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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Developing a Replay System — Market simulation (Part 23): FOREX (IV)

Developing a Replay System — Market simulation (Part 23): FOREX (IV)

Now the creation occurs at the same point where we converted ticks into bars. This way, if something goes wrong during the conversion process, we will immediately notice the error. This is because the same code that places 1-minute bars on the chart during fast forwarding is also used for the positioning system to place bars during normal performance. In other words, the code that is responsible for this task is not duplicated anywhere else. This way we get a much better system for both maintenance and improvement.
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Neural networks made easy (Part 42): Model procrastination, reasons and solutions

Neural networks made easy (Part 42): Model procrastination, reasons and solutions

In the context of reinforcement learning, model procrastination can be caused by several reasons. The article considers some of the possible causes of model procrastination and methods for overcoming them.
View of Technical Analysis in the Context of Automatic Control Systems (ACS), or "Reverse View"
View of Technical Analysis in the Context of Automatic Control Systems (ACS), or "Reverse View"

View of Technical Analysis in the Context of Automatic Control Systems (ACS), or "Reverse View"

The article demonstrates an alternative view of technical analysis, which is based on the principles of both the modern automatic control theory and technical analysis itself. It is an introductory article representing the theory with some practical applications of it.
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Data Science and ML (Part 32): Keeping your AI models updated, Online Learning

Data Science and ML (Part 32): Keeping your AI models updated, Online Learning

In the ever-changing world of trading, adapting to market shifts is not just a choice—it's a necessity. New patterns and trends emerge everyday, making it harder even the most advanced machine learning models to stay effective in the face of evolving conditions. In this article, we’ll explore how to keep your models relevant and responsive to new market data by automatically retraining.
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MQL5 Wizard Techniques you should know (Part 61): Using Patterns of ADX and CCI with Supervised Learning

MQL5 Wizard Techniques you should know (Part 61): Using Patterns of ADX and CCI with Supervised Learning

The ADX Oscillator and CCI oscillator are trend following and momentum indicators that can be paired when developing an Expert Advisor. We look at how this can be systemized by using all the 3 main training modes of Machine Learning. Wizard Assembled Expert Advisors allow us to evaluate the patterns presented by these two indicators, and we start by looking at how Supervised-Learning can be applied with these Patterns.
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MQL5 Wizard Techniques you should know (Part 24): Moving Averages

MQL5 Wizard Techniques you should know (Part 24): Moving Averages

Moving Averages are a very common indicator that are used and understood by most Traders. We explore possible use cases that may not be so common within MQL5 Wizard assembled Expert Advisors.
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Price Action Analysis Toolkit Development (Part 31): Python Candlestick Recognition Engine (I) — Manual Detection

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.
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DoEasy. Controls (Part 31): Scrolling the contents of the ScrollBar control

DoEasy. Controls (Part 31): Scrolling the contents of the ScrollBar control

In this article, I will implement the functionality of scrolling the contents of the container using the buttons of the horizontal scrollbar.
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Automating Trading Strategies in MQL5 (Part 32): Creating a Price Action 5 Drives Harmonic Pattern System

Automating Trading Strategies in MQL5 (Part 32): Creating a Price Action 5 Drives Harmonic Pattern System

In this article, we develop a 5 Drives pattern system in MQL5 that identifies bullish and bearish 5 Drives harmonic patterns using pivot points and Fibonacci ratios, executing trades with customizable entry, stop loss, and take-profit levels based on user-selected options. We enhance trader insight with visual feedback through chart objects like triangles, trendlines, and labels to clearly display the A-B-C-D-E-F pattern structure.
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MQL5 Trading Tools (Part 7): Informational Dashboard for Multi-Symbol Position and Account Monitoring

MQL5 Trading Tools (Part 7): Informational Dashboard for Multi-Symbol Position and Account Monitoring

In this article, we develop an informational dashboard in MQL5 for monitoring multi-symbol positions and account metrics like balance, equity, and free margin. We implement a sortable grid with real-time updates, CSV export, and a glowing header effect to enhance usability and visual appeal.
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From Novice to Expert: Animated News Headline Using MQL5 (III) — Indicator Insights

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.
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Developing a multi-currency Expert Advisor (Part 8): Load testing and handling a new bar

Developing a multi-currency Expert Advisor (Part 8): Load testing and handling a new bar

As we progressed, we used more and more simultaneously running instances of trading strategies in one EA. Let's try to figure out how many instances we can get to before we hit resource limitations.
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Moving to MQL5 Algo Forge (Part 3): Using External Repositories in Your Own Projects

Moving to MQL5 Algo Forge (Part 3): Using External Repositories in Your Own Projects

Let's explore how you can start integrating external code from any repository in the MQL5 Algo Forge storage into your own project. In this article, we finally turn to this promising, yet more complex, task: how to practically connect and use libraries from third-party repositories within MQL5 Algo Forge.
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From Novice to Expert: Collaborative Debugging in MQL5

