MQL4 and MQL5 Programming Articles
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 (Part 74): New Chart Trade (I)
In this article, we will modify the last code shown in this series about Chart Trade. These changes are necessary to adapt the code to the current replay/simulation system model. 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.
Websockets for MetaTrader 5: Asynchronous client connections with the Windows API
This article details the development of a custom dynamically linked library designed to facilitate asynchronous websocket client connections for MetaTrader programs.
Category Theory in MQL5 (Part 7): Multi, Relative and Indexed Domains
Category Theory is a diverse and expanding branch of Mathematics which is only recently getting some coverage in the MQL5 community. These series of articles look to explore and examine some of its concepts & axioms with the overall goal of establishing an open library that provides insight while also hopefully furthering the use of this remarkable field in Traders' strategy development.
DoEasy. Controls (Part 22): SplitContainer. Changing the properties of the created object
In the current article, I will implement the ability to change the properties and appearance of the newly created SplitContainer control.
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.
Combine Fundamental And Technical Analysis Strategies in MQL5 For Beginners
In this article, we will discuss how to integrate trend following and fundamental principles seamlessly into one Expert Advisors to build a strategy that is more robust. This article will demonstrate how easy it is for anyone to get up and running building customized trading algorithms using MQL5.
MQL5 Wizard Techniques you should know (Part 37): Gaussian Process Regression with Linear and Matérn Kernels
Linear Kernels are the simplest matrix of its kind used in machine learning for linear regression and support vector machines. The Matérn kernel on the other hand is a more versatile version of the Radial Basis Function we looked at in an earlier article, and it is adept at mapping functions that are not as smooth as the RBF would assume. We build a custom signal class that utilizes both kernels in forecasting long and short conditions.
Developing a Replay System (Part 32): Order System (I)
Of all the things that we have developed so far, this system, as you will probably notice and eventually agree, is the most complex. Now we need to do something very simple: make our system simulate the operation of a trading server. This need to accurately implement the way the trading server operates seems like a no-brainer. At least in words. But we need to do this so that the everything is seamless and transparent for the user of the replay/simulation system.
Interview with Vitaly Antonov (ATC 2011)
It was only this summer that Vitaly Antonov (beast) has learned about the upcoming Automated Trading Championship and got to know MetaTrader 5 terminal. Time was running out, besides, Vitaly was a newcomer. So, he randomly chose GBPUSD currency pair to develop his trading system. And the choice turned out to be successful. It would have been impossible to use other symbols with the strategy.
Neural Networks in Trading: Unified Trajectory Generation Model (UniTraj)
Understanding agent behavior is important in many different areas, but most methods focus on just one of the tasks (understanding, noise removal, or prediction), which reduces their effectiveness in real-world scenarios. In this article, we will get acquainted with a model that can adapt to solving various problems.
Turtle Shell Evolution Algorithm (TSEA)
This is a unique optimization algorithm inspired by the evolution of the turtle shell. The TSEA algorithm emulates the gradual formation of keratinized skin areas, which represent optimal solutions to a problem. The best solutions become "harder" and are located closer to the outer surface, while the less successful solutions remain "softer" and are located inside. The algorithm uses clustering of solutions by quality and distance, allowing to preserve less successful options and providing flexibility and adaptability.
Design Patterns in software development and MQL5 (Part 2): Structural Patterns
In this article, we will continue our articles about Design Patterns after learning how much this topic is more important for us as developers to develop extendable, reliable applications not only by the MQL5 programming language but others as well. We will learn about another type of Design Patterns which is the structural one to learn how to design systems by using what we have as classes to form larger structures.
Market Reactions and Trading Strategies in Response to Dividend Announcements: Evaluating the Efficient Market Hypothesis in Stock Trading
In this article, we will analyse the impact of dividend announcements on stock market returns and see how investors can earn more returns than those offered by the market when they expect a company to announce dividends. In doing so, we will also check the validity of the Efficient Market Hypothesis in the context of the Indian Stock Market.
Statistical Arbitrage Through Cointegrated Stocks (Part 2): Expert Advisor, Backtests, and Optimization
This article presents a sample Expert Advisor implementation for trading a basket of four Nasdaq stocks. The stocks were initially filtered based on Pearson correlation tests. The filtered group was then tested for cointegration with Johansen tests. Finally, the cointegrated spread was tested for stationarity with the ADF and KPSS tests. Here we will see some notes about this process and the results of the backtests after a small optimization.
