Articles on manual and algorithmic trading in MetaTrader 5

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This category features articles on all aspects of trading - from manual to fully automatic trading, from Expert Advisor ideas to trading robot creation using the MQL5 Wizard. Position management, processing of trade events and money management - these integral parts of trading are covered in theses articles.

Learn how to copy trading signals and how to provide around-the-clock operation of Expert Advisors, how to create a trading robot and how to run MetaTrader on Linux and MacOS, what social trading is and how to order a trading robot.

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Creating an EA that works automatically (Part 07): Account types (II)

Creating an EA that works automatically (Part 07): Account types (II)

Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. The trader should always be aware of what the automatic EA is doing, so that if it "goes off the rails", the trader could remove it from the chart as soon as possible and take control of the situation.
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Developing a trading Expert Advisor from scratch (Part 24): Providing system robustness (I)

Developing a trading Expert Advisor from scratch (Part 24): Providing system robustness (I)

In this article, we will make the system more reliable to ensure a robust and secure use. One of the ways to achieve the desired robustness is to try to re-use the code as much as possible so that it is constantly tested in different cases. But this is only one of the ways. Another one is to use OOP.
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Improve Your Trading Charts With Interactive GUI's in MQL5 (Part I): Movable GUI (I)

Improve Your Trading Charts With Interactive GUI's in MQL5 (Part I): Movable GUI (I)

Unleash the power of dynamic data representation in your trading strategies or utilities with our comprehensive guide on creating movable GUI in MQL5. Dive into the core concept of chart events and learn how to design and implement simple and multiple movable GUI on the same chart. This article also explores the process of adding elements to your GUI, enhancing their functionality and aesthetic appeal.
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Design Patterns in software development and MQL5 (Part 3): Behavioral Patterns 1

Design Patterns in software development and MQL5 (Part 3): Behavioral Patterns 1

A new article from Design Patterns articles and we will take a look at one of its types which is behavioral patterns to understand how we can build communication methods between created objects effectively. By completing these Behavior patterns we will be able to understand how we can create and build a reusable, extendable, tested software.
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Data Science and Machine Learning (Part 18): The battle of Mastering Market Complexity, Truncated SVD Versus NMF

Data Science and Machine Learning (Part 18): The battle of Mastering Market Complexity, Truncated SVD Versus NMF

Truncated Singular Value Decomposition (SVD) and Non-Negative Matrix Factorization (NMF) are dimensionality reduction techniques. They both play significant roles in shaping data-driven trading strategies. Discover the art of dimensionality reduction, unraveling insights, and optimizing quantitative analyses for an informed approach to navigating the intricacies of financial markets.
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Discrete Hartley transform

Discrete Hartley transform

In this article, we will consider one of the methods of spectral analysis and signal processing - the discrete Hartley transform. It allows filtering signals, analyzing their spectrum and much more. The capabilities of DHT are no less than those of the discrete Fourier transform. However, unlike DFT, DHT uses only real numbers, which makes it more convenient for implementation in practice, and the results of its application are more visual.
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ALGLIB numerical analysis library in MQL5

ALGLIB numerical analysis library in MQL5

The article takes a quick look at the ALGLIB 3.19 numerical analysis library, its applications and new algorithms that can improve the efficiency of financial data analysis.
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Deep Learning GRU model with Python to ONNX  with EA, and GRU vs LSTM models

Deep Learning GRU model with Python to ONNX with EA, and GRU vs LSTM models

We will guide you through the entire process of DL with python to make a GRU ONNX model, culminating in the creation of an Expert Advisor (EA) designed for trading, and subsequently comparing GRU model with LSTN model.
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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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Developing a trading Expert Advisor from scratch (Part 27): Towards the future (II)

Developing a trading Expert Advisor from scratch (Part 27): Towards the future (II)

Let's move on to a more complete order system directly on the chart. In this article, I will show a way to fix the order system, or rather, to make it more intuitive.
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Design Patterns in software development and MQL5 (Part I): Creational Patterns

