MQL5 Wizard Techniques you should know (Part 33): Gaussian Process Kernels
Gaussian Process Kernels are the covariance function of the Normal Distribution that could play a role in forecasting. We explore this unique algorithm in a custom signal class of MQL5 to see if it could be put to use as a prime entry and exit signal.
Developing a Replay System (Part 52): Things Get Complicated (IV)
In this article, we will change the mouse pointer to enable the interaction with the control indicator to ensure reliable and stable operation.
MQL5 Trading Toolkit (Part 5): Expanding the History Management EX5 Library with Position Functions
Discover how to create exportable EX5 functions to efficiently query and save historical position data. In this step-by-step guide, we will expand the History Management EX5 library by developing modules that retrieve key properties of the most recently closed position. These include net profit, trade duration, pip-based stop loss, take profit, profit values, and various other important details.
Category Theory in MQL5 (Part 11): Graphs
This article is a continuation in a series that look at Category Theory implementation in MQL5. In here we examine how Graph-Theory could be integrated with monoids and other data structures when developing a close-out strategy to a trading system.
Market Simulation (Part 03): A Matter of Performance
Often we have to take a step back and then move forward. In this article, we will show all the changes necessary to ensure that the Mouse and Chart Trade indicators do not break. As a bonus, we'll also cover other changes that have occurred in other header files that will be widely used in the future.
Population optimization algorithms: Binary Genetic Algorithm (BGA). Part I
In this article, we will explore various methods used in binary genetic and other population algorithms. We will look at the main components of the algorithm, such as selection, crossover and mutation, and their impact on the optimization. In addition, we will study data presentation methods and their impact on optimization results.
Gating mechanisms in ensemble learning
In this article, we continue our exploration of ensemble models by discussing the concept of gates, specifically how they may be useful in combining model outputs to enhance either prediction accuracy or model generalization.
An Introduction to the Study of Fractal Market Structures Using Machine Learning
The article attempts to examine financial time series from the perspective of self-similar fractal structures. Since we have too many analogies that confirm the possibility of considering market quotes as self-similar fractals, this allows us to think about the forecasting horizons of such structures.
MQL5 Wizard Techniques you should know (Part 35): Support Vector Regression
Support Vector Regression is an idealistic way of finding a function or ‘hyper-plane’ that best describes the relationship between two sets of data. We attempt to exploit this in time series forecasting within custom classes of the MQL5 wizard.
Market Simulation (Part 05): Creating the C_Orders Class (II)
In this article, I will explain how Chart Trade, together with the Expert Advisor, will process a request to close all of the users' open positions. This may sound simple, but there are a few complications that you need to know how to manage.
Eigenvectors and eigenvalues: Exploratory data analysis in MetaTrader 5
In this article we explore different ways in which the eigenvectors and eigenvalues can be applied in exploratory data analysis to reveal unique relationships in data.
Dolphin Echolocation Algorithm (DEA)
In this article, we take a closer look at the DEA algorithm, a metaheuristic optimization method inspired by dolphins' unique ability to find prey using echolocation. From mathematical foundations to practical implementation in MQL5, from analysis to comparison with classical algorithms, we will examine in detail why this relatively new method deserves a place in the arsenal of researchers facing optimization problems.
Analyzing binary code of prices on the exchange (Part I): A new look at technical analysis
This article presents an innovative approach to technical analysis based on converting price movements into binary code. The author demonstrates how various aspects of market behavior — from simple price movements to complex patterns — can be encoded in a sequence of zeros and ones.
Population optimization algorithms: Micro Artificial immune system (Micro-AIS)
The article considers an optimization method based on the principles of the body's immune system - Micro Artificial Immune System (Micro-AIS) - a modification of AIS. Micro-AIS uses a simpler model of the immune system and simple immune information processing operations. The article also discusses the advantages and disadvantages of Micro-AIS compared to conventional AIS.
MQL5 Trading Tools (Part 20): Canvas Graphing with Statistical Correlation and Regression Analysis
In this article, we create a canvas-based graphing tool in MQL5 for statistical correlation and linear regression analysis between two symbols, with draggable and resizable features. We incorporate ALGLIB for regression calculations, dynamic tick labels, data points, and a stats panel displaying slope, intercept, correlation, and R-squared. This interactive visualization aids in pair trading insights, supporting customizable themes, borders, and real-time updates on new bars
Developing a Replay System (Part 30): Expert Advisor project — C_Mouse class (IV)
Today we will learn a technique that can help us a lot in different stages of our professional life as a programmer. Often it is not the platform itself that is limited, but the knowledge of the person who talks about the limitations. This article will tell you that with common sense and creativity you can make the MetaTrader 5 platform much more interesting and versatile without resorting to creating crazy programs or anything like that, and create simple yet safe and reliable code. We will use our creativity to modify existing code without deleting or adding a single line to the source code.
