Implementing Practical Modules from Other Languages in MQL5 (Part 03): Schedule Module from Python, the OnTimer Event on Steroids
The schedule module in Python offers a simple way to schedule repeated tasks. While MQL5 lacks a built-in equivalent, in this article we’ll implement a similar library to make it easier to set up timed events in MetaTrader 5.
MQL5 Trading Tools (Part 6): Dynamic Holographic Dashboard with Pulse Animations and Controls
In this article, we create a dynamic holographic dashboard in MQL5 for monitoring symbols and timeframes with RSI, volatility alerts, and sorting options. We add pulse animations, interactive buttons, and holographic effects to make the tool visually engaging and responsive.
Population ADAM (Adaptive Moment Estimation)
The article presents the transformation of the well-known and popular ADAM gradient optimization method into a population algorithm and its modification with the introduction of hybrid individuals. The new approach allows creating agents that combine elements of successful decisions using probability distribution. The key innovation is the formation of hybrid population individuals that adaptively accumulate information from the most promising solutions, increasing the efficiency of search in complex multidimensional spaces.
Reimagining Classic Strategies (Part 14): Multiple Strategy Analysis
In this article, we continue our exploration of building an ensemble of trading strategies and using the MT5 genetic optimizer to tune the strategy parameters. Today, we analyzed the data in Python, showing our model could better predict which strategy would outperform, achieving higher accuracy than forecasting market returns directly. However, when we tested our application with its statistical models, our performance levels fell dismally. We subsequently discovered that the genetic optimizer unfortunately favored highly correlated strategies, prompting us to revise our method to keep vote weights fixed and focus optimization on indicator settings instead.
MQL5 Trading Tools (Part 5): Creating a Rolling Ticker Tape for Real-Time Symbol Monitoring
In this article, we develop a rolling ticker tape in MQL5 for real-time monitoring of multiple symbols, displaying bid prices, spreads, and daily percentage changes with scrolling effects. We implement customizable fonts, colors, and scroll speeds to highlight price movements and trends effectively.
Creating 3D bars based on time, price and volume
The article dwells on multivariate 3D price charts and their creation. We will also consider how 3D bars predict price reversals, and how Python and MetaTrader 5 allow us to plot these volume bars in real time.
Data Science and ML (Part 46): Stock Markets Forecasting Using N-BEATS in Python
N-BEATS is a revolutionary deep learning model designed for time series forecasting. It was released to surpass classical models for time series forecasting such as ARIMA, PROPHET, VAR, etc. In this article, we are going to discuss this model and use it in predicting the stock market.
Price Action Analysis Toolkit Development (Part 32): Python Candlestick Recognition Engine (II) — Detection Using Ta-Lib
In this article, we’ve transitioned from manually coding candlestick‑pattern detection in Python to leveraging TA‑Lib, a library that recognizes over sixty distinct patterns. These formations offer valuable insights into potential market reversals and trend continuations. Follow along to learn more.
From Novice to Expert: Animated News Headline Using MQL5 (VI) — Pending Order Strategy for News Trading
In this article, we shift focus toward integrating news-driven order execution logic—enabling the EA to act, not just inform. Join us as we explore how to implement automated trade execution in MQL5 and extend the News Headline EA into a fully responsive trading system. Expert Advisors offer significant advantages for algorithmic developers thanks to the wide range of features they support. So far, we’ve focused on building a news and calendar events presentation tool, complete with integrated AI insights lanes and technical indicator insights.
MQL5 Trading Tools (Part 4): Improving the Multi-Timeframe Scanner Dashboard with Dynamic Positioning and Toggle Features
In this article, we upgrade the MQL5 Multi-Timeframe Scanner Dashboard with movable and toggle features. We enable dragging the dashboard and a minimize/maximize option for better screen use. We implement and test these enhancements for improved trading flexibility.
Developing a Replay System (Part 75): New Chart Trade (II)
In this article, we will talk about the C_ChartFloatingRAD class. This is what makes Chart Trade work. However, the explanation does not end there. We will complete it in the next article, as the content of this article is quite extensive and requires deep understanding. 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.
Price Action Analysis Toolkit Development (Part 31): Python Candlestick Recognition Engine (I) — Manual Detection
Candlestick patterns are fundamental to price-action trading, offering valuable insights into potential market reversals or continuations. Envision a reliable tool that continuously monitors each new price bar, identifies key formations such as engulfing patterns, hammers, dojis, and stars, and promptly notifies you when a significant trading setup is detected. This is precisely the functionality we have developed. Whether you are new to trading or an experienced professional, this system provides real-time alerts for candlestick patterns, enabling you to focus on executing trades with greater confidence and efficiency. Continue reading to learn how it operates and how it can enhance your trading strategy.
Non-linear regression models on the stock exchange
Non-linear regression models on the stock exchange: Is it possible to predict financial markets? Let's consider creating a model for forecasting prices for EURUSD, and make two robots based on it - in Python and MQL5.
From Novice to Expert: Animated News Headline Using MQL5 (V)—Event Reminder System
In this discussion, we’ll explore additional advancements as we integrate refined event‑alerting logic for the economic calendar events displayed by the News Headline EA. This enhancement is critical—it ensures users receive timely notifications a short time before key upcoming events. Join this discussion to discover more.

