![Custom symbols: Practical basics](https://c.mql5.com/2/49/Custom_symbols_Practical_basics_600x314.jpg)
Custom symbols: Practical basics
The article is devoted to the programmatic generation of custom symbols which are used to demonstrate some popular methods for displaying quotes. It describes a suggested variant of minimally invasive adaptation of Expert Advisors for trading a real symbol from a derived custom symbol chart. MQL source codes are attached to this article.
![MQL5 Cookbook - Programming moving channels](https://c.mql5.com/2/22/ava.png)
![MQL5 Cookbook - Programming moving channels](https://c.mql5.com/i/articles/overlay.png)
MQL5 Cookbook - Programming moving channels
This article presents a method of programming the equidistant channel system. Certain details of building such channels are being considered here. Channel typification is provided, and a universal type of moving channels' method is suggested. Object-oriented programming (OOP) is used for code implementation.
![DIY multi-threaded asynchronous MQL5 WebRequest](https://c.mql5.com/2/34/Multi_WebRequest_MQL5.png)
![DIY multi-threaded asynchronous MQL5 WebRequest](https://c.mql5.com/i/articles/overlay.png)
DIY multi-threaded asynchronous MQL5 WebRequest
The article describes the library allowing you to increase the efficiency of working with HTTP requests in MQL5. Execution of WebRequest in non-blocking mode is implemented in additional threads that use auxiliary charts and Expert Advisors, exchanging custom events and reading shared resources. The source codes are applied as well.
![Learn how to design a trading system by ADX](https://c.mql5.com/2/46/why-and-how__3.png)
![Learn how to design a trading system by ADX](https://c.mql5.com/i/articles/overlay.png)
Learn how to design a trading system by ADX
In this article, we will continue our series about designing a trading system using the most popular indicators and we will talk about the average directional index (ADX) indicator. We will learn this indicator in detail to understand it well and we will learn how we to use it through a simple strategy. By learning something deeply we can get more insights and we can use it better.
![The Optimal Method for Calculation of Total Position Volume by Specified Magic Number](https://c.mql5.com/2/0/calculate_volume_MQL5__1.png)
![The Optimal Method for Calculation of Total Position Volume by Specified Magic Number](https://c.mql5.com/i/articles/overlay.png)
The Optimal Method for Calculation of Total Position Volume by Specified Magic Number
The problem of calculation of the total position volume of the specified symbol and magic number is considered in this article. The proposed method requests only the minimum necessary part of the history of deals, finds the closest time when the total position was equal to zero, and performs the calculations with the recent deals. Working with global variables of the client terminal is also considered.
![Neural networks made easy (Part 7): Adaptive optimization methods](https://c.mql5.com/2/49/Neural_Networks_Easy_007_600x314.jpg)
Neural networks made easy (Part 7): Adaptive optimization methods
In previous articles, we used stochastic gradient descent to train a neural network using the same learning rate for all neurons within the network. In this article, I propose to look towards adaptive learning methods which enable changing of the learning rate for each neuron. We will also consider the pros and cons of this approach.
![Ready-made Expert Advisors from the MQL5 Wizard work in MetaTrader 4](https://c.mql5.com/2/26/MQL5_expert_in_MT4.png)
![Ready-made Expert Advisors from the MQL5 Wizard work in MetaTrader 4](https://c.mql5.com/i/articles/overlay.png)
Ready-made Expert Advisors from the MQL5 Wizard work in MetaTrader 4
The article offers a simple emulator of the MetaTrader 5 trading environment for MetaTrader 4. The emulator implements migration and adjustment of trade classes of the Standard Library. As a result, Expert Advisors generated in the MetaTrader 5 Wizard can be compiled and executed in MetaTrader 4 without changes.
![Reversing: Formalizing the entry point and developing a manual trading algorithm](https://c.mql5.com/2/34/Reverse_trade.png)
![Reversing: Formalizing the entry point and developing a manual trading algorithm](https://c.mql5.com/i/articles/overlay.png)
Reversing: Formalizing the entry point and developing a manual trading algorithm
This is the last article within the series devoted to the Reversing trading strategy. Here we will try to solve the problem, which caused the testing results instability in previous articles. We will also develop and test our own algorithm for manual trading in any market using the reversing strategy.
![Practical application of neural networks in trading (Part 2). Computer vision](https://c.mql5.com/2/49/Practical_application_of_neural_networks_in_trading_001_600x314.jpg)
Practical application of neural networks in trading (Part 2). Computer vision
The use of computer vision allows training neural networks on the visual representation of the price chart and indicators. This method enables wider operations with the whole complex of technical indicators, since there is no need to feed them digitally into the neural network.