Developing a Replay System (Part 64): Playing the service (V)
In this article, we will look at how to fix two errors in the code. However, I will try to explain them in a way that will help you, beginner programmers, understand that things don't always go as you expect. Anyway, this is an opportunity to learn. The content presented here is intended solely for educational purposes. In no way should this application be considered as a final document with any purpose other than to explore the concepts presented.
MQL5 Wizard Techniques you should know (Part 18): Neural Architecture Search with Eigen Vectors
Neural Architecture Search, an automated approach at determining the ideal neural network settings can be a plus when facing many options and large test data sets. We examine how when paired Eigen Vectors this process can be made even more efficient.
Non-stationary processes and spurious regression
The article demonstrates spurious regression occurring when attempting to apply regression analysis to non-stationary processes using Monte Carlo simulation.
Low-Frequency Quantitative Strategies in MetaTrader 5 (Part 3): A Regime-Adaptive Mean-Reversion Swing Trading System
The article describes and codes MR Swing in MQL5, a mean‑reversion swing approach that combines a 200‑day hysteresis channel with Value Charts, DVO, and SVAPO. We document entry/exit rules for bull and bear regimes and show five‑year backtests on six high‑liquidity Nasdaq stocks. The complete EA code and backtest configurations are provided for reproducibility.
The Group Method of Data Handling: Implementing the Multilayered Iterative Algorithm in MQL5
In this article we describe the implementation of the Multilayered Iterative Algorithm of the Group Method of Data Handling in MQL5.
MQL5 Wizard Techniques you should know (Part 87): Volatility-Scaled Money Management with Monotonic Queue in MQL5
This article presents a custom MQL5 money management class that adapts position sizing to real-time volatility using a monotonic queue for O(N) sliding-window extremes. The class applies inverse volatility scaling and optionally validates risk with an RBF network. We show implementation details in the Optimize method and compare results with the inbuilt Size-Optimized class to assess latency and risk control benefits.
Statistical Arbitrage Through Cointegrated Stocks (Part 10): Detecting Structural Breaks
This article presents the Chow test for detecting structural breaks in pair relationships and the application of the Cumulative Sum of Squares - CUSUM - for structural breaks monitoring and early detection. The article uses the Nvidia/Intel partnership announcement and the US Gov foreign trade tariff announcement as examples of slope inversion and intercept shift, respectively. Python scripts for all the tests are provided.
Larry Williams Market Secrets (Part 7): An Empirical Study of the Trade Day of the Week Concept
An empirical study of Larry Williams’ Trade Day of the Week concept, showing how time-based market bias can be measured, tested, and applied using MQL5. This article presents a practical framework for analyzing win rates and performance across trading days to improve short-term trading systems.
Deterministic Oscillatory Search (DOS)
Deterministic Oscillatory Search (DOS) algorithm is an innovative global optimization method that combines the advantages of gradient and swarm algorithms without the use of random numbers. The fitness oscillation and slope mechanism allows DOS to explore complex search spaces in a deterministic manner.
MQL5 Wizard Techniques you should know (Part 10). The Unconventional RBM
Restrictive Boltzmann Machines are at the basic level, a two-layer neural network that is proficient at unsupervised classification through dimensionality reduction. We take its basic principles and examine if we were to re-design and train it unorthodoxly, we could get a useful signal filter.
Developing a Replay System (Part 57): Understanding a Test Service
One point to note: although the service code is not included in this article and will only be provided in the next one, I'll explain it since we'll be using that same code as a springboard for what we're actually developing. So, be attentive and patient. Wait for the next article, because every day everything becomes more interesting.
Atmosphere Clouds Model Optimization (ACMO): Theory
The article is devoted to the metaheuristic Atmosphere Clouds Model Optimization (ACMO) algorithm, which simulates the behavior of clouds to solve optimization problems. The algorithm uses the principles of cloud generation, movement and propagation, adapting to the "weather conditions" in the solution space. The article reveals how the algorithm's meteorological simulation finds optimal solutions in a complex possibility space and describes in detail the stages of ACMO operation, including "sky" preparation, cloud birth, cloud movement, and rain concentration.
