MQL4 and MQL5 Programming Articles

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Study the MQL5 language for programming trading strategies in numerous published articles mostly written by you - the community members. The articles are grouped into categories to help you quicker find answers to any questions related to programming: Integration, Tester, Trading Strategies, etc.

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Introduction to MQL5 (Part 13): A Beginner's Guide to Building Custom Indicators (II)

This article guides you through building a custom Heikin Ashi indicator from scratch and demonstrates how to integrate custom indicators into an EA. It covers indicator calculations, trade execution logic, and risk management techniques to enhance automated trading strategies.
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Artificial Algae Algorithm (AAA)

The article considers the Artificial Algae Algorithm (AAA) based on biological processes characteristic of microalgae. The algorithm includes spiral motion, evolutionary process and adaptation, which allows it to solve optimization problems. The article provides an in-depth analysis of the working principles of AAA and its potential in mathematical modeling, highlighting the connection between nature and algorithmic solutions.
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Neural Network in Practice: Sketching a Neuron

In this article we will build a basic neuron. And although it looks simple, and many may consider this code completely trivial and meaningless, I want you to have fun studying this simple sketch of a neuron. Don't be afraid to modify the code, understanding it fully is the goal.
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Automating Trading Strategies in MQL5 (Part 10): Developing the Trend Flat Momentum Strategy

In this article, we develop an Expert Advisor in MQL5 for the Trend Flat Momentum Strategy. We combine a two moving averages crossover with RSI and CCI momentum filters to generate trade signals. We also cover backtesting and potential enhancements for real-world performance.
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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.
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William Gann methods (Part II): Creating Gann Square indicator

We will create an indicator based on the Gann's Square of 9, built by squaring time and price. We will prepare the code and test the indicator in the platform on different time intervals.
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From Basic to Intermediate: Operators

In this article we will look at the main operators. Although the topic is simple to understand, there are certain points that are of great importance when it comes to including mathematical expressions in the code format. Without an adequate understanding of these details, programmers with little or no experience eventually give up trying to create their own solutions.
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Price Action Analysis Toolkit Development (Part 15): Introducing Quarters Theory (I) — Quarters Drawer Script

Points of support and resistance are critical levels that signal potential trend reversals and continuations. Although identifying these levels can be challenging, once you pinpoint them, you’re well-prepared to navigate the market. For further assistance, check out the Quarters Drawer tool featured in this article, it will help you identify both primary and minor support and resistance levels.
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Trading with the MQL5 Economic Calendar (Part 6): Automating Trade Entry with News Event Analysis and Countdown Timers

In this article, we implement automated trade entry using the MQL5 Economic Calendar by applying user-defined filters and time offsets to identify qualifying news events. We compare forecast and previous values to determine whether to open a BUY or SELL trade. Dynamic countdown timers display the remaining time until news release and reset automatically after a trade.
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Automating Trading Strategies in MQL5 (Part 9): Building an Expert Advisor for the Asian Breakout Strategy

In this article, we build an Expert Advisor in MQL5 for the Asian Breakout Strategy by calculating the session's high and low and applying trend filtering with a moving average. We implement dynamic object styling, user-defined time inputs, and robust risk management. Finally, we demonstrate backtesting and optimization techniques to refine the program.
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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.
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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.
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Automating Trading Strategies in MQL5 (Part 8): Building an Expert Advisor with Butterfly Harmonic Patterns

In this article, we build an MQL5 Expert Advisor to detect Butterfly harmonic patterns. We identify pivot points and validate Fibonacci levels to confirm the pattern. We then visualize the pattern on the chart and automatically execute trades when confirmed.
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Neural Networks in Trading: Injection of Global Information into Independent Channels (InjectTST)

Most modern multimodal time series forecasting methods use the independent channels approach. This ignores the natural dependence of different channels of the same time series. Smart use of two approaches (independent and mixed channels) is the key to improving the performance of the models.
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Build Self Optimizing Expert Advisors in MQL5 (Part 6): Stop Out Prevention

Join us in our discussion today as we look for an algorithmic procedure to minimize the total number of times we get stopped out of winning trades. The problem we faced is significantly challenging, and most solutions given in community discussions lack set and fixed rules. Our algorithmic approach to solving the problem increased the profitability of our trades and reduced our average loss per trade. However, there are further advancements to be made to completely filter out all trades that will be stopped out, our solution is a good first step for anyone to try.
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Neural Networks in Trading: Practical Results of the TEMPO Method

Neural Networks in Trading: Practical Results of the TEMPO Method

We continue our acquaintance with the TEMPO method. In this article we will evaluate the actual effectiveness of the proposed approaches on real historical data.
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Price Action Analysis Toolkit Development (Part 14): Parabolic Stop and Reverse Tool

Price Action Analysis Toolkit Development (Part 14): Parabolic Stop and Reverse Tool

Embracing technical indicators in price action analysis is a powerful approach. These indicators often highlight key levels of reversals and retracements, offering valuable insights into market dynamics. In this article, we demonstrate how we developed an automated tool that generates signals using the Parabolic SAR indicator.
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William Gann methods (Part I): Creating Gann Angles indicator

William Gann methods (Part I): Creating Gann Angles indicator

What is the essence of Gann Theory? How are Gann angles constructed? We will create Gann Angles indicator for MetaTrader 5.
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Master MQL5 from beginner to pro (Part IV): About Arrays, Functions and Global Terminal Variables

Master MQL5 from beginner to pro (Part IV): About Arrays, Functions and Global Terminal Variables