From Novice to Expert: Collaborative Debugging in MQL5

Problem-solving can establish a concise routine for mastering complex skills, such as programming in MQL5. This approach allows you to concentrate on solving problems while simultaneously developing your skills. The more problems you tackle, the more advanced expertise is transferred to your brain. Personally, I believe that debugging is the most effective way to master programming. Today, we will walk through the code-cleaning process and discuss the best techniques for transforming a messy program into a clean, functional one. Read through this article and uncover valuable insights.
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Developing a multi-currency Expert Advisor (Part 15): Preparing EA for real trading

Developing a multi-currency Expert Advisor (Part 15): Preparing EA for real trading

As we gradually approach to obtaining a ready-made EA, we need to pay attention to issues that seem secondary at the stage of testing a trading strategy, but become important when moving on to real trading.
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Alternative risk return metrics in MQL5

Alternative risk return metrics in MQL5

In this article we present the implementation of several risk return metrics billed as alternatives to the Sharpe ratio and examine hypothetical equity curves to analyze their characteristics.
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Neural Networks in Trading: Node-Adaptive Graph Representation with NAFS

Neural Networks in Trading: Node-Adaptive Graph Representation with NAFS

We invite you to get acquainted with the NAFS (Node-Adaptive Feature Smoothing) method, which is a non-parametric approach to creating node representations that does not require parameter training. NAFS extracts features of each node given its neighbors and then adaptively combines these features to form a final representation.
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Implementation of the Augmented Dickey Fuller test in MQL5

Implementation of the Augmented Dickey Fuller test in MQL5

In this article we demonstrate the implementation of the Augmented Dickey-Fuller test, and apply it to conduct cointegration tests using the Engle-Granger method.
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Introduction to MQL5 (Part 21): Automating Harmonic Pattern Detection

Introduction to MQL5 (Part 21): Automating Harmonic Pattern Detection

Learn how to detect and display the Gartley harmonic pattern in MetaTrader 5 using MQL5. This article explains each step of the process, from identifying swing points to applying Fibonacci ratios and plotting the full pattern on the chart for clear visual confirmation.
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Neural Networks Made Easy (Part 95): Reducing Memory Consumption in Transformer Models

Neural Networks Made Easy (Part 95): Reducing Memory Consumption in Transformer Models

Transformer architecture-based models demonstrate high efficiency, but their use is complicated by high resource costs both at the training stage and during operation. In this article, I propose to get acquainted with algorithms that allow to reduce memory usage of such models.
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Developing a Replay System — Market simulation (Part 22): FOREX (III)

Developing a Replay System — Market simulation (Part 22): FOREX (III)

Although this is the third article on this topic, I must explain for those who have not yet understood the difference between the stock market and the foreign exchange market: the big difference is that in the Forex there is no, or rather, we are not given information about some points that actually occurred during the course of trading.
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Data Science and Machine Learning (Part 16): A Refreshing Look at Decision Trees

Data Science and Machine Learning (Part 16): A Refreshing Look at Decision Trees

Dive into the intricate world of decision trees in the latest installment of our Data Science and Machine Learning series. Tailored for traders seeking strategic insights, this article serves as a comprehensive recap, shedding light on the powerful role decision trees play in the analysis of market trends. Explore the roots and branches of these algorithmic trees, unlocking their potential to enhance your trading decisions. Join us for a refreshing perspective on decision trees and discover how they can be your allies in navigating the complexities of financial markets.
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Custom Indicator: Plotting Partial Entry, Exit and Reversal Deals for Netting Accounts

Custom Indicator: Plotting Partial Entry, Exit and Reversal Deals for Netting Accounts

In this article, we will look at a non-standard way of creating an indicator in MQL5. Instead of focusing on a trend or chart pattern, our goal will be to manage our own positions, including partial entries and exits. We will make extensive use of dynamic matrices and some trading functions related to trade history and open positions to indicate on the chart where these trades were made.
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Neural networks made easy (Part 40): Using Go-Explore on large amounts of data

Neural networks made easy (Part 40): Using Go-Explore on large amounts of data

This article discusses the use of the Go-Explore algorithm over a long training period, since the random action selection strategy may not lead to a profitable pass as training time increases.
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Formulating Dynamic Multi-Pair EA (Part 2): Portfolio Diversification and Optimization

Formulating Dynamic Multi-Pair EA (Part 2): Portfolio Diversification and Optimization

Portfolio Diversification and Optimization strategically spreads investments across multiple assets to minimize risk while selecting the ideal asset mix to maximize returns based on risk-adjusted performance metrics.
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From Novice to Expert: The Essential Journey Through MQL5 Trading

From Novice to Expert: The Essential Journey Through MQL5 Trading

Unlock your potential! You're surrounded by opportunities. Discover 3 top secrets to kickstart your MQL5 journey or take it to the next level. Let's dive into discussion of tips and tricks for beginners and pros alike.
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Neural Networks in Trading: An Agent with Layered Memory (Final Part)

Neural Networks in Trading: An Agent with Layered Memory (Final Part)