![Neural networks made easy (Part 4): Recurrent networks](https://c.mql5.com/2/49/Neural_Networks_Easy_004_600x314.jpg)
Neural networks made easy (Part 4): Recurrent networks
We continue studying the world of neural networks. In this article, we will consider another type of neural networks, recurrent networks. This type is proposed for use with time series, which are represented in the MetaTrader 5 trading platform by price charts.
![How to use MQL5 to detect candlesticks patterns](https://c.mql5.com/2/53/how_to_use_mql5_to_detect_candlesticks_patterns_600x314.jpg)
How to use MQL5 to detect candlesticks patterns
A new article to learn how to detect candlesticks patterns on prices automatically by MQL5.
![Self-adapting algorithm (Part IV): Additional functionality and tests](https://c.mql5.com/2/41/50_percents__4.png)
![Self-adapting algorithm (Part IV): Additional functionality and tests](https://c.mql5.com/i/articles/overlay.png)
Self-adapting algorithm (Part IV): Additional functionality and tests
I continue filling the algorithm with the minimum necessary functionality and testing the results. The profitability is quite low but the articles demonstrate the model of the fully automated profitable trading on completely different instruments traded on fundamentally different markets.
![Modeling time series using custom symbols according to specified distribution laws](https://c.mql5.com/2/33/Custom_series_modelling.png)
![Modeling time series using custom symbols according to specified distribution laws](https://c.mql5.com/i/articles/overlay.png)
Modeling time series using custom symbols according to specified distribution laws
The article provides an overview of the terminal's capabilities for creating and working with custom symbols, offers options for simulating a trading history using custom symbols, trend and various chart patterns.
![Learn how to design a trading system by Ichimoku](https://c.mql5.com/2/49/learnhow_ichimoku_600x314.jpg)
Learn how to design a trading system by Ichimoku
Here is a new article in our series about how to design a trading system b the most popular indicators, we will talk about the Ichimoku indicator in detail and how to design a trading system by this indicator.
![Learn how to design a trading system by Momentum](https://c.mql5.com/2/45/why-and-how__5.png)
![Learn how to design a trading system by Momentum](https://c.mql5.com/i/articles/overlay.png)
Learn how to design a trading system by Momentum
In my previous article, I mentioned the importance of identifying the trend which is the direction of prices. In this article I will share one of the most important concepts and indicators which is the Momentum indicator. I will share how to design a trading system based on this Momentum indicator.
![Applying OLAP in trading (part 3): Analyzing quotes for the development of trading strategies](https://c.mql5.com/2/38/OLAP_02.png)
![Applying OLAP in trading (part 3): Analyzing quotes for the development of trading strategies](https://c.mql5.com/i/articles/overlay.png)
Applying OLAP in trading (part 3): Analyzing quotes for the development of trading strategies
In this article we will continue dealing with the OLAP technology applied to trading. We will expand the functionality presented in the first two articles. This time we will consider the operational analysis of quotes. We will put forward and test the hypotheses on trading strategies based on aggregated historical data. The article presents Expert Advisors for studying bar patterns and adaptive trading.
![MQL5 Cookbook: Saving Optimization Results of an Expert Advisor Based on Specified Criteria](https://c.mql5.com/2/0/avatar__7.png)
![MQL5 Cookbook: Saving Optimization Results of an Expert Advisor Based on Specified Criteria](https://c.mql5.com/i/articles/overlay.png)
MQL5 Cookbook: Saving Optimization Results of an Expert Advisor Based on Specified Criteria
We continue the series of articles on MQL5 programming. This time we will see how to get results of each optimization pass right during the Expert Advisor parameter optimization. The implementation will be done so as to ensure that if the conditions specified in the external parameters are met, the corresponding pass values will be written to a file. In addition to test values, we will also save the parameters that brought about such results.
![Cross-Platform Expert Advisor: Custom Stops, Breakeven and Trailing](https://c.mql5.com/2/30/Cross_Platform_Expert_Advisor__1.png)
![Cross-Platform Expert Advisor: Custom Stops, Breakeven and Trailing](https://c.mql5.com/i/articles/overlay.png)
Cross-Platform Expert Advisor: Custom Stops, Breakeven and Trailing
This article discusses how custom stop levels can be set up in a cross-platform expert advisor. It also discusses a closely-related method by which the evolution of a stop level over time can be defined.