The article is a continuation of the series for beginners. It covers in detail data arrays, the interaction of data and functions, as well as global terminal variables that allow data exchange between different MQL5 programs.
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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.
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Automating Trading Strategies in MQL5 (Part 7): Building a Grid Trading EA with Dynamic Lot Scaling

Automating Trading Strategies in MQL5 (Part 7): Building a Grid Trading EA with Dynamic Lot Scaling

In this article, we build a grid trading expert advisor in MQL5 that uses dynamic lot scaling. We cover the strategy design, code implementation, and backtesting process. Finally, we share key insights and best practices for optimizing the automated trading system.
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Price Action Analysis Toolkit Development (Part 13): RSI Sentinel Tool

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.
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Creating a Trading Administrator Panel in MQL5 (Part IX): Code Organization (II): Modularization

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.
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Developing a Replay System (Part 59): A New Future

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?
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From Basic to Intermediate: Variables (III)

From Basic to Intermediate: Variables (III)

Today we will look at how to use predefined MQL5 language variables and constants. In addition, we will analyze another special type of variables: functions. Knowing how to properly work with these variables can mean the difference between an application that works and one that doesn't. In order to understand what is presented here, it is necessary to understand the material that was discussed in previous articles.
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Deconstructing examples of trading strategies in the client terminal

Deconstructing examples of trading strategies in the client terminal

The article uses block diagrams to examine the logic of the candlestick-based training EAs located in the Experts\Free Robots folder of the terminal.
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MQL5 Wizard Techniques you should know (Part 54): Reinforcement Learning with hybrid SAC and Tensors

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.
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Building a Keltner Channel Indicator with Custom Canvas Graphics in MQL5

Building a Keltner Channel Indicator with Custom Canvas Graphics in MQL5

In this article, we build a Keltner Channel indicator with custom canvas graphics in MQL5. We detail the integration of moving averages, ATR calculations, and enhanced chart visualization. We also cover backtesting to evaluate the indicator’s performance for practical trading insights.
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Mastering JSON: Create Your Own JSON Reader from Scratch in MQL5

Mastering JSON: Create Your Own JSON Reader from Scratch in MQL5

Experience a step-by-step guide on creating a custom JSON parser in MQL5, complete with object and array handling, error checking, and serialization. Gain practical insights into bridging your trading logic and structured data with this flexible solution for handling JSON in MetaTrader 5.
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Neural Networks in Trading: Using Language Models for Time Series Forecasting

Neural Networks in Trading: Using Language Models for Time Series Forecasting

We continue to study time series forecasting models. In this article, we get acquainted with a complex algorithm built on the use of a pre-trained language model.
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Robustness Testing on Expert Advisors

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.
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Mastering Log Records (Part 5): Optimizing the Handler with Cache and Rotation

Mastering Log Records (Part 5): Optimizing the Handler with Cache and Rotation

This article improves the logging library by adding formatters in handlers, the CIntervalWatcher class to manage execution cycles, optimization with caching and file rotation, performance tests and practical examples. With these improvements, we ensure an efficient, scalable and adaptable logging system to different development scenarios.
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Automating Trading Strategies in MQL5 (Part 6): Mastering Order Block Detection for Smart Money Trading

Automating Trading Strategies in MQL5 (Part 6): Mastering Order Block Detection for Smart Money Trading

In this article, we automate order block detection in MQL5 using pure price action analysis. We define order blocks, implement their detection, and integrate automated trade execution. Finally, we backtest the strategy to evaluate its performance.
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Neural Networks in Trading: Lightweight Models for Time Series Forecasting

Neural Networks in Trading: Lightweight Models for Time Series Forecasting

Lightweight time series forecasting models achieve high performance using a minimum number of parameters. This, in turn, reduces the consumption of computing resources and speeds up decision-making. Despite being lightweight, such models achieve forecast quality comparable to more complex ones.
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Price Action Analysis Toolkit Development (Part 12): External Flow (III) TrendMap

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.
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Creating a Trading Administrator Panel in MQL5 (Part IX): Code Organization (I)

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.
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Introduction to MQL5 (Part 12): A Beginner's Guide to Building Custom Indicators

Introduction to MQL5 (Part 12): A Beginner's Guide to Building Custom Indicators

Learn how to build a custom indicator in MQL5. With a project-based approach. This beginner-friendly guide covers indicator buffers, properties, and trend visualization, allowing you to learn step-by-step.
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Artificial Bee Hive Algorithm (ABHA): Tests and results

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.
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Feature Engineering With Python And MQL5 (Part III): Angle Of Price (2) Polar Coordinates

Feature Engineering With Python And MQL5 (Part III): Angle Of Price (2) Polar Coordinates

In this article, we take our second attempt to convert the changes in price levels on any market, into a corresponding change in angle. This time around, we selected a more mathematically sophisticated approach than we selected in our first attempt, and the results we obtained suggest that our change in approach may have been the right decision. Join us today, as we discuss how we can use Polar coordinates to calculate the angle formed by changes in price levels, in a meaningful way, regardless of which market you are analyzing.
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Developing a Replay System (Part 58): Returning to Work on the Service

Developing a Replay System (Part 58): Returning to Work on the Service

After a break in development and improvement of the service used for replay/simulator, we are resuming work on it. Now that we've abandoned the use of resources like terminal globals, we'll have to completely restructure some parts of it. Don't worry, this process will be explained in detail so that everyone can follow the development of our service.