class to be able to send orders to the trading server. We'll do this little by little, as our goal is to explain in detail how this will happen through the messaging system.
preview
Capital management in trading and the trader's home accounting program with a database

Capital management in trading and the trader's home accounting program with a database

How can a trader manage capital? How can a trader and investor keep track of expenses, income, assets, and liabilities? I am not just going to introduce you to accounting software; I am going to show you a tool that might become your reliable financial navigator in the stormy sea of trading.
preview
Developing a Replay System (Part 43): Chart Trade Project (II)

Developing a Replay System (Part 43): Chart Trade Project (II)

Most people who want or dream of learning to program don't actually have a clue what they're doing. Their activity consists of trying to create things in a certain way. However, programming is not about tailoring suitable solutions. Doing it this way can create more problems than solutions. Here we will be doing something more advanced and therefore different.
preview
Developing a Replay System (Part 40): Starting the second phase (I)

Developing a Replay System (Part 40): Starting the second phase (I)

Today we'll talk about the new phase of the replay/simulator system. At this stage, the conversation will become truly interesting and quite rich in content. I strongly recommend that you read the article carefully and use the links provided in it. This will help you understand the content better.
preview
Successful Restaurateur Algorithm (SRA)

Successful Restaurateur Algorithm (SRA)

Successful Restaurateur Algorithm (SRA) is an innovative optimization method inspired by restaurant business management principles. Unlike traditional approaches, SRA does not discard weak solutions, but improves them by combining with elements of successful ones. The algorithm shows competitive results and offers a fresh perspective on balancing exploration and exploitation in optimization problems.
preview
Developing a Replay System (Part 29): Expert Advisor project — C_Mouse class (III)

Developing a Replay System (Part 29): Expert Advisor project — C_Mouse class (III)

After improving the C_Mouse class, we can focus on creating a class designed to create a completely new framework fr our analysis. We will not use inheritance or polymorphism to create this new class. Instead, we will change, or better said, add new objects to the price line. That's what we will do in this article. In the next one, we will look at how to change the analysis. All this will be done without changing the code of the C_Mouse class. Well, actually, it would be easier to achieve this using inheritance or polymorphism. However, there are other methods to achieve the same result.
preview
Population optimization algorithms: Spiral Dynamics Optimization (SDO) algorithm

Population optimization algorithms: Spiral Dynamics Optimization (SDO) algorithm

The article presents an optimization algorithm based on the patterns of constructing spiral trajectories in nature, such as mollusk shells - the spiral dynamics optimization (SDO) algorithm. I have thoroughly revised and modified the algorithm proposed by the authors. The article will consider the necessity of these changes.
preview
Forecasting exchange rates using classic machine learning methods: Logit and Probit models

Forecasting exchange rates using classic machine learning methods: Logit and Probit models

In the article, an attempt is made to build a trading EA for predicting exchange rate quotes. The algorithm is based on classical classification models - logistic and probit regression. The likelihood ratio criterion is used as a filter for trading signals.
preview
From Novice to Expert: Market Periods Synchronizer

From Novice to Expert: Market Periods Synchronizer

In this discussion, we introduce a Higher-to-Lower Timeframe Synchronizer tool designed to solve the problem of analyzing market patterns that span across higher timeframe periods. The built-in period markers in MetaTrader 5 are often limited, rigid, and not easily customizable for non-standard timeframes. Our solution leverages the MQL5 language to develop an indicator that provides a dynamic and visual way to align higher timeframe structures within lower timeframe charts. This tool can be highly valuable for detailed market analysis. To learn more about its features and implementation, I invite you to join the discussion.
preview
Ensemble methods to enhance numerical predictions in MQL5

Ensemble methods to enhance numerical predictions in MQL5

In this article, we present the implementation of several ensemble learning methods in MQL5 and examine their effectiveness across different scenarios.
preview
Creating a Trading Administrator Panel in MQL5 (Part X): External resource-based interface

Creating a Trading Administrator Panel in MQL5 (Part X): External resource-based interface

Today, we are harnessing the capabilities of MQL5 to utilize external resources—such as images in the BMP format—to create a uniquely styled home interface for the Trading Administrator Panel. The strategy demonstrated here is particularly useful when packaging multiple resources, including images, sounds, and more, for streamlined distribution. Join us in this discussion as we explore how these features are implemented to deliver a modern and visually appealing interface for our New_Admin_Panel EA.
preview
Economic forecasts: Exploring the Python potential

Economic forecasts: Exploring the Python potential

How to use World Bank economic data for forecasts? What happens when you combine AI models and economics?
preview
Animal Migration Optimization (AMO) algorithm