![Multibot in MetaTrader: Launching multiple robots from a single chart](https://c.mql5.com/2/53/launching_multiple_robots_600x314.jpg)
Multibot in MetaTrader: Launching multiple robots from a single chart
In this article, I will consider a simple template for creating a universal MetaTrader robot that can be used on multiple charts while being attached to only one chart, without the need to configure each instance of the robot on each individual chart.
![Cross-Platform Expert Advisor: Introduction](https://c.mql5.com/2/24/Expert_Advisor_Introduction.png)
![Cross-Platform Expert Advisor: Introduction](https://c.mql5.com/i/articles/overlay.png)
Cross-Platform Expert Advisor: Introduction
This article details a method by which cross-platform expert advisors can be developed faster and easier. The proposed method consolidates the features shared by both versions into a single class, and splits the implementation on derived classes for incompatible features.
![Another MQL5 OOP Class](https://c.mql5.com/2/0/hand.png)
![Another MQL5 OOP Class](https://c.mql5.com/i/articles/overlay.png)
Another MQL5 OOP Class
This article shows you how to build an Object-Oriented Expert Advisor from scratch, from conceiving a theoretical trading idea to programming a MQL5 EA that makes that idea real in the empirical world. Learning by doing is IMHO a solid approach to succeed, so I am showing a practical example in order for you to see how you can order your ideas to finally code your Forex robots. My goal is also to invite you to adhere the OO principles.
![Graphics in DoEasy library (Part 74): Basic graphical element powered by the CCanvas class](https://c.mql5.com/2/42/MQL5-avatar-doeasy-library3-2__1.png)
![Graphics in DoEasy library (Part 74): Basic graphical element powered by the CCanvas class](https://c.mql5.com/i/articles/overlay.png)
Graphics in DoEasy library (Part 74): Basic graphical element powered by the CCanvas class
In this article, I will rework the concept of building graphical objects from the previous article and prepare the base class of all graphical objects of the library powered by the Standard Library CCanvas class.
![Cross-Platform Expert Advisor: The CExpertAdvisor and CExpertAdvisors Classes](https://c.mql5.com/2/30/Cross_Platform_Expert_Advisor__2.png)
![Cross-Platform Expert Advisor: The CExpertAdvisor and CExpertAdvisors Classes](https://c.mql5.com/i/articles/overlay.png)
Cross-Platform Expert Advisor: The CExpertAdvisor and CExpertAdvisors Classes
This article deals primarily with the classes CExpertAdvisor and CExpertAdvisors, which serve as the container for all the other components described in this article-series regarding cross-platform expert advisors.
![Building interactive semi-automatic drag-and-drop Expert Advisor based on predefined risk and R/R ratio](https://c.mql5.com/2/0/z5491084X.png)
![Building interactive semi-automatic drag-and-drop Expert Advisor based on predefined risk and R/R ratio](https://c.mql5.com/i/articles/overlay.png)
Building interactive semi-automatic drag-and-drop Expert Advisor based on predefined risk and R/R ratio
Some traders execute all their trades automatically, and some mix automatic and manual trades based on the output of several indicators. Being a member of the latter group I needed an interactive tool to asses dynamically risk and reward price levels directly from the chart. This article will present a way to implement an interactive semi-automatic Expert Advisor with predefined equity risk and R/R ratio. The Expert Advisor risk, R/R and lot size parameters can be changed during runtime on the EA panel.
![Neural Networks Cheap and Cheerful - Link NeuroPro with MetaTrader 5](https://c.mql5.com/2/12/NeuroPro_MetaTrader4_neural_net.png)
![Neural Networks Cheap and Cheerful - Link NeuroPro with MetaTrader 5](https://c.mql5.com/i/articles/overlay.png)
Neural Networks Cheap and Cheerful - Link NeuroPro with MetaTrader 5
If specific neural network programs for trading seem expensive and complex or, on the contrary, too simple, try NeuroPro. It is free and contains the optimal set of functionalities for amateurs. This article will tell you how to use it in conjunction with MetaTrader 5.
![Design Patterns in software development and MQL5 (Part 4): Behavioral Patterns 2](https://c.mql5.com/2/63/midjourney_image_13876_57_514_5_600x314.jpg)
Design Patterns in software development and MQL5 (Part 4): Behavioral Patterns 2
In this article, we will complete our series about the Design Patterns topic, we mentioned that there are three types of design patterns creational, structural, and behavioral. We will complete the remaining patterns of the behavioral type which can help set the method of interaction between objects in a way that makes our code clean.
