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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Larry Williams Market Secrets (Part 9): Patterns to Profit

Larry Williams Market Secrets (Part 9): Patterns to Profit

An empirical study of Larry Williams' short-term trading patterns, showing how classic setups can be automated in MQL5, tested on real market data, and evaluated for consistency, profitability, and practical trading value.
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Category Theory in MQL5 (Part 15) : Functors with Graphs

Category Theory in MQL5 (Part 15) : Functors with Graphs

This article on Category Theory implementation in MQL5, continues the series by looking at Functors but this time as a bridge between Graphs and a set. We revisit calendar data, and despite its limitations in Strategy Tester use, make the case using functors in forecasting volatility with the help of correlation.
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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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Matrix Utils, Extending the Matrices and Vector Standard Library Functionality

Matrix Utils, Extending the Matrices and Vector Standard Library Functionality

Matrix serves as the foundation of machine learning algorithms and computers in general because of their ability to effectively handle large mathematical operations, The Standard library has everything one needs but let's see how we can extend it by introducing several functions in the utils file, that are not yet available in the library
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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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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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Population optimization algorithms: Artificial Bee Colony (ABC)

Population optimization algorithms: Artificial Bee Colony (ABC)

In this article, we will study the algorithm of an artificial bee colony and supplement our knowledge with new principles of studying functional spaces. In this article, I will showcase my interpretation of the classic version of the algorithm.
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DoEasy. Controls (Part 29): ScrollBar auxiliary control

DoEasy. Controls (Part 29): ScrollBar auxiliary control

In this article, I will start developing the ScrollBar auxiliary control element and its derivative objects — vertical and horizontal scrollbars. A scrollbar is used to scroll the content of the form if it goes beyond the container. Scrollbars are usually located at the bottom and to the right of the form. The horizontal one at the bottom scrolls content left and right, while the vertical one scrolls up and down.
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News Trading Made Easy (Part 5): Performing Trades (II)

News Trading Made Easy (Part 5): Performing Trades (II)

This article will expand on the trade management class to include buy-stop and sell-stop orders to trade news events and implement an expiration constraint on these orders to prevent any overnight trading. A slippage function will be embedded into the expert to try and prevent or minimize possible slippage that may occur when using stop orders in trading, especially during news events.
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From Novice to Expert: Forex Market Periods

From Novice to Expert: Forex Market Periods

Every market period has a beginning and an end, each closing with a price that defines its sentiment—much like any candlestick session. Understanding these reference points allows us to gauge the prevailing market mood, revealing whether bullish or bearish forces are in control. In this discussion, we take an important step forward by developing a new feature within the Market Periods Synchronizer—one that visualizes Forex market sessions to support more informed trading decisions. This tool can be especially powerful for identifying, in real time, which side—bulls or bears—dominates the session. Let’s explore this concept and uncover the insights it offers.
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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.
Andrey Voitenko: Programming errors cost me $15,000 (ATC 2010)
Andrey Voitenko: Programming errors cost me $15,000 (ATC 2010)

Andrey Voitenko: Programming errors cost me $15,000 (ATC 2010)

Andrey Voitenko is participating in the Automated Trading Championship for the first time, but his Expert Advisor is showing mature trading. For already several weeks Andrey's Expert Advisors has been listed in the top ten and seems to be continuing his positive performance. In this interview Andrey is telling about his EA's features, errors and the price they cost him.
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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.
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From Novice to Expert: Detecting Liquidity Zone Flips Using MQL5

From Novice to Expert: Detecting Liquidity Zone Flips Using MQL5

This article presents an MQL5 indicator that detects and manages liquidity zone flips. It identifies supply and demand zones from higher timeframes using a base–impulse pattern, applies objective breakout and impulse thresholds, and flips zones automatically when structure changes. The result is a dynamic support‑resistance map that reduces manual redraws and gives you clear, actionable context for signals and retests.
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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.
Two-Stage Modification of Opened Positions
Two-Stage Modification of Opened Positions

Two-Stage Modification of Opened Positions

The two-stage approach allows you to avoid the unnecessary closing and re-opening of positions in situations close to the trend and in cases of possible occurrence of divirgence.
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Chaos theory in trading (Part 1): Introduction, application in financial markets and Lyapunov exponent

Chaos theory in trading (Part 1): Introduction, application in financial markets and Lyapunov exponent

Can chaos theory be applied to financial markets? In this article, we will consider how conventional Chaos theory and chaotic systems are different from the concept proposed by Bill Williams.
Interview with Egidijus Bockus (ATC 2012)
Interview with Egidijus Bockus (ATC 2012)

Interview with Egidijus Bockus (ATC 2012)

"I examined many indicators before realizing that they are not necessary for making money on Forex" - our present interviewee Egidijus Bockus (Egidijus) told us boldly. We have all reasons to take his words seriously, as his Expert Advisor occupies the third place with more than $32 000 beginning from the third week of the Automated Trading Championship 2012.
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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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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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Developing a trading Expert Advisor from scratch (Part 25): Providing system robustness (II)

Developing a trading Expert Advisor from scratch (Part 25): Providing system robustness (II)

In this article, we will make the final step towards the EA's performance. So, be prepared for a long read. To make our Expert Advisor reliable, we will first remove everything from the code that is not part of the trading system.
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Market Simulation (Part 06): Transferring Information from MetaTrader 5 to Excel