Animal Migration Optimization (AMO) algorithm

The article is devoted to the AMO algorithm, which models the seasonal migration of animals in search of optimal conditions for life and reproduction. The main features of AMO include the use of topological neighborhood and a probabilistic update mechanism, which makes it easy to implement and flexible for various optimization tasks.
preview
Developing a Replay System (Part 67): Refining the Control Indicator

Developing a Replay System (Part 67): Refining the Control Indicator

In this article, we'll look at what can be achieved with a little code refinement. This refinement is aimed at simplifying our code, making more use of MQL5 library calls and, above all, making it much more stable, secure and easy to use in other projects that we may develop in the future.
preview
MQL5 Trading Tools (Part 24): Depth-Perception Upgrades with 3D Curves, Pan Mode, and ViewCube Navigation

MQL5 Trading Tools (Part 24): Depth-Perception Upgrades with 3D Curves, Pan Mode, and ViewCube Navigation

In this article, we enhance the 3D binomial distribution graphing tool in MQL5 by adding a segmented 3D curve for improved depth perception of the probability mass function, integrating pan mode for view target shifting, and implementing an interactive view cube with hover zones and animations for quick orientation changes. We incorporate clickable sub-zones on the view cube for faces, edges, and corners to animate camera transitions to standard views, while maintaining switchable 2D/3D modes, real-time updates, and customizable parameters for immersive probabilistic analysis in trading.
preview
Biological neuron for forecasting financial time series

Biological neuron for forecasting financial time series

We will build a biologically correct system of neurons for time series forecasting. The introduction of a plasma-like environment into the neural network architecture creates a kind of "collective intelligence," where each neuron influences the system's operation not only through direct connections, but also through long-range electromagnetic interactions. Let's see how the neural brain modeling system will perform in the market.
preview
Most notable Artificial Cooperative Search algorithm modifications (ACSm)

Most notable Artificial Cooperative Search algorithm modifications (ACSm)

Here we will consider the evolution of the ACS algorithm: three modifications aimed at improving the convergence characteristics and the algorithm efficiency. Transformation of one of the leading optimization algorithms. From matrix modifications to revolutionary approaches regarding population formation.
preview
Spurious Regressions in Python

Spurious Regressions in Python

Spurious regressions occur when two time series exhibit a high degree of correlation purely by chance, leading to misleading results in regression analysis. In such cases, even though variables may appear to be related, the correlation is coincidental and the model may be unreliable.
preview
Developing a Replay System (Part 33): Order System (II)

Developing a Replay System (Part 33): Order System (II)

Today we will continue to develop the order system. As you will see, we will be massively reusing what has already been shown in other articles. Nevertheless, you will receive a small reward in this article. First, we will develop a system that can be used with a real trading server, both from a demo account or from a real one. We will make extensive use of the MetaTrader 5 platform, which will provide us with all the necessary support from the beginning.
preview
Developing a Replay System (Part 69): Getting the Time Right (II)

Developing a Replay System (Part 69): Getting the Time Right (II)

Today we will look at why we need the iSpread feature. At the same time, we will understand how the system informs us about the remaining time of the bar when there is not a single tick available for it. The content presented here is intended solely for educational purposes. Under no circumstances should the application be viewed for any purpose other than to learn and master the concepts presented.
preview
Chemical reaction optimization (CRO) algorithm (Part I): Process chemistry in optimization

Chemical reaction optimization (CRO) algorithm (Part I): Process chemistry in optimization

In the first part of this article, we will dive into the world of chemical reactions and discover a new approach to optimization! Chemical reaction optimization (CRO) uses principles derived from the laws of thermodynamics to achieve efficient results. We will reveal the secrets of decomposition, synthesis and other chemical processes that became the basis of this innovative method.
preview
Anarchic Society Optimization (ASO) algorithm

Anarchic Society Optimization (ASO) algorithm

In this article, we will get acquainted with the Anarchic Society Optimization (ASO) algorithm and discuss how an algorithm based on the irrational and adventurous behavior of participants in an anarchic society (an anomalous system of social interaction free from centralized power and various kinds of hierarchies) is able to explore the solution space and avoid the traps of local optimum. The article presents a unified ASO structure applicable to both continuous and discrete problems.
preview
Integrating MQL5 with data processing packages (Part 3): Enhanced Data Visualization

Integrating MQL5 with data processing packages (Part 3): Enhanced Data Visualization

In this article, we will perform Enhanced Data Visualization by going beyond basic charts by incorporating features like interactivity, layered data, and dynamic elements, enabling traders to explore trends, patterns, and correlations more effectively.
preview
An introduction to Receiver Operating Characteristic curves

An introduction to Receiver Operating Characteristic curves

ROC curves are graphical representations used to evaluate the performance of classifiers. Despite ROC graphs being relatively straightforward, there exist common misconceptions and pitfalls when using them in practice. This article aims to provide an introduction to ROC graphs as a tool for practitioners seeking to understand classifier performance evaluation.
preview
Causal inference in time series classification problems