Design Patterns in software development and MQL5 (Part I): Creational Patterns

There are methods that can be used to solve many problems that can be repeated. Once understand how to use these methods it can be very helpful to create your software effectively and apply the concept of DRY ((Do not Repeat Yourself). In this context, the topic of Design Patterns will serve very well because they are patterns that provide solutions to well-described and repeated problems.
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Developing a Replay System (Part 27): Expert Advisor project — C_Mouse class (I)

Developing a Replay System (Part 27): Expert Advisor project — C_Mouse class (I)

In this article we will implement the C_Mouse class. It provides the ability to program at the highest level. However, talking about high-level or low-level programming languages is not about including obscene words or jargon in the code. It's the other way around. When we talk about high-level or low-level programming, we mean how easy or difficult the code is for other programmers to understand.
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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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Integrate Your Own LLM into EA (Part 2): Example of Environment Deployment

Integrate Your Own LLM into EA (Part 2): Example of Environment Deployment

With the rapid development of artificial intelligence today, language models (LLMs) are an important part of artificial intelligence, so we should think about how to integrate powerful LLMs into our algorithmic trading. For most people, it is difficult to fine-tune these powerful models according to their needs, deploy them locally, and then apply them to algorithmic trading. This series of articles will take a step-by-step approach to achieve this goal.
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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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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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Developing a trading Expert Advisor from scratch (Part 26): Towards the future (I)

Developing a trading Expert Advisor from scratch (Part 26): Towards the future (I)

Today we will take our order system to the next level. But before that, we need to solve a few problems. Now we have some questions that are related to how we want to work and what things we do during the trading day.
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Automated exchange grid trading using stop pending orders on Moscow Exchange (MOEX)

Automated exchange grid trading using stop pending orders on Moscow Exchange (MOEX)

The article considers the grid trading approach based on stop pending orders and implemented in an MQL5 Expert Advisor on the Moscow Exchange (MOEX). When trading in the market, one of the simplest strategies is a grid of orders designed to "catch" the market price.
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Developing a Replay System — Market simulation (Part 14): Birth of the SIMULATOR (IV)

Developing a Replay System — Market simulation (Part 14): Birth of the SIMULATOR (IV)

In this article we will continue the simulator development stage. this time we will see how to effectively create a RANDOM WALK type movement. This type of movement is very intriguing because it forms the basis of everything that happens in the capital market. In addition, we will begin to understand some concepts that are fundamental to those conducting market analysis.
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Developing a Replay System — Market simulation (Part 11): Birth of the SIMULATOR (I)

Developing a Replay System — Market simulation (Part 11): Birth of the SIMULATOR (I)

In order to use the data that forms the bars, we must abandon replay and start developing a simulator. We will use 1 minute bars because they offer the least amount of difficulty.
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How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 7): ZigZag with Awesome Oscillator Indicators Signal

How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 7): ZigZag with Awesome Oscillator Indicators Signal

The multi-currency expert advisor in this article is an expert advisor or automated trading that uses ZigZag indicator which are filtered with the Awesome Oscillator or filter each other's signals.
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Market Reactions and Trading Strategies in Response to Dividend Announcements: Evaluating the Efficient Market Hypothesis in Stock Trading

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.
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Benefiting from Forex market seasonality

Benefiting from Forex market seasonality

We are all familiar with the concept of seasonality, for example, we are all accustomed to rising prices for fresh vegetables in winter or rising fuel prices during severe frosts, but few people know that similar patterns exist in the Forex market.
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Developing a Replay System — Market simulation (Part 13): Birth of the SIMULATOR (III)

Developing a Replay System — Market simulation (Part 13): Birth of the SIMULATOR (III)

Here we will simplify a few elements related to the work in the next article. I'll also explain how you can visualize what the simulator generates in terms of randomness.
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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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Integrate Your Own LLM into EA (Part 1): Hardware and Environment Deployment

Integrate Your Own LLM into EA (Part 1): Hardware and Environment Deployment

With the rapid development of artificial intelligence today, language models (LLMs) are an important part of artificial intelligence, so we should think about how to integrate powerful LLMs into our algorithmic trading. For most people, it is difficult to fine-tune these powerful models according to their needs, deploy them locally, and then apply them to algorithmic trading. This series of articles will take a step-by-step approach to achieve this goal.
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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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Developing a Replay System — Market simulation (Part 24): FOREX (V)