Singular Spectrum Analysis in MQL5
This article is meant as a guide for those unfamiliar with the concept of Singular Spectrum Analysis and who wish to gain enough understanding to be able to apply the built-in tools available in MQL5.

Developing a Replay System (Part 74): New Chart Trade (I)
In this article, we will modify the last code shown in this series about Chart Trade. These changes are necessary to adapt the code to the current replay/simulation system model. 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.

From Novice to Expert: Animated News Headline Using MQL5 (IV) — Locally hosted AI model market insights
In today's discussion, we explore how to self-host open-source AI models and use them to generate market insights. This forms part of our ongoing effort to expand the News Headline EA, introducing an AI Insights Lane that transforms it into a multi-integration assistive tool. The upgraded EA aims to keep traders informed through calendar events, financial breaking news, technical indicators, and now AI-generated market perspectives—offering timely, diverse, and intelligent support to trading decisions. Join the conversation as we explore practical integration strategies and how MQL5 can collaborate with external resources to build a powerful and intelligent trading work terminal.

Statistical Arbitrage Through Cointegrated Stocks (Part 1): Engle-Granger and Johansen Cointegration Tests
This article aims to provide a trader-friendly, gentle introduction to the most common cointegration tests, along with a simple guide to understanding their results. The Engle-Granger and Johansen cointegration tests can reveal statistically significant pairs or groups of assets that share long-term dynamics. The Johansen test is especially useful for portfolios with three or more assets, as it calculates the strength of cointegrating vectors all at once.

Using association rules in Forex data analysis
How to apply predictive rules of supermarket retail analytics to the real Forex market? How are purchases of cookies, milk and bread related to stock exchange transactions? The article discusses an innovative approach to algorithmic trading based on the use of association rules.

Price Action Analysis Toolkit Development (Part 30): Commodity Channel Index (CCI), Zero Line EA
Automating price action analysis is the way forward. In this article, we utilize the Dual CCI indicator, the Zero Line Crossover strategy, EMA, and price action to develop a tool that generates trade signals and sets stop-loss (SL) and take-profit (TP) levels using ATR. Please read this article to learn how we approach the development of the CCI Zero Line EA.

From Novice to Expert: Animated News Headline Using MQL5 (III) — Indicator Insights
In this article, we’ll advance the News Headline EA by introducing a dedicated indicator insights lane—a compact, on-chart display of key technical signals generated from popular indicators such as RSI, MACD, Stochastic, and CCI. This approach eliminates the need for multiple indicator subwindows on the MetaTrader 5 terminal, keeping your workspace clean and efficient. By leveraging the MQL5 API to access indicator data in the background, we can process and visualize market insights in real-time using custom logic. Join us as we explore how to manipulate indicator data in MQL5 to create an intelligent and space-saving scrolling insights system, all within a single horizontal lane on your trading chart.

Price Action Analysis Toolkit Development (Part 29): Boom and Crash Interceptor EA
Discover how the Boom & Crash Interceptor EA transforms your charts into a proactive alert system-spotting explosive moves with lightning-fast velocity scans, volatility surge checks, trend confirmation, and pivot-zone filters. With crisp green “Boom” and red “Crash” arrows guiding your every decision, this tool cuts through the noise and lets you capitalize on market spikes like never before. Dive in to see how it works and why it can become your next essential edge.

Volumetric neural network analysis as a key to future trends
The article explores the possibility of improving price forecasting based on trading volume analysis by integrating technical analysis principles with LSTM neural network architecture. Particular attention is paid to the detection and interpretation of anomalous volumes, the use of clustering and the creation of features based on volumes and their definition in the context of machine learning.

MetaTrader 5 Machine Learning Blueprint (Part 1): Data Leakage and Timestamp Fixes
Before we can even begin to make use of ML in our trading on MetaTrader 5, it’s crucial to address one of the most overlooked pitfalls—data leakage. This article unpacks how data leakage, particularly the MetaTrader 5 timestamp trap, can distort our model's performance and lead to unreliable trading signals. By diving into the mechanics of this issue and presenting strategies to prevent it, we pave the way for building robust machine learning models that deliver trustworthy predictions in live trading environments.

Developing a Replay System (Part 73): An Unusual Communication (II)
In this article, we will look at how to transmit information in real time between the indicator and the service, and also understand why problems may arise when changing the timeframe and how to solve them. As a bonus, you will get access to the latest version of the replay /simulation app.

Atomic Orbital Search (AOS) algorithm
The article considers the Atomic Orbital Search (AOS) algorithm, which uses the concepts of the atomic orbital model to simulate the search for solutions. The algorithm is based on probability distributions and the dynamics of interactions in the atom. The article discusses in detail the mathematical aspects of AOS, including updating the positions of candidate solutions and the mechanisms of energy absorption and release. AOS opens new horizons for applying quantum principles to computing problems by offering an innovative approach to optimization.

