Articles on trading system automation in MQL5

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Read articles on the trading systems with a wide variety of ideas at the core. Learn how to use statistical methods and patterns on candlestick charts, how to filter signals and where to use semaphore indicators.

The MQL5 Wizard will help you create robots without programming to quickly check your trading ideas. Use the Wizard to learn about genetic algorithms.

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Building A Candlestick Trend Constraint Model (Part 5): Notification System (Part II)

Building A Candlestick Trend Constraint Model (Part 5): Notification System (Part II)

Today, we are discussing a working Telegram integration for MetaTrader 5 Indicator notifications using the power of MQL5, in partnership with Python and the Telegram Bot API. We will explain everything in detail so that no one misses any point. By the end of this project, you will have gained valuable insights to apply in your projects.
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Integrate Your Own LLM into EA (Part 4): Training Your Own LLM with GPU

Integrate Your Own LLM into EA (Part 4): Training Your Own LLM with GPU

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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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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Multibot in MetaTrader (Part II): Improved dynamic template

Multibot in MetaTrader (Part II): Improved dynamic template

Developing the theme of the previous article, I decided to create a more flexible and functional template that has greater capabilities and can be effectively used both in freelancing and as a base for developing multi-currency and multi-period EAs with the ability to integrate with external solutions.
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Building A Candlestick Trend Constraint Model (Part 5): Notification System (Part I)

Building A Candlestick Trend Constraint Model (Part 5): Notification System (Part I)

We will breakdown the main MQL5 code into specified code snippets to illustrate the integration of Telegram and WhatsApp for receiving signal notifications from the Trend Constraint indicator we are creating in this article series. This will help traders, both novices and experienced developers, grasp the concept easily. First, we will cover the setup of MetaTrader 5 for notifications and its significance to the user. This will help developers in advance to take notes to further apply in their systems.
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How to earn money by fulfilling traders' orders in the Freelance service

How to earn money by fulfilling traders' orders in the Freelance service

MQL5 Freelance is an online service where developers are paid to create trading applications for traders customers. The service has been successfully operating since 2010, with over 100,000 projects completed to date, totaling $7 million in value. As we can see, a substantial amount of money is involved here.
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Neural networks made easy (Part 76): Exploring diverse interaction patterns with Multi-future Transformer

Neural networks made easy (Part 76): Exploring diverse interaction patterns with Multi-future Transformer

This article continues the topic of predicting the upcoming price movement. I invite you to get acquainted with the Multi-future Transformer architecture. Its main idea is to decompose the multimodal distribution of the future into several unimodal distributions, which allows you to effectively simulate various models of interaction between agents on the scene.
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Neural networks made easy (Part 75): Improving the performance of trajectory prediction models

Neural networks made easy (Part 75): Improving the performance of trajectory prediction models

The models we create are becoming larger and more complex. This increases the costs of not only their training as well as operation. However, the time required to make a decision is often critical. In this regard, let us consider methods for optimizing model performance without loss of quality.
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Neural networks made easy (Part 74): Trajectory prediction with adaptation

Neural networks made easy (Part 74): Trajectory prediction with adaptation

This article introduces a fairly effective method of multi-agent trajectory forecasting, which is able to adapt to various environmental conditions.
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Developing a multi-currency Expert Advisor (Part 3): Architecture revision

Developing a multi-currency Expert Advisor (Part 3): Architecture revision

We have already made some progress in developing a multi-currency EA with several strategies working in parallel. Considering the accumulated experience, let's review the architecture of our solution and try to improve it before we go too far ahead.
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MQL5 Trading Toolkit (Part 1): Developing A Positions Management EX5 Library

MQL5 Trading Toolkit (Part 1): Developing A Positions Management EX5 Library

Learn how to create a developer's toolkit for managing various position operations with MQL5. In this article, I will demonstrate how to create a library of functions (ex5) that will perform simple to advanced position management operations, including automatic handling and reporting of the different errors that arise when dealing with position management tasks with MQL5.
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A Step-by-Step Guide on Trading the Break of Structure (BoS) Strategy

A Step-by-Step Guide on Trading the Break of Structure (BoS) Strategy

A comprehensive guide to developing an automated trading algorithm based on the Break of Structure (BoS) strategy. Detailed information on all aspects of creating an advisor in MQL5 and testing it in MetaTrader 5 — from analyzing price support and resistance to risk management
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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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MQL5 Wizard Techniques you should know (Part 22): Conditional GANs

MQL5 Wizard Techniques you should know (Part 22): Conditional GANs

Generative Adversarial Networks are a pairing of Neural Networks that train off of each other for more accurate results. We adopt the conditional type of these networks as we look to possible application in forecasting Financial time series within an Expert Signal Class.
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Neural networks made easy (Part 73): AutoBots for predicting price movements

