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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Risk Management (Part 2): Implementing Lot Calculation in a Graphical Interface

Risk Management (Part 2): Implementing Lot Calculation in a Graphical Interface

In this article, we will look at how to improve and more effectively apply the concepts presented in the previous article using the powerful MQL5 graphical control libraries. We'll go step by step through the process of creating a fully functional GUI. I'll be explaining the ideas behind it, as well as the purpose and operation of each method used. Additionally, at the end of the article, we will test the panel we created to ensure it functions correctly and meets its stated goals.
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Using PSAR, Heiken Ashi, and Deep Learning Together for Trading

Using PSAR, Heiken Ashi, and Deep Learning Together for Trading

This project explores the fusion of deep learning and technical analysis to test trading strategies in forex. A Python script is used for rapid experimentation, employing an ONNX model alongside traditional indicators like PSAR, SMA, and RSI to predict EUR/USD movements. A MetaTrader 5 script then brings this strategy into a live environment, using historical data and technical analysis to make informed trading decisions. The backtesting results indicate a cautious yet consistent approach, with a focus on risk management and steady growth rather than aggressive profit-seeking.
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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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Neural Networks Made Easy (Part 94): Optimizing the Input Sequence

Neural Networks Made Easy (Part 94): Optimizing the Input Sequence

When working with time series, we always use the source data in their historical sequence. But is this the best option? There is an opinion that changing the sequence of the input data will improve the efficiency of the trained models. In this article I invite you to get acquainted with one of the methods for optimizing the input sequence.
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Brute force approach to patterns search (Part V): Fresh angle

Brute force approach to patterns search (Part V): Fresh angle

In this article, I will show a completely different approach to algorithmic trading I ended up with after quite a long time. Of course, all this has to do with my brute force program, which has undergone a number of changes that allow it to solve several problems simultaneously. Nevertheless, the article has turned out to be more general and as simple as possible, which is why it is also suitable for those who know nothing about brute force.
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Data Science and Machine Learning (Part 19): Supercharge Your AI models with AdaBoost

Data Science and Machine Learning (Part 19): Supercharge Your AI models with AdaBoost

AdaBoost, a powerful boosting algorithm designed to elevate the performance of your AI models. AdaBoost, short for Adaptive Boosting, is a sophisticated ensemble learning technique that seamlessly integrates weak learners, enhancing their collective predictive strength.
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Quantum computing and trading: A fresh approach to price forecasts

Quantum computing and trading: A fresh approach to price forecasts

The article describes an innovative approach to forecasting price movements in financial markets using quantum computing. The main focus is on the application of the Quantum Phase Estimation (QPE) algorithm to find prototypes of price patterns allowing traders to significantly speed up the market data analysis.
Ten Basic Errors of a Newcomer in Trading
Ten Basic Errors of a Newcomer in Trading

Ten Basic Errors of a Newcomer in Trading

There are ten basic errors of a newcomer intrading: trading at market opening, undue hurry in taking profit, adding of lots in a losing position, closing positions starting with the best one, revenge, the most preferable positions, trading by the principle of 'bought for ever', closing of a profitable strategic position on the first day, closing of a position when alerted to open an opposite position, doubts.
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Timeseries in DoEasy library (part 50): Multi-period multi-symbol standard indicators with a shift

Timeseries in DoEasy library (part 50): Multi-period multi-symbol standard indicators with a shift

In the article, let’s improve library methods for correct display of multi-symbol multi-period standard indicators, which lines are displayed on the current symbol chart with a shift set in the settings. As well, let’s put things in order in methods of work with standard indicators and remove the redundant code to the library area in the final indicator program.
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Neural networks made easy (Part 35): Intrinsic Curiosity Module

Neural networks made easy (Part 35): Intrinsic Curiosity Module

We continue to study reinforcement learning algorithms. All the algorithms we have considered so far required the creation of a reward policy to enable the agent to evaluate each of its actions at each transition from one system state to another. However, this approach is rather artificial. In practice, there is some time lag between an action and a reward. In this article, we will get acquainted with a model training algorithm which can work with various time delays from the action to the reward.
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Data Science and ML (Part 33): Pandas Dataframe in MQL5, Data Collection for ML Usage made easier