MQL5 Trading Toolkit (Part 6): Expanding the History Management EX5 Library with the Last Filled Pending Order Functions
Learn how to create an EX5 module of exportable functions that seamlessly query and save data for the most recently filled pending order. In this comprehensive step-by-step guide, we will enhance the History Management EX5 library by developing dedicated and compartmentalized functions to retrieve essential properties of the last filled pending order. These properties include the order type, setup time, execution time, filling type, and other critical details necessary for effective pending orders trade history management and analysis.
Developing a Replay System (Part 60): Playing the Service (I)
We have been working on just the indicators for a long time now, but now it's time to get the service working again and see how the chart is built based on the data provided. However, since the whole thing is not that simple, we will have to be attentive to understand what awaits us ahead.
Introduction to MQL5 (Part 41): Beginner Guide to File Handling in MQL5 (III)
Learn how to read a CSV file in MQL5 and organize its trading data into dynamic arrays. This article shows step by step how to count file elements, store all data in a single array, and separate each column into dedicated arrays, laying the foundation for advanced analysis and trading performance visualization.
A feature selection algorithm using energy based learning in pure MQL5
In this article we present the implementation of a feature selection algorithm described in an academic paper titled,"FREL: A stable feature selection algorithm", called Feature weighting as regularized energy based learning.
Analyzing Price Time Gaps in MQL5 (Part I): Building a Basic Indicator
Time gap analysis helps traders identify potential market reversal points. The article discusses what a time gap is, how to interpret it, and how it can be used to detect large volume influxes into the market.
Atmosphere Clouds Model Optimization (ACMO): Practice
In this article, we will continue diving into the implementation of the ACMO (Atmospheric Cloud Model Optimization) algorithm. In particular, we will discuss two key aspects: the movement of clouds into low-pressure regions and the rain simulation, including the initialization of droplets and their distribution among clouds. We will also look at other methods that play an important role in managing the state of clouds and ensuring their interaction with the environment.
Population optimization algorithms: Bacterial Foraging Optimization - Genetic Algorithm (BFO-GA)
The article presents a new approach to solving optimization problems by combining ideas from bacterial foraging optimization (BFO) algorithms and techniques used in the genetic algorithm (GA) into a hybrid BFO-GA algorithm. It uses bacterial swarming to globally search for an optimal solution and genetic operators to refine local optima. Unlike the original BFO, bacteria can now mutate and inherit genes.
Application of the Grey Model in Technical Analysis of Financial Time Series
This article explores the grey model, a promising tool that can expand trader's capabilities. We will look at some options for applying this model to technical analysis and building trading strategies.
Developing a Replay System (Part 45): Chart Trade Project (IV)
The main purpose of this article is to introduce and explain the C_ChartFloatingRAD class. We have a Chart Trade indicator that works in a rather interesting way. As you may have noticed, we still have a fairly small number of objects on the chart, and yet we get the expected functionality. The values present in the indicator can be edited. The question is, how is this possible? This article will start to make things clearer.
Adaptive Social Behavior Optimization (ASBO): Two-phase evolution
We continue dwelling on the topic of social behavior of living organisms and its impact on the development of a new mathematical model - ASBO (Adaptive Social Behavior Optimization). We will dive into the two-phase evolution, test the algorithm and draw conclusions. Just as in nature a group of living organisms join their efforts to survive, ASBO uses principles of collective behavior to solve complex optimization problems.
Market Simulation (Part 12): Sockets (VI)
In this article, we will look at how to solve certain problems and issues that arise when using Python code within other programs. More specifically, we will demonstrate a common issue encountered when using Excel in conjunction with MetaTrader 5, although we will be using Python to facilitate this interaction. However, this implementation has a minor drawback. It does not occur in all cases, but only in certain specific situations. When it does happen, it is necessary to understand the cause. In today’s article, we will begin explaining how to resolve this issue.
Feature selection and dimensionality reduction using principal components
The article delves into the implementation of a modified Forward Selection Component Analysis algorithm, drawing inspiration from the research presented in “Forward Selection Component Analysis: Algorithms and Applications” by Luca Puggini and Sean McLoone.