Causal inference in time series classification problems

In this article, we will look at the theory of causal inference using machine learning, as well as the custom approach implementation in Python. Causal inference and causal thinking have their roots in philosophy and psychology and play an important role in our understanding of reality.
preview
Ordinal Encoding for Nominal Variables

Ordinal Encoding for Nominal Variables

In this article, we discuss and demonstrate how to convert nominal predictors into numerical formats that are suitable for machine learning algorithms, using both Python and MQL5.
preview
MQL5 Wizard Techniques you should know (Part 52): Accelerator Oscillator

MQL5 Wizard Techniques you should know (Part 52): Accelerator Oscillator

The Accelerator Oscillator is another Bill Williams Indicator that tracks price momentum's acceleration and not just its pace. Although much like the Awesome oscillator we reviewed in a recent article, it seeks to avoid the lagging effects by focusing more on acceleration as opposed to just speed. We examine as always what patterns we can get from this and also what significance each could have in trading via a wizard assembled Expert Advisor.
preview
Integrating MQL5 with Data Processing Packages (Part 6): Merging Market Feedback with Model Adaptation

Integrating MQL5 with Data Processing Packages (Part 6): Merging Market Feedback with Model Adaptation

In this part, we focus on how to merge real-time market feedback—such as live trade outcomes, volatility changes, and liquidity shifts—with adaptive model learning to maintain a responsive and self-improving trading system.
preview
Python-MetaTrader 5 Strategy Tester (Part 05): Multi-Symbols and Timeframes Strategy Tester

Python-MetaTrader 5 Strategy Tester (Part 05): Multi-Symbols and Timeframes Strategy Tester

This article presents a MetaTrader 5–compatible backtesting workflow that scales across symbols and timeframes. We use HistoryManager to parallelize data collection, synchronize bars and ticks from all timeframes, and run symbol‑isolated OnTick handlers in threads. You will learn how modelling modes affect speed/accuracy, when to rely on terminal data, how to reduce I/O with event‑driven updates, and how to assemble a complete multicurrency trading robot.
preview
Category Theory in MQL5 (Part 12): Orders

Category Theory in MQL5 (Part 12): Orders

This article which is part of a series that follows Category Theory implementation of Graphs in MQL5, delves in Orders. We examine how concepts of Order-Theory can support monoid sets in informing trade decisions by considering two major ordering types.
preview
Hybridization of population algorithms. Sequential and parallel structures

Hybridization of population algorithms. Sequential and parallel structures

Here we will dive into the world of hybridization of optimization algorithms by looking at three key types: strategy mixing, sequential and parallel hybridization. We will conduct a series of experiments combining and testing relevant optimization algorithms.
preview
Data Science and ML (Part 44): Forex OHLC Time series Forecasting using Vector Autoregression (VAR)

Data Science and ML (Part 44): Forex OHLC Time series Forecasting using Vector Autoregression (VAR)

Explore how Vector Autoregression (VAR) models can forecast Forex OHLC (Open, High, Low, and Close) time series data. This article covers VAR implementation, model training, and real-time forecasting in MetaTrader 5, helping traders analyze interdependent currency movements and improve their trading strategies.
preview
Python-MetaTrader 5 Strategy Tester (Part 02): Dealing with Bars, Ticks, and Overloading Built-in Functions in a Simulator

Python-MetaTrader 5 Strategy Tester (Part 02): Dealing with Bars, Ticks, and Overloading Built-in Functions in a Simulator

In this article, we introduce functions similar to those provided by the Python-MetaTrader 5 module, providing a simulator with a familiar interface and a custom way of handling bars and ticks internally.
preview
Creating Custom Indicators in MQL5 (Part 10): Enhancing the Footprint Chart with Per-Bar Volume Sentiment Information Box

Creating Custom Indicators in MQL5 (Part 10): Enhancing the Footprint Chart with Per-Bar Volume Sentiment Information Box

The article enhances an MQL5 footprint indicator with a compact box above each candle that summarizes net delta, total volume, and buy/sell percentages. We implement supersampled anti‑aliased rendering, rounded corners via arc and quadrilateral rasterization, and per‑pixel alpha compositing. Supporting utilities include ARGB conversion, scanline fills, and box‑filter downsampling. The box delivers fast sentiment reads that stay legible across zoom levels.
preview
Market Simulation (Part 02): Cross Orders (II)

Market Simulation (Part 02): Cross Orders (II)

Unlike what was done in the previous article, here we will test the selection option using an Expert Advisor. Although this is not a final solution yet, it will be enough for now. With the help of this article, you will be able to understand how to implement one of the possible solutions.