Neural networks made easy (Part 73): AutoBots for predicting price movements

We continue to discuss algorithms for training trajectory prediction models. In this article, we will get acquainted with a method called "AutoBots".
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Neural networks made easy (Part 72): Trajectory prediction in noisy environments

Neural networks made easy (Part 72): Trajectory prediction in noisy environments

The quality of future state predictions plays an important role in the Goal-Conditioned Predictive Coding method, which we discussed in the previous article. In this article I want to introduce you to an algorithm that can significantly improve the prediction quality in stochastic environments, such as financial markets.
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News Trading Made Easy (Part 2): Risk Management

News Trading Made Easy (Part 2): Risk Management

In this article, inheritance will be introduced into our previous and new code. A new database design will be implemented to provide efficiency. Additionally, a risk management class will be created to tackle volume calculations.
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Developing a multi-currency Expert Advisor (Part 2): Transition to virtual positions of trading strategies

Developing a multi-currency Expert Advisor (Part 2): Transition to virtual positions of trading strategies

Let's continue developing a multi-currency EA with several strategies working in parallel. Let's try to move all the work associated with opening market positions from the strategy level to the level of the EA managing the strategies. The strategies themselves will trade only virtually, without opening market positions.
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MQL5 Wizard Techniques you should know (Part 21): Testing with Economic Calendar Data

MQL5 Wizard Techniques you should know (Part 21): Testing with Economic Calendar Data

Economic Calendar Data is not available for testing with Expert Advisors within Strategy Tester, by default. We look at how Databases could help in providing a work around this limitation. So, for this article we explore how SQLite databases can be used to archive Economic Calendar news such that wizard assembled Expert Advisors can use this to generate trade signals.
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Neural networks made easy (Part 71): Goal-Conditioned Predictive Coding (GCPC)

Neural networks made easy (Part 71): Goal-Conditioned Predictive Coding (GCPC)

In previous articles, we discussed the Decision Transformer method and several algorithms derived from it. We experimented with different goal setting methods. During the experiments, we worked with various ways of setting goals. However, the model's study of the earlier passed trajectory always remained outside our attention. In this article. I want to introduce you to a method that fills this gap.
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Modified Grid-Hedge EA in MQL5 (Part IV): Optimizing Simple Grid Strategy (I)

Modified Grid-Hedge EA in MQL5 (Part IV): Optimizing Simple Grid Strategy (I)

In this fourth part, we revisit the Simple Hedge and Simple Grid Expert Advisors (EAs) developed earlier. Our focus shifts to refining the Simple Grid EA through mathematical analysis and a brute force approach, aiming for optimal strategy usage. This article delves deep into the mathematical optimization of the strategy, setting the stage for future exploration of coding-based optimization in later installments.
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Neural networks made easy (Part 70): Closed-Form Policy Improvement Operators (CFPI)

Neural networks made easy (Part 70): Closed-Form Policy Improvement Operators (CFPI)

In this article, we will get acquainted with an algorithm that uses closed-form policy improvement operators to optimize Agent actions in offline mode.
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Causal inference in time series classification problems

Causal inference in time series classification problems

In this article, we will look at the theory of causal inference using machine learning, as well as the custom approach implementation in Python. Causal inference and causal thinking have their roots in philosophy and psychology and play an important role in our understanding of reality.
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Building A Candlestick Trend Constraint Model(Part 3): Detecting changes in trends while using this system

Building A Candlestick Trend Constraint Model(Part 3): Detecting changes in trends while using this system

This article explores how economic news releases, investor behavior, and various factors can influence market trend reversals. It includes a video explanation and proceeds by incorporating MQL5 code into our program to detect trend reversals, alert us, and take appropriate actions based on market conditions. This builds upon previous articles in the series.
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MQL5 Wizard Techniques you should know (Part 20): Symbolic Regression

MQL5 Wizard Techniques you should know (Part 20): Symbolic Regression

Symbolic Regression is a form of regression that starts with minimal to no assumptions on what the underlying model that maps the sets of data under study would look like. Even though it can be implemented by Bayesian Methods or Neural Networks, we look at how an implementation with Genetic Algorithms can help customize an expert signal class usable in the MQL5 wizard.
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Learn how to trade the Fair Value Gap (FVG)/Imbalances step-by-step: A Smart Money concept approach

Learn how to trade the Fair Value Gap (FVG)/Imbalances step-by-step: A Smart Money concept approach

A step-by-step guide to creating and implementing an automated trading algorithm in MQL5 based on the Fair Value Gap (FVG) trading strategy. A detailed tutorial on creating an expert advisor that can be useful for both beginners and experienced traders.
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Triangular arbitrage with predictions