Reusing Invalidated Orderblocks As Mitigation Blocks (SMC)
In this article, we explore how previously invalidated orderblocks can be reused as mitigation blocks within Smart Money Concepts (SMC). These zones reveal where institutional traders re-enter the market after a failed orderblock, providing high-probability areas for trade continuation in the dominant trend.
DoEasy. Controls (Part 21): SplitContainer control. Panel separator
In this article, I will create the class of an auxiliary panel separator object for the SplitContainer control.
Interview with Antonio Morillas (ATC 2011)
Antonio Morillas from Spain (sallirom, by the way - it is reversed surname!) was first who doubled his starting balance from the beginning of the Championship and thus attracted our attention. His trading strategy is extremely risky. We decided to talk to Antonio about risk and luck as these are part and parcel of Automated Trading Championship.
From Basic to Intermediate: Template and Typename (I)
In this article, we start considering one of the concepts that many beginners avoid. This is related to the fact that templates are not an easy topic, as many do not understand the basic principle underlying the template: overload of functions and procedures.
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.
Price Action Analysis Toolkit Development (Part 8): Metrics Board
As one of the most powerful Price Action analysis toolkits, the Metrics Board is designed to streamline market analysis by instantly providing essential market metrics with just a click of a button. Each button serves a specific function, whether it’s analyzing high/low trends, volume, or other key indicators. This tool delivers accurate, real-time data when you need it most. Let’s dive deeper into its features in this article.
Data Science and Machine Learning (Part 20): Algorithmic Trading Insights, A Faceoff Between LDA and PCA in MQL5
Uncover the secrets behind these powerful dimensionality reduction techniques as we dissect their applications within the MQL5 trading environment. Delve into the nuances of Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA), gaining a profound understanding of their impact on strategy development and market analysis.
MetaTrader 5 Machine Learning Blueprint (Part 11): Kelly Criterion, Prop Firm Integration, and CPCV Dynamic Backtesting
The bet-sizing signal from Part 10 is concurrency-corrected but carries no payoff-ratio adjustment, no response to a hard drawdown budget, and no validation across combinatorial paths. This article covers three additions: a two-stage architecture in which a Kelly payoff multiplier is applied on top of get_signal, preserving the concurrency correction while incorporating win/loss asymmetry; a prop firm integration layer that calibrates the sigmoid w parameter continuously from the remaining drawdown budget under FundedNext Stellar 2-Step rules; and a CPCV backtest framework that simulates a fresh account state across all φ[N, k] paths, producing a Sharpe distribution and a PBO audit.
Codex Pipelines: From Python to MQL5 for Indicator Selection — A Multi-Quarter Analysis of the FXI ETF
We continue our look at how MetaTrader can be used outside its forex trading ‘comfort-zone’ by looking at another tradable asset in the form of the FXI ETF. Unlike in the last article where we tried to do ‘too-much’ by delving into not just indicator selection, but also considering indicator pattern combinations, for this article we will swim slightly upstream by focusing more on indicator selection. Our end product for this is intended as a form of pipeline that can help recommend indicators for various assets, provided we have a reasonable amount of their price history.
Archery Algorithm (AA)
The article takes a detailed look at the archery-inspired optimization algorithm, with an emphasis on using the roulette method as a mechanism for selecting promising areas for "arrows". The method allows evaluating the quality of solutions and selecting the most promising positions for further study.
MetaTrader 5 Machine Learning Blueprint (Part 6): Engineering a Production-Grade Caching System
Tired of watching progress bars instead of testing trading strategies? Traditional caching fails financial ML, leaving you with lost computations and frustrating restarts. We've engineered a sophisticated caching architecture that understands the unique challenges of financial data—temporal dependencies, complex data structures, and the constant threat of look-ahead bias. Our three-layer system delivers dramatic speed improvements while automatically invalidating stale results and preventing costly data leaks. Stop waiting for computations and start iterating at the pace the markets demand.
