
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.

Data Science and ML (Part 36): Dealing with Biased Financial Markets
Financial markets are not perfectly balanced. Some markets are bullish, some are bearish, and some exhibit some ranging behaviors indicating uncertainty in either direction, this unbalanced information when used to train machine learning models can be misleading as the markets change frequently. In this article, we are going to discuss several ways to tackle this issue.

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.

Developing a Replay System (Part 65): Playing the service (VI)
In this article, we will look at how to implement and solve the mouse pointer issue when using it in conjunction with a replay/simulation application. 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 20): External Flow (IV) — Correlation Pathfinder
Correlation Pathfinder offers a fresh approach to understanding currency pair dynamics as part of the Price Action Analysis Toolkit Development Series. This tool automates data collection and analysis, providing insight into how pairs like EUR/USD and GBP/USD interact. Enhance your trading strategy with practical, real-time information that helps you manage risk and spot opportunities more effectively.

Decoding Opening Range Breakout Intraday Trading Strategies
Opening Range Breakout (ORB) strategies are built on the idea that the initial trading range established shortly after the market opens reflects significant price levels where buyers and sellers agree on value. By identifying breakouts above or below a certain range, traders can capitalize on the momentum that often follows as the market direction becomes clearer. In this article, we will explore three ORB strategies adapted from the Concretum Group.

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.

Developing a Replay System (Part 63): Playing the service (IV)
In this article, we will finally solve the problems with the simulation of ticks on a one-minute bar so that they can coexist with real ticks. This will help us avoid problems in the future. The material presented here is for educational purposes only. Under no circumstances should the application be viewed for any purpose other than to learn and master the concepts presented.

Statistical Arbitrage Through Mean Reversion in Pairs Trading: Beating the Market by Math
This article describes the fundamentals of portfolio-level statistical arbitrage. Its goal is to facilitate the understanding of the principles of statistical arbitrage to readers without deep math knowledge and propose a starting point conceptual framework. The article includes a working Expert Advisor, some notes about its one-year backtest, and the respective backtest configuration settings (.ini file) for the reproduction of the experiment.

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.

Quantitative approach to risk management: Applying VaR model to optimize multi-currency portfolio using Python and MetaTrader 5
This article explores the potential of the Value at Risk (VaR) model for multi-currency portfolio optimization. Using the power of Python and the functionality of MetaTrader 5, we demonstrate how to implement VaR analysis for efficient capital allocation and position management. From theoretical foundations to practical implementation, the article covers all aspects of applying one of the most robust risk calculation systems – VaR – in algorithmic trading.

Day Trading Larry Connors RSI2 Mean-Reversion Strategies
Larry Connors is a renowned trader and author, best known for his work in quantitative trading and strategies like the 2-period RSI (RSI2), which helps identify short-term overbought and oversold market conditions. In this article, we’ll first explain the motivation behind our research, then recreate three of Connors’ most famous strategies in MQL5 and apply them to intraday trading of the S&P 500 index CFD.

Developing a Replay System (Part 62): Playing the service (III)
In this article, we will begin to address the issue of tick excess that can impact application performance when using real data. This excess often interferes with the correct timing required to construct a one-minute bar in the appropriate window.

Data Science and ML (Part 35): NumPy in MQL5 – The Art of Making Complex Algorithms with Less Code
NumPy library is powering almost all the machine learning algorithms to the core in Python programming language, In this article we are going to implement a similar module which has a collection of all the complex code to aid us in building sophisticated models and algorithms of any kind.

Developing a Replay System (Part 61): Playing the service (II)
In this article, we will look at changes that will allow the replay/simulation system to operate more efficiently and securely. I will also not leave without attention those who want to get the most out of using classes. In addition, we will consider a specific problem in MQL5 that reduces code performance when working with classes, and explain how to solve it.