Data Science and ML (Part 33): Pandas Dataframe in MQL5, Data Collection for ML Usage made easier

When working with machine learning models, it’s essential to ensure consistency in the data used for training, validation, and testing. In this article, we will create our own version of the Pandas library in MQL5 to ensure a unified approach for handling machine learning data, for ensuring the same data is applied inside and outside MQL5, where most of the training occurs.
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Creating Custom Indicators in MQL5 (Part 9): Order Flow Footprint Chart with Price Level Volume Tracking

Creating Custom Indicators in MQL5 (Part 9): Order Flow Footprint Chart with Price Level Volume Tracking

This article builds an order-flow footprint indicator in MQL5 that aggregates tick-by-tick volume into quantized price levels and supports Bid vs Ask and Delta display modes. A canvas overlay renders color-scaled volume text aligned with the candles and updates on every tick. You will learn sorting of price levels, max-value normalization for color mapping, and responsive redraws on zoom, scroll, and resize to read volume distribution and aggressor dominance inside each bar.
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Understand and Efficiently use OpenCL API by Recreating built-in support as DLL on Linux (Part 2): OpenCL Simple DLL implementation

Understand and Efficiently use OpenCL API by Recreating built-in support as DLL on Linux (Part 2): OpenCL Simple DLL implementation

Continued from the part 1 in the series, now we proceed to implement as a simple DLL then test with MetaTrader 5. This will prepare us well before developing a full-fledge OpenCL as DLL support in the following part to come.
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Developing a multi-currency Expert Advisor (Part 4): Pending virtual orders and saving status

Developing a multi-currency Expert Advisor (Part 4): Pending virtual orders and saving status

Having started developing a multi-currency EA, we have already achieved some results and managed to carry out several code improvement iterations. However, our EA was unable to work with pending orders and resume operation after the terminal restart. Let's add these features.
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Pipelines in MQL5

Pipelines in MQL5

In this piece, we look at a key data preparation step for machine learning that is gaining rapid significance. Data Preprocessing Pipelines. These in essence are a streamlined sequence of data transformation steps that prepare raw data before it is fed to a model. As uninteresting as this may initially seem to the uninducted, this ‘data standardization’ not only saves on training time and execution costs, but it goes a long way in ensuring better generalization. In this article we are focusing on some SCIKIT-LEARN preprocessing functions, and while we are not exploiting the MQL5 Wizard, we will return to it in coming articles.
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Integrating MQL5 with data processing packages (Part 2): Machine Learning and Predictive Analytics

Integrating MQL5 with data processing packages (Part 2): Machine Learning and Predictive Analytics

In our series on integrating MQL5 with data processing packages, we delve in to the powerful combination of machine learning and predictive analysis. We will explore how to seamlessly connect MQL5 with popular machine learning libraries, to enable sophisticated predictive models for financial markets.
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Moving to MQL5 Algo Forge (Part 2): Working with Multiple Repositories

Moving to MQL5 Algo Forge (Part 2): Working with Multiple Repositories

In this article, we are considering one of the possible approaches to organizing the storage of the project's source code in a public repository. We will distribute the code across different branches to establish clear and convenient rules for the project development.
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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.
How to Use Crashlogs to Debug Your Own DLLs
How to Use Crashlogs to Debug Your Own DLLs

How to Use Crashlogs to Debug Your Own DLLs

25 to 30% of all crashlogs received from users appear due to errors occurring when functions imported from custom dlls are executed.
Betting Modeling as Means of Developing "Market Intuition"
Betting Modeling as Means of Developing "Market Intuition"

Betting Modeling as Means of Developing "Market Intuition"

The article dwells on the notion of "market intuition" and ways of developing it. The method described in the article is based on the modeling of financial betting in the form of a simple game.
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Self Optimizing Expert Advisor With MQL5 And Python (Part V): Deep Markov Models