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.

Training a multilayer perceptron using the Levenberg-Marquardt algorithm
The article presents an implementation of the Levenberg-Marquardt algorithm for training feedforward neural networks. A comparative analysis of performance with algorithms from the scikit-learn Python library has been conducted. Simpler learning methods, such as gradient descent, gradient descent with momentum, and stochastic gradient descent are preliminarily discussed.

Data Science and ML (Part 43): Hidden Patterns Detection in Indicators Data Using Latent Gaussian Mixture Models (LGMM)
Have you ever looked at the chart and felt that strange sensation… that there’s a pattern hidden just beneath the surface? A secret code that might reveal where prices are headed if only you could crack it? Meet LGMM, the Market’s Hidden Pattern Detector. A machine learning model that helps identify those hidden patterns in the market.

Analyzing weather impact on currencies of agricultural countries using Python
What is the relationship between weather and Forex? Classical economic theory has long ignored the influence of such factors as weather on market behavior. But everything has changed. Let's try to find connections between the weather conditions and the position of agricultural currencies on the market.

From Novice to Expert: Animated News Headline Using MQL5 (I)
News accessibility is a critical factor when trading on the MetaTrader 5 terminal. While numerous news APIs are available, many traders face challenges in accessing and integrating them effectively into their trading environment. In this discussion, we aim to develop a streamlined solution that brings news directly onto the chart—where it’s most needed. We'll accomplish this by building a News Headline Expert Advisor that monitors and displays real-time news updates from API sources.

Developing a Replay System (Part 72): An Unusual Communication (I)
What we create today will be difficult to understand. Therefore, in this article I will only talk about the initial stage. Please read this article carefully, it is an important prerequisite before we proceed to the next step. The purpose of this material is purely didactic as we will only study and master the presented concepts, without practical application.

Price Action Analysis Toolkit Development (Part 27): Liquidity Sweep With MA Filter Tool
Understanding the subtle dynamics behind price movements can give you a critical edge. One such phenomenon is the liquidity sweep, a deliberate strategy that large traders, especially institutions, use to push prices through key support or resistance levels. These levels often coincide with clusters of retail stop-loss orders, creating pockets of liquidity that big players can exploit to enter or exit sizeable positions with minimal slippage.

ALGLIB library optimization methods (Part II)
In this article, we will continue to study the remaining optimization methods from the ALGLIB library, paying special attention to their testing on complex multidimensional functions. This will allow us not only to evaluate the efficiency of each algorithm, but also to identify their strengths and weaknesses in different conditions.

Price Action Analysis Toolkit Development (Part 26): Pin Bar, Engulfing Patterns and RSI Divergence (Multi-Pattern) Tool
Aligned with our goal of developing practical price-action tools, this article explores the creation of an EA that detects pin bar and engulfing patterns, using RSI divergence as a confirmation trigger before generating any trading signals.

Developing a Replay System (Part 71): Getting the Time Right (IV)
In this article, we will look at how to implement what was shown in the previous article related to our replay/simulation service. As in many other things in life, problems are bound to arise. And this case was no exception. In this article, we continue to improve things. 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.

Data Science and ML (Part 42): Forex Time series Forecasting using ARIMA in Python, Everything you need to Know
ARIMA, short for Auto Regressive Integrated Moving Average, is a powerful traditional time series forecasting model. With the ability to detect spikes and fluctuations in a time series data, this model can make accurate predictions on the next values. In this article, we are going to understand what is it, how it operates, what you can do with it when it comes to predicting the next prices in the market with high accuracy and much more.

Price Action Analysis Toolkit Development (Part 25): Dual EMA Fractal Breaker
Price action is a fundamental approach for identifying profitable trading setups. However, manually monitoring price movements and patterns can be challenging and time-consuming. To address this, we are developing tools that analyze price action automatically, providing timely signals whenever potential opportunities are detected. This article introduces a robust tool that leverages fractal breakouts alongside EMA 14 and EMA 200 to generate reliable trading signals, helping traders make informed decisions with greater confidence.

ALGLIB library optimization methods (Part I)
In this article, we will get acquainted with the ALGLIB library optimization methods for MQL5. The article includes simple and clear examples of using ALGLIB to solve optimization problems, which will make mastering the methods as accessible as possible. We will take a detailed look at the connection of such algorithms as BLEIC, L-BFGS and NS, and use them to solve a simple test problem.

Build Self Optimizing Expert Advisors in MQL5 (Part 7): Trading With Multiple Periods At Once
In this series of articles, we have considered multiple different ways of identifying the best period to use our technical indicators with. Today, we shall demonstrate to the reader how they can instead perform the opposite logic, that is to say, instead of picking the single best period to use, we will demonstrate to the reader how to employ all available periods effectively. This approach reduces the amount of data discarded, and offers alternative use cases for machine learning algorithms beyond ordinary price prediction.