Triangular arbitrage with predictions

This article simplifies triangular arbitrage, showing you how to use predictions and specialized software to trade currencies smarter, even if you're new to the market. Ready to trade with expertise?
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Neural networks made easy (Part 69): Density-based support constraint for the behavioral policy (SPOT)

Neural networks made easy (Part 69): Density-based support constraint for the behavioral policy (SPOT)

In offline learning, we use a fixed dataset, which limits the coverage of environmental diversity. During the learning process, our Agent can generate actions beyond this dataset. If there is no feedback from the environment, how can we be sure that the assessments of such actions are correct? Maintaining the Agent's policy within the training dataset becomes an important aspect to ensure the reliability of training. This is what we will talk about in this article.
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MQL5 Wizard Techniques you should know (Part 19): Bayesian Inference

MQL5 Wizard Techniques you should know (Part 19): Bayesian Inference

Bayesian inference is the adoption of Bayes Theorem to update probability hypothesis as new information is made available. This intuitively leans to adaptation in time series analysis, and so we have a look at how we could use this in building custom classes not just for the signal but also money-management and trailing-stops.
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Statistical Arbitrage with predictions

Statistical Arbitrage with predictions

We will walk around statistical arbitrage, we will search with python for correlation and cointegration symbols, we will make an indicator for Pearson's coefficient and we will make an EA for trading statistical arbitrage with predictions done with python and ONNX models.
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Building A Candlestick Trend Constraint Model(Part 2): Merging Native Indicators

Building A Candlestick Trend Constraint Model(Part 2): Merging Native Indicators

This article focuses on taking advantage of in-built meta trader 5 indicators to screen out off-trend signals. Advancing from the previous article we will explore how to do it using MQL5 code to communicate our idea to the final program.
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Developing a Replay System (Part 38): Paving the Path (II)

Developing a Replay System (Part 38): Paving the Path (II)

Many people who consider themselves MQL5 programmers do not have the basic knowledge that I will outline in this article. Many people consider MQL5 to be a limited tool, but the actual reason is that they do not have the required knowledge. So, if you don't know something, don't be ashamed of it. It's better to feel ashamed for not asking. Simply forcing MetaTrader 5 to disable indicator duplication in no way ensures two-way communication between the indicator and the Expert Advisor. We are still very far from this, but the fact that the indicator is not duplicated on the chart gives us some confidence.
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Custom Indicators (Part 1): A Step-by-Step Introductory Guide to Developing Simple Custom Indicators in MQL5

Custom Indicators (Part 1): A Step-by-Step Introductory Guide to Developing Simple Custom Indicators in MQL5

Learn how to create custom indicators using MQL5. This introductory article will guide you through the fundamentals of building simple custom indicators and demonstrate a hands-on approach to coding different custom indicators for any MQL5 programmer new to this interesting topic.
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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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Neural networks made easy (Part 68): Offline Preference-guided Policy Optimization

Neural networks made easy (Part 68): Offline Preference-guided Policy Optimization

Since the first articles devoted to reinforcement learning, we have in one way or another touched upon 2 problems: exploring the environment and determining the reward function. Recent articles have been devoted to the problem of exploration in offline learning. In this article, I would like to introduce you to an algorithm whose authors completely eliminated the reward function.
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Developing a Replay System (Part 36): Making Adjustments (II)

Developing a Replay System (Part 36): Making Adjustments (II)

One of the things that can make our lives as programmers difficult is assumptions. In this article, I will show you how dangerous it is to make assumptions: both in MQL5 programming, where you assume that the type will have a certain value, and in MetaTrader 5, where you assume that different servers work the same.
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How to build and optimize a volatility-based trading system (Chaikin Volatility - CHV)

How to build and optimize a volatility-based trading system (Chaikin Volatility - CHV)

In this article, we will provide another volatility-based indicator named Chaikin Volatility. We will understand how to build a custom indicator after identifying how it can be used and constructed. We will share some simple strategies that can be used and then test them to understand which one can be better.
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Building A Candlestick Trend Constraint Model (Part 1): For EAs And Technical Indicators

Building A Candlestick Trend Constraint Model (Part 1): For EAs And Technical Indicators

This article is aimed at beginners and pro-MQL5 developers. It provides a piece of code to define and constrain signal-generating indicators to trends in higher timeframes. In this way, traders can enhance their strategies by incorporating a broader market perspective, leading to potentially more robust and reliable trading signals.
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Creating a market making algorithm in MQL5

Creating a market making algorithm in MQL5

How do market makers work? Let's consider this issue and create a primitive market-making algorithm.
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Developing a Replay System (Part 34): Order System (III)

Developing a Replay System (Part 34): Order System (III)

In this article, we will complete the first phase of construction. Although this part is fairly quick to complete, I will cover details that were not discussed previously. I will explain some points that many do not understand. Do you know why you have to press the Shift or Ctrl key?