Self Optimizing Expert Advisor With MQL5 And Python (Part V): Deep Markov Models

In this discussion, we will apply a simple Markov Chain on an RSI Indicator, to observe how price behaves after the indicator passes through key levels. We concluded that the strongest buy and sell signals on the NZDJPY pair are generated when the RSI is in the 11-20 range and 71-80 range, respectively. We will demonstrate how you can manipulate your data, to create optimal trading strategies that are learned directly from the data you have. Furthermore, we will demonstrate how to train a deep neural network to learn to use the transition matrix optimally.
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MQL5 Wizard Techniques you should know (Part 78): Gator and AD Oscillator Strategies for Market Resilience

MQL5 Wizard Techniques you should know (Part 78): Gator and AD Oscillator Strategies for Market Resilience

The article presents the second half of a structured approach to trading with the Gator Oscillator and Accumulation/Distribution. By introducing five new patterns, the author shows how to filter false moves, detect early reversals, and align signals across timeframes. With clear coding examples and performance tests, the material bridges theory and practice for MQL5 developers.
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News Trading Made Easy (Part 6): Performing Trades (III)

News Trading Made Easy (Part 6): Performing Trades (III)

In this article news filtration for individual news events based on their IDs will be implemented. In addition, previous SQL queries will be improved to provide additional information or reduce the query's runtime. Furthermore, the code built in the previous articles will be made functional.
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Multiple Symbol Analysis With Python And MQL5 (Part 3): Triangular Exchange Rates

Multiple Symbol Analysis With Python And MQL5 (Part 3): Triangular Exchange Rates

Traders often face drawdowns from false signals, while waiting for confirmation can lead to missed opportunities. This article introduces a triangular trading strategy using Silver’s pricing in Dollars (XAGUSD) and Euros (XAGEUR), along with the EURUSD exchange rate, to filter out noise. By leveraging cross-market relationships, traders can uncover hidden sentiment and refine their entries in real time.
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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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Building A Candlestick Trend Constraint Model (Part 7): Refining our model for EA development

Building A Candlestick Trend Constraint Model (Part 7): Refining our model for EA development

In this article, we will delve into the detailed preparation of our indicator for Expert Advisor (EA) development. Our discussion will encompass further refinements to the current version of the indicator to enhance its accuracy and functionality. Additionally, we will introduce new features that mark exit points, addressing a limitation of the previous version, which only identified entry points.
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Population optimization algorithms: Cuckoo Optimization Algorithm (COA)

Population optimization algorithms: Cuckoo Optimization Algorithm (COA)

The next algorithm I will consider is cuckoo search optimization using Levy flights. This is one of the latest optimization algorithms and a new leader in the leaderboard.
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Neural Networks in Trading: Hierarchical Vector Transformer (HiVT)

Neural Networks in Trading: Hierarchical Vector Transformer (HiVT)

We invite you to get acquainted with the Hierarchical Vector Transformer (HiVT) method, which was developed for fast and accurate forecasting of multimodal time series.
Interview with Atsushi Yamanaka (ATC 2011)
Interview with Atsushi Yamanaka (ATC 2011)

Interview with Atsushi Yamanaka (ATC 2011)

What is common between skydiving, Futures, Hawaii, translations and spies? We didn't know it until we've managed to communicate with disqualified participant Atsushi Yamanaka (alohafx). His has a creed "Life is Good!", and one can hardly doubt that. It was interesting to know that distances between the continents are not an obstacle for communication among our Championship's participants.
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Reimagining Classic Strategies (Part II): Bollinger Bands Breakouts

Reimagining Classic Strategies (Part II): Bollinger Bands Breakouts

This article explores a trading strategy that integrates Linear Discriminant Analysis (LDA) with Bollinger Bands, leveraging categorical zone predictions for strategic market entry signals.
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Building a Research-Grounded Grid EA in MQL5: Why Most Grid EAs Fail and What Taranto Proved

Building a Research-Grounded Grid EA in MQL5: Why Most Grid EAs Fail and What Taranto Proved