Market Simulation (Part 06): Transferring Information from MetaTrader 5 to Excel

Many people, especially non=programmers, find it very difficult to transfer information between MetaTrader 5 and other programs. One such program is Excel. Many use Excel as a way to manage and maintain their risk control. It is an excellent program and easy to learn, even for those who are not VBA programmers. Here we will look at how to establish a connection between MetaTrader 5 and Excel (a very simple method).
Testing Visualization: Account State Charts
Testing Visualization: Account State Charts

Testing Visualization: Account State Charts

Enjoy the process of testing with charts, displaying the balance - now all the necessary information is always in view!
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Evolutionary trading algorithm with reinforcement learning and extinction of feeble individuals (ETARE)

Evolutionary trading algorithm with reinforcement learning and extinction of feeble individuals (ETARE)

In this article, I introduce an innovative trading algorithm that combines evolutionary algorithms with deep reinforcement learning for Forex trading. The algorithm uses the mechanism of extinction of inefficient individuals to optimize the trading strategy.
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Developing a trading Expert Advisor from scratch (Part 23): New order system (VI)

Developing a trading Expert Advisor from scratch (Part 23): New order system (VI)

We will make the order system more flexible. Here we will consider changes to the code that will make it more flexible, which will allow us to change position stop levels much faster.
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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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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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Encoding Candlestick Patterns (Part 2): Modeling Price Action as an Ordered Sequence

Encoding Candlestick Patterns (Part 2): Modeling Price Action as an Ordered Sequence

Developing permutation-based tools in MQL5 provides a systematic way to analyze candlestick pattern combinations for trading strategies. This article introduces a permutation calculator and generator designed to compute and enumerate all possible ordered candlestick sequences from bullish and bearish sets, with or without repetition. By generating exhaustive pattern combinations, traders can perform data-driven analysis to identify high-probability market patterns and improve decision-making in automated trading systems.
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MQL5 Wizard Techniques you should know (Part 56): Bill Williams Fractals

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.
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Neural Networks in Trading: Scene-Aware Object Detection (HyperDet3D)

Neural Networks in Trading: Scene-Aware Object Detection (HyperDet3D)

We invite you to get acquainted with a new approach to detecting objects using hypernetworks. A hypernetwork generates weights for the main model, which allows taking into account the specifics of the current market situation. This approach allows us to improve forecasting accuracy by adapting the model to different trading conditions.
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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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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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Reimagining Classic Strategies in Python: MA Crossovers

Reimagining Classic Strategies in Python: MA Crossovers

In this article, we revisit the classic moving average crossover strategy to assess its current effectiveness. Given the amount of time since its inception, we explore the potential enhancements that AI can bring to this traditional trading strategy. By incorporating AI techniques, we aim to leverage advanced predictive capabilities to potentially optimize trade entry and exit points, adapt to varying market conditions, and enhance overall performance compared to conventional approaches.
Market Diagnostics by Pulse
Market Diagnostics by Pulse

Market Diagnostics by Pulse

In the article, an attempt is made to visualize the intensity of specific markets and of their time segments, to detect their regularities and behavior patterns.
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Integrating ML models with the Strategy Tester (Part 3): Managing CSV files (II)

Integrating ML models with the Strategy Tester (Part 3): Managing CSV files (II)

This material provides a complete guide to creating a class in MQL5 for efficient management of CSV files. We will see the implementation of methods for opening, writing, reading, and transforming data. We will also consider how to use them to store and access information. In addition, we will discuss the limitations and the most important aspects of using such a class. This article ca be a valuable resource for those who want to learn how to process CSV files in MQL5.
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Category Theory in MQL5 (Part 3)

Category Theory in MQL5 (Part 3)

Category Theory is a diverse and expanding branch of Mathematics which as of yet is relatively uncovered in the MQL5 community. These series of articles look to introduce and examine some of its concepts with the overall goal of establishing an open library that provides insight while hopefully furthering the use of this remarkable field in Traders' strategy development.
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MQL5 Trading Tools (Part 13): Creating a Canvas-Based Price Dashboard with Graph and Stats Panels

MQL5 Trading Tools (Part 13): Creating a Canvas-Based Price Dashboard with Graph and Stats Panels

In this article, we develop a canvas-based price dashboard in MQL5 using the CCanvas class to create interactive panels for visualizing recent price graphs and account statistics, with support for background images, fog effects, and gradient fills. The system includes draggable and resizable features via mouse event handling, theme toggling between dark and light modes with dynamic color adjustments, and minimize/maximize controls for efficient chart space management.
Interview with Alexander Prishchenko (ATC 2012)
Interview with Alexander Prishchenko (ATC 2012)

Interview with Alexander Prishchenko (ATC 2012)

What can be more complicated than a multicurrency trading robot? Surely, it is an automated strategy based on Elliott Wave Principle. Can we imagine something more complicated than that? Yes, we can. It is a multicurrency Expert Advisor using Elliott Waves on each currency pair! Alexander Prishchenko (Crucian) believes that even a newcomer can learn the rules.
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From Novice to Expert: Parameter Control Utility

From Novice to Expert: Parameter Control Utility

Imagine transforming the traditional EA or indicator input properties into a real-time, on-chart control interface. This discussion builds upon our foundational work in the Market Periods Synchronizer indicator, marking a significant evolution in how we visualize and manage higher-timeframe (HTF) market structures. Here, we turn that concept into a fully interactive utility—a dashboard that brings dynamic control and enhanced multi-period price action visualization directly onto the chart. Join us as we explore how this innovation reshapes the way traders interact with their tools.
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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.