Price Action Analysis Toolkit Development (Part 8): Metrics Board
As one of the most powerful Price Action analysis toolkits, the Metrics Board is designed to streamline market analysis by instantly providing essential market metrics with just a click of a button. Each button serves a specific function, whether it’s analyzing high/low trends, volume, or other key indicators. This tool delivers accurate, real-time data when you need it most. Let’s dive deeper into its features in this article.
Archery Algorithm (AA)
The article takes a detailed look at the archery-inspired optimization algorithm, with an emphasis on using the roulette method as a mechanism for selecting promising areas for "arrows". The method allows evaluating the quality of solutions and selecting the most promising positions for further study.
Data Science and ML (Part 46): Stock Markets Forecasting Using N-BEATS in Python
N-BEATS is a revolutionary deep learning model designed for time series forecasting. It was released to surpass classical models for time series forecasting such as ARIMA, PROPHET, VAR, etc. In this article, we are going to discuss this model and use it in predicting the stock market.
Creating a Trading Administrator Panel in MQL5 (Part VI):Trade Management Panel (II)
In this article, we enhance the Trade Management Panel of our multi-functional Admin Panel. We introduce a powerful helper function that simplifies the code, improving readability, maintainability, and efficiency. We will also demonstrate how to seamlessly integrate additional buttons and enhance the interface to handle a wider range of trading tasks. Whether managing positions, adjusting orders, or simplifying user interactions, this guide will help you develop a robust, user-friendly Trade Management Panel.
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.
Trading with the MQL5 Economic Calendar (Part 7): Preparing for Strategy Testing with Resource-Based News Event Analysis
In this article, we prepare our MQL5 trading system for strategy testing by embedding economic calendar data as a resource for non-live analysis. We implement event loading and filtering for time, currency, and impact, then validate it in the Strategy Tester. This enables effective backtesting of news-driven strategies.
Elastic net regression using coordinate descent in MQL5
In this article we explore the practical implementation of elastic net regression to minimize overfitting and at the same time automatically separate useful predictors from those that have little prognostic power.
Interview with Boris Odintsov (ATC 2010)
Boris Odintsov is one of the most impressive participants of the Championship who managed to go beyond $100,000 on the third week of the competition. Boris explains the rapid rise of his expert Advisor as a favorable combination of circumstances. In this interview he tells about what is important in trading, and what market would be unfavorable for his EA.
ATC Champions League: Interview with Olexandr Topchylo (ATC 2011)
Interview with Olexandr Topchylo (Better) is the second publication within the "ATC Champions League" project. Having won the Automated Trading Championship 2007, this professional trader caught the attention of investors. Olexandr says that his first place in the ATC 2007 is one of the major events of his trading experience. However, later on this popularity helped him discover the biggest disappointment - it is so easy to lose investors after the first drawdown on an investor account.
Grouped File Operations
It is sometimes necessary to perform identical operations with a group of files. If you have a list of files included into a group, then it is no problem. However, if you need to make this list yourself, then a question arises: "How can I do this?" The article proposes doing this using functions FindFirstFile() and FindNextFile() included in kernel32.dll.
Trading with the MQL5 Economic Calendar (Part 7): Preparing for Strategy Testing with Resource-Based News Event Analysis
In this article, we prepare our MQL5 trading system for strategy testing by embedding economic calendar data as a resource for non-live analysis. We implement event loading and filtering for time, currency, and impact, then validate it in the Strategy Tester. This enables effective backtesting of news-driven strategies.
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.
From Simple Close Buttons to a Rule-Based Risk Dashboard in MQL5
Build a rule-based on-chart risk management panel in MetaTrader 5 using the MQL5 Standard Library. The guide covers a CAppDialog-based GUI, manual event routing, and an automated update loop. You will bind UI events to CTrade to execute conditional closures, show net floating P/L, and read automated targets directly from the chart.
Developing a Replay System (Part 48): Understanding the concept of a service
How about learning something new? In this article, you will learn how to convert scripts into services and why it is useful to do so.
ATC Champions League: Interview with Roman Zamozhniy (ATC 2011)
This is the first interview in the "ATC Champions League" project. Roman Zamozhniy (Rich) from Ukraine was the winner of the first Automated Trading Championship in 2006. In addition, he is a regular participant of our Championships - he has not missed a single contest. In this interview, we talked about Roman's first place and tried to figure out what is necessary for successful participation.