This article implements a regime-adaptive grid trading EA based on the PhD research of Aldo Taranto. It presents a regime‑adaptive grid trading EA that constrains risk through restartable cycles and equity‑based safeguards. We explain why naive grids fail (variance growth and almost‑sure ruin), derive the loss formula for real‑time exposure, and implement regime‑aware gating, ATR‑dynamic spacing, and a live kill switch. Readers get the mathematical tools and production patterns needed to build, test, and operate a constrained grid safely.
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Developing a Replay System (Part 78): New Chart Trade (V)

Developing a Replay System (Part 78): New Chart Trade (V)

In this article, we will look at how to implement part of the receiver code. Here we will implement an Expert Advisor to test and learn how the protocol interaction works. 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.
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Market Simulation (Part 18): First Steps with SQL (I)

Market Simulation (Part 18): First Steps with SQL (I)

It doesn't matter which SQL program we use: MySQL, SQL Server, SQLite, OpenSQL, or another. They all have something in common, and the common element is the SQL language. Even if we do not intend to use Workbench, we can manipulate or work with the database directly in MetaEditor or through MQL5 to perform actions in MetaTrader 5, but to do so, you will need knowledge of SQL. So here, we will learn at least the basics.
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Neural networks made easy (Part 44): Learning skills with dynamics in mind

Neural networks made easy (Part 44): Learning skills with dynamics in mind

In the previous article, we introduced the DIAYN method, which offers the algorithm for learning a variety of skills. The acquired skills can be used for various tasks. But such skills can be quite unpredictable, which can make them difficult to use. In this article, we will look at an algorithm for learning predictable skills.
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DoEasy. Controls (Part 30): Animating the ScrollBar control

DoEasy. Controls (Part 30): Animating the ScrollBar control

In this article, I will continue the development of the ScrollBar control and start implementing the mouse interaction functionality. In addition, I will expand the lists of mouse state flags and events.
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Creating Custom Indicators in MQL5 (Part 4): Smart WaveTrend Crossover with Dual Oscillators

Creating Custom Indicators in MQL5 (Part 4): Smart WaveTrend Crossover with Dual Oscillators

In this article, we develop a custom indicator in MQL5 called Smart WaveTrend Crossover, utilizing dual WaveTrend oscillators—one for generating crossover signals and another for trend filtering—with customizable parameters for channel, average, and moving average lengths. The indicator plots colored candles based on the trend direction, displays buy and sell arrow signals on crossovers, and includes options to enable trend confirmation and adjust visual elements like colors and offsets.
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Data Science and Machine Learning (Part 17): Money in the Trees? The Art and Science of Random Forests in Forex Trading

Data Science and Machine Learning (Part 17): Money in the Trees? The Art and Science of Random Forests in Forex Trading

Discover the secrets of algorithmic alchemy as we guide you through the blend of artistry and precision in decoding financial landscapes. Unearth how Random Forests transform data into predictive prowess, offering a unique perspective on navigating the complex terrain of stock markets. Join us on this journey into the heart of financial wizardry, where we demystify the role of Random Forests in shaping market destiny and unlocking the doors to lucrative opportunities
Interview with Francisco García García (ATC 2012)
Interview with Francisco García García (ATC 2012)

Interview with Francisco García García (ATC 2012)

Today we interview Francisco García García (chuliweb) from Spain. A week ago his Expert Advisor reached the 8th place, but the unfortunate logic error in programming threw it from the first page of the Championship leaders. As confirmed by statistics, such an error is not uncommon for many participants.
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Data Science and ML (Part 31): Using CatBoost AI Models for Trading

Data Science and ML (Part 31): Using CatBoost AI Models for Trading

CatBoost AI models have gained massive popularity recently among machine learning communities due to their predictive accuracy, efficiency, and robustness to scattered and difficult datasets. In this article, we are going to discuss in detail how to implement these types of models in an attempt to beat the forex market.
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Pure implementation of RSA encryption in MQL5

Pure implementation of RSA encryption in MQL5

MQL5 lacks built-in asymmetric cryptography, making secure data exchange over insecure channels like HTTP difficult. This article presents a pure MQL5 implementation of RSA using PKCS#1 v1.5 padding, enabling safe transmission of AES session keys and small data blocks without external libraries. This approach provides HTTPS-like security over standard HTTP and even more, it fills an important gap in secure communication for MQL5 applications.