We continue our work on creating the FinMem framework, which uses layered memory approaches that mimic human cognitive processes. This allows the model not only to effectively process complex financial data but also to adapt to new signals, significantly improving the accuracy and effectiveness of investment decisions in dynamically changing markets.
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Data label for time series mining (Part 4):Interpretability Decomposition Using Label Data

Data label for time series mining (Part 4):Interpretability Decomposition Using Label Data

This series of articles introduces several time series labeling methods, which can create data that meets most artificial intelligence models, and targeted data labeling according to needs can make the trained artificial intelligence model more in line with the expected design, improve the accuracy of our model, and even help the model make a qualitative leap!
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Building A Candlestick Trend Constraint Model (Part 4): Customizing Display Style For Each Trend Wave

Building A Candlestick Trend Constraint Model (Part 4): Customizing Display Style For Each Trend Wave

In this article, we will explore the capabilities of the powerful MQL5 language in drawing various indicator styles on Meta Trader 5. We will also look at scripts and how they can be used in our model.
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Developing a Replay System (Part 37): Paving the Path (I)

Developing a Replay System (Part 37): Paving the Path (I)

In this article, we will finally begin to do what we wanted to do much earlier. However, due to the lack of "solid ground", I did not feel confident to present this part publicly. Now I have the basis to do this. I suggest that you focus as much as possible on understanding the content of this article. I mean not simply reading it. I want to emphasize that if you do not understand this article, you can completely give up hope of understanding the content of the following ones.
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Self Optimizing Expert Advisors in MQL5 (Part 13): A Gentle Introduction To Control Theory Using Matrix Factorization

Self Optimizing Expert Advisors in MQL5 (Part 13): A Gentle Introduction To Control Theory Using Matrix Factorization

Financial markets are unpredictable, and trading strategies that look profitable in the past often collapse in real market conditions. This happens because most strategies are fixed once deployed and cannot adapt or learn from their mistakes. By borrowing ideas from control theory, we can use feedback controllers to observe how our strategies interact with markets and adjust their behavior toward profitability. Our results show that adding a feedback controller to a simple moving average strategy improved profits, reduced risk, and increased efficiency, proving that this approach has strong potential for trading applications.
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DoEasy. Service functions (Part 3): Outside Bar pattern

DoEasy. Service functions (Part 3): Outside Bar pattern

In this article, we will develop the Outside Bar Price Action pattern in the DoEasy library and optimize the methods of access to price pattern management. In addition, we will fix errors and shortcomings identified during library tests.
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Neural Network in Practice: Sketching a Neuron

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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Indicator of historical positions on the chart as their profit/loss diagram

Indicator of historical positions on the chart as their profit/loss diagram

In this article, I will consider the option of obtaining information about closed positions based on their trading history. Besides, I will create a simple indicator that displays the approximate profit/loss of positions on each bar as a diagram.
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Population optimization algorithms: Differential Evolution (DE)

Population optimization algorithms: Differential Evolution (DE)

In this article, we will consider the algorithm that demonstrates the most controversial results of all those discussed previously - the differential evolution (DE) algorithm.
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Developing a Replay System (Part 51): Things Get Complicated (III)

Developing a Replay System (Part 51): Things Get Complicated (III)

In this article, we will look into one of the most difficult issues in the field of MQL5 programming: how to correctly obtain a chart ID, and why objects are sometimes not plotted on the chart. The materials presented here are for didactic purposes only. Under no circumstances should the application be viewed for any purpose other than to learn and master the concepts presented.
Superposition and Interference of Financial Securities
Superposition and Interference of Financial Securities

Superposition and Interference of Financial Securities

The more factors influence the behavior of a currency pair, the more difficult it is to evaluate its behavior and make up future forecasts. Therefore, if we managed to extract components of a currency pair, values of a national currency that change with the time, we could considerably delimit the freedom of national currency movement as compared to the currency pair with this currency, as well as the number of factors influencing its behavior. As a result we would increase the accuracy of its behavior estimation and future forecasting. How can we do that?
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Developing a Replay System — Market simulation (Part 19): Necessary adjustments

Developing a Replay System — Market simulation (Part 19): Necessary adjustments

Here we will prepare the ground so that if we need to add new functions to the code, this will happen smoothly and easily. The current code cannot yet cover or handle some of the things that will be necessary to make meaningful progress. We need everything to be structured in order to enable the implementation of certain things with the minimal effort. If we do everything correctly, we can get a truly universal system that can very easily adapt to any situation that needs to be handled.
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Population optimization algorithms: Mind Evolutionary Computation (MEC) algorithm

Population optimization algorithms: Mind Evolutionary Computation (MEC) algorithm

The article considers the algorithm of the MEC family called the simple mind evolutionary computation algorithm (Simple MEC, SMEC). The algorithm is distinguished by the beauty of its idea and ease of implementation.
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Chaos theory in trading (Part 2): Diving deeper

Chaos theory in trading (Part 2): Diving deeper

We continue our dive into chaos theory in financial markets. This time I will consider its applicability to the analysis of currencies and other assets.