Developing a Replay System — Market simulation (Part 24): FOREX (V)

Today we will remove a limitation that has been preventing simulations based on the Last price and will introduce a new entry point specifically for this type of simulation. The entire operating mechanism will be based on the principles of the forex market. The main difference in this procedure is the separation of Bid and Last simulations. However, it is important to note that the methodology used to randomize the time and adjust it to be compatible with the C_Replay class remains identical in both simulations. This is good because changes in one mode lead to automatic improvements in the other, especially when it comes to handling time between ticks.
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Developing a Replay System — Market simulation (Part 12): Birth of the SIMULATOR (II)

Developing a Replay System — Market simulation (Part 12): Birth of the SIMULATOR (II)

Developing a simulator can be much more interesting than it seems. Today we'll take a few more steps in this direction because things are getting more interesting.
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Introduction to MQL5 (Part 2): Navigating Predefined Variables, Common Functions, and  Control Flow Statements

Introduction to MQL5 (Part 2): Navigating Predefined Variables, Common Functions, and Control Flow Statements

Embark on an illuminating journey with Part Two of our MQL5 series. These articles are not just tutorials, they're doorways to an enchanted realm where programming novices and wizards alike unite. What makes this journey truly magical? Part Two of our MQL5 series stands out with its refreshing simplicity, making complex concepts accessible to all. Engage with us interactively as we answer your questions, ensuring an enriching and personalized learning experience. Let's build a community where understanding MQL5 is an adventure for everyone. Welcome to the enchantment!
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Data Science and Machine Learning (Part 20): Algorithmic Trading Insights, A Faceoff Between LDA and PCA in MQL5

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,
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Design Patterns in software development and MQL5 (Part 2): Structural Patterns

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.
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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 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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Introduction to MQL5 (Part 6): A Beginner's Guide to Array Functions in MQL5

Introduction to MQL5 (Part 6): A Beginner's Guide to Array Functions in MQL5

Embark on the next phase of our MQL5 journey. In this insightful and beginner-friendly article, we'll look into the remaining array functions, demystifying complex concepts to empower you to craft efficient trading strategies. We’ll be discussing ArrayPrint, ArrayInsert, ArraySize, ArrayRange, ArrarRemove, ArraySwap, ArrayReverse, and ArraySort. Elevate your algorithmic trading expertise with these essential array functions. Join us on the path to MQL5 mastery!
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Developing a Replay System (Part 28): Expert Advisor project — C_Mouse class (II)

Developing a Replay System (Part 28): Expert Advisor project — C_Mouse class (II)

When people started creating the first systems capable of computing, everything required the participation of engineers, who had to know the project very well. We are talking about the dawn of computer technology, a time when there were not even terminals for programming. As it developed and more people got interested in being able to create something, new ideas and ways of programming emerged which replaced the previous-style changing of connector positions. This is when the first terminals appeared.
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Advanced Variables and Data Types in MQL5

Advanced Variables and Data Types in MQL5

Variables and data types are very important topics not only in MQL5 programming but also in any programming language. MQL5 variables and data types can be categorized as simple and advanced ones. In this article, we will identify and learn about advanced ones because we already mentioned simple ones in a previous article.
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Developing a Replay System — Market simulation (Part 25): Preparing for the next phase

Developing a Replay System — Market simulation (Part 25): Preparing for the next phase

In this article, we complete the first phase of developing our replay and simulation system. Dear reader, with this achievement I confirm that the system has reached an advanced level, paving the way for the introduction of new functionality. The goal is to enrich the system even further, turning it into a powerful tool for research and development of market analysis.
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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
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Developing a Replay System — Market simulation (Part 07): First improvements (II)

Developing a Replay System — Market simulation (Part 07): First improvements (II)

In the previous article, we made some fixes and added tests to our replication system to ensure the best possible stability. We also started creating and using a configuration file for this system.