Price Action Analysis Toolkit Development (Part 18): Introducing Quarters Theory (III) — Quarters Board
In this article, we enhance the original Quarters Script by introducing the Quarters Board, a tool that lets you toggle quarter levels directly on the chart without needing to revisit the code. You can easily activate or deactivate specific levels, and the EA also provides trend direction commentary to help you better understand market movements.

Resampling techniques for prediction and classification assessment in MQL5
In this article, we will explore and implement, methods for assessing model quality that utilize a single dataset as both training and validation sets.

A New Approach to Custom Criteria in Optimizations (Part 1): Examples of Activation Functions
The first of a series of articles looking at the mathematics of Custom Criteria with a specific focus on non-linear functions used in Neural Networks, MQL5 code for implementation and the use of targeted and correctional offsets.

Price Action Analysis Toolkit Development (Part 17): TrendLoom EA Tool
As a price action observer and trader, I've noticed that when a trend is confirmed by multiple timeframes, it usually continues in that direction. What may vary is how long the trend lasts, and this depends on the type of trader you are, whether you hold positions for the long term or engage in scalping. The timeframes you choose for confirmation play a crucial role. Check out this article for a quick, automated system that helps you analyze the overall trend across different timeframes with just a button click or regular updates.

Creating a Trading Administrator Panel in MQL5 (Part IX): Code Organization (III): Communication Module
Join us for an in-depth discussion on the latest advancements in MQL5 interface design as we unveil the redesigned Communications Panel and continue our series on building the New Admin Panel using modularization principles. We'll develop the CommunicationsDialog class step by step, thoroughly explaining how to inherit it from the Dialog class. Additionally, we'll leverage arrays and ListView class in our development. Gain actionable insights to elevate your MQL5 development skills—read through the article and join the discussion in the comments section!

Data Science and ML (Part 34): Time series decomposition, Breaking the stock market down to the core
In a world overflowing with noisy and unpredictable data, identifying meaningful patterns can be challenging. In this article, we'll explore seasonal decomposition, a powerful analytical technique that helps separate data into its key components: trend, seasonal patterns, and noise. By breaking data down this way, we can uncover hidden insights and work with cleaner, more interpretable information.

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.

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.

Price Action Analysis Toolkit Development (Part 16): Introducing Quarters Theory (II) — Intrusion Detector EA
In our previous article, we introduced a simple script called "The Quarters Drawer." Building on that foundation, we are now taking the next step by creating a monitor Expert Advisor (EA) to track these quarters and provide oversight regarding potential market reactions at these levels. Join us as we explore the process of developing a zone detection tool in this article.

MQL5 Trading Toolkit (Part 8): How to Implement and Use the History Manager EX5 Library in Your Codebase
Discover how to effortlessly import and utilize the History Manager EX5 library in your MQL5 source code to process trade histories in your MetaTrader 5 account in this series' final article. With simple one-line function calls in MQL5, you can efficiently manage and analyze your trading data. Additionally, you will learn how to create different trade history analytics scripts and develop a price-based Expert Advisor as practical use-case examples. The example EA leverages price data and the History Manager EX5 library to make informed trading decisions, adjust trade volumes, and implement recovery strategies based on previously closed trades.

William Gann methods (Part III): Does Astrology Work?
Do the positions of planets and stars affect financial markets? Let's arm ourselves with statistics and big data, and embark on an exciting journey into the world where stars and stock charts intersect.

Cycles and Forex
Cycles are of great importance in our lives. Day and night, seasons, days of the week and many other cycles of different nature are present in the life of any person. In this article, we will consider cycles in financial markets.

MQL5 Wizard Techniques you should know (Part 56): Bill Williams Fractals
The Fractals by Bill Williams is a potent indicator that is easy to overlook when one initially spots it on a price chart. It appears too busy and probably not incisive enough. We aim to draw away this curtain on this indicator by examining what its various patterns could accomplish when examined with forward walk tests on all, with wizard assembled Expert Advisor.

The Kalman Filter for Forex Mean-Reversion Strategies
The Kalman filter is a recursive algorithm used in algorithmic trading to estimate the true state of a financial time series by filtering out noise from price movements. It dynamically updates predictions based on new market data, making it valuable for adaptive strategies like mean reversion. This article first introduces the Kalman filter, covering its calculation and implementation. Next, we apply the filter to a classic mean-reversion forex strategy as an example. Finally, we conduct various statistical analyses by comparing the filter with a moving average across different forex pairs.

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.

MQL5 Wizard Techniques you should know (Part 55): SAC with Prioritized Experience Replay
Replay buffers in Reinforcement Learning are particularly important with off-policy algorithms like DQN or SAC. This then puts the spotlight on the sampling process of this memory-buffer. While default options with SAC, for instance, use random selection from this buffer, Prioritized Experience Replay buffers fine tune this by sampling from the buffer based on a TD-score. We review the importance of Reinforcement Learning, and, as always, examine just this hypothesis (not the cross-validation) in a wizard assembled Expert Advisor.

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.

Price Action Analysis Toolkit Development (Part 13): RSI Sentinel Tool
Price action can be effectively analyzed by identifying divergences, with technical indicators such as the RSI providing crucial confirmation signals. In the article below, we explain how automated RSI divergence analysis can identify trend continuations and reversals, thereby offering valuable insights into market sentiment.

Creating a Trading Administrator Panel in MQL5 (Part IX): Code Organization (II): Modularization
In this discussion, we take a step further in breaking down our MQL5 program into smaller, more manageable modules. These modular components will then be integrated into the main program, enhancing its organization and maintainability. This approach simplifies the structure of our main program and makes the individual components reusable in other Expert Advisors (EAs) and indicator developments. By adopting this modular design, we create a solid foundation for future enhancements, benefiting both our project and the broader developer community.

Developing a Replay System (Part 59): A New Future
Having a proper understanding of different ideas allows us to do more with less effort. In this article, we'll look at why it's necessary to configure a template before the service can interact with the chart. Also, what if we improve the mouse pointer so we can do more things with it?

MQL5 Wizard Techniques you should know (Part 54): Reinforcement Learning with hybrid SAC and Tensors
Soft Actor Critic is a Reinforcement Learning algorithm that we looked at in a previous article, where we also introduced python and ONNX to these series as efficient approaches to training networks. We revisit the algorithm with the aim of exploiting tensors, computational graphs that are often exploited in Python.

Robustness Testing on Expert Advisors
In strategy development, there are many intricate details to consider, many of which are not highlighted for beginner traders. As a result, many traders, myself included, have had to learn these lessons the hard way. This article is based on my observations of common pitfalls that most beginner traders encounter when developing strategies on MQL5. It will offer a range of tips, tricks, and examples to help identify the disqualification of an EA and test the robustness of our own EAs in an easy-to-implement way. The goal is to educate readers, helping them avoid future scams when purchasing EAs as well as preventing mistakes in their own strategy development.

Price Action Analysis Toolkit Development (Part 12): External Flow (III) TrendMap
The flow of the market is determined by the forces between bulls and bears. There are specific levels that the market respects due to the forces acting on them. Fibonacci and VWAP levels are especially powerful in influencing market behavior. Join me in this article as we explore a strategy based on VWAP and Fibonacci levels for signal generation.

Creating a Trading Administrator Panel in MQL5 (Part IX): Code Organization (I)
This discussion delves into the challenges encountered when working with large codebases. We will explore the best practices for code organization in MQL5 and implement a practical approach to enhance the readability and scalability of our Trading Administrator Panel source code. Additionally, we aim to develop reusable code components that can potentially benefit other developers in their algorithm development. Read on and join the conversation.

Artificial Bee Hive Algorithm (ABHA): Tests and results
In this article, we will continue exploring the Artificial Bee Hive Algorithm (ABHA) by diving into the code and considering the remaining methods. As you might remember, each bee in the model is represented as an individual agent whose behavior depends on internal and external information, as well as motivational state. We will test the algorithm on various functions and summarize the results by presenting them in the rating table.