![Learn how to design a trading system by Bear's Power](https://c.mql5.com/2/49/learnhow_bears_power_600x314.jpg)
Learn how to design a trading system by Bear's Power
Welcome to a new article in our series about learning how to design a trading system by the most popular technical indicator here is a new article about learning how to design a trading system by Bear's Power technical indicator.
![OpenAI's ChatGPT features within the framework of MQL4 and MQL5 development](https://c.mql5.com/2/55/mql5-openai_600x314.jpg)
OpenAI's ChatGPT features within the framework of MQL4 and MQL5 development
In this article, we will fiddle around ChatGPT from OpenAI in order to understand its capabilities in terms of reducing the time and labor intensity of developing Expert Advisors, indicators and scripts. I will quickly navigate you through this technology and try to show you how to use it correctly for programming in MQL4 and MQL5.
![Video: How to setup MetaTrader 5 and MQL5 for simple automated trading](https://c.mql5.com/2/46/Metaquotes-simple-automated-trading.png)
![Video: How to setup MetaTrader 5 and MQL5 for simple automated trading](https://c.mql5.com/i/articles/overlay.png)
Video: How to setup MetaTrader 5 and MQL5 for simple automated trading
In this little video course you will learn how to download, install and setup MetaTrader 5 for Automated Trading. You will also learn how to adjust the chart settings and the options for automated trading. You will do your first backtest and by the end of this course you will know how to import an Expert Advisor that can automatically trade 24/7 while you don't have to sit in front of your screen.
![Using MetaTrader 5 as a Signal Provider for MetaTrader 4](https://c.mql5.com/2/0/MetaTrader_5_Signal_Provider_MetaTrader_4.png)
![Using MetaTrader 5 as a Signal Provider for MetaTrader 4](https://c.mql5.com/i/articles/overlay.png)
Using MetaTrader 5 as a Signal Provider for MetaTrader 4
Analyse and examples of techniques how trading analysis can be performed on MetaTrader 5 platform, but executed by MetaTrader 4. Article will show you how to create simple signal provider in your MetaTrader 5, and connect to it with multiple clients, even running MetaTrader 4. Also you will find out how you can follow participants of Automated Trading Championship in your real MetaTrader 4 account.
![Learn how to design a trading system by Stochastic](https://c.mql5.com/2/46/why-and-how__2.png)
![Learn how to design a trading system by Stochastic](https://c.mql5.com/i/articles/overlay.png)
Learn how to design a trading system by Stochastic
In this article, we continue our learning series — this time we will learn how to design a trading system using one of the most popular and useful indicators, which is the Stochastic Oscillator indicator, to build a new block in our knowledge of basics.
![Deep Neural Networks (Part II). Working out and selecting predictors](https://c.mql5.com/2/48/Deep_Neural_Networks_02.png)
![Deep Neural Networks (Part II). Working out and selecting predictors](https://c.mql5.com/i/articles/overlay.png)
Deep Neural Networks (Part II). Working out and selecting predictors
The second article of the series about deep neural networks will consider the transformation and choice of predictors during the process of preparing data for training a model.
![A Few Tips for First-Time Customers](https://c.mql5.com/2/0/MQL5_Job_Service_Recommendations.png)
![A Few Tips for First-Time Customers](https://c.mql5.com/i/articles/overlay.png)
A Few Tips for First-Time Customers
A proverbial wisdom often attributed to various famous people says: "He who makes no mistakes never makes anything." Unless you consider idleness itself a mistake, this statement is hard to argue with. But you can always analyze the past mistakes (your own and of others) to minimize the number of your future mistakes. We are going to attempt to review possible situations arising when executing jobs in the same-name service.
![Matrices and vectors in MQL5](https://c.mql5.com/2/49/matrix_vectors_mql5_600x314.jpg)
Matrices and vectors in MQL5
By using special data types 'matrix' and 'vector', it is possible to create code which is very close to mathematical notation. With these methods, you can avoid the need to create nested loops or to mind correct indexing of arrays in calculations. Therefore, the use of matrix and vector methods increases the reliability and speed in developing complex programs.
![CatBoost machine learning algorithm from Yandex with no Python or R knowledge required](https://c.mql5.com/2/49/CatBoost-machine-learning-algorithm-from-Yandex-with-no-Python-or-R-knowledge-required_600x314.jpg)
CatBoost machine learning algorithm from Yandex with no Python or R knowledge required
The article provides the code and the description of the main stages of the machine learning process using a specific example. To obtain the model, you do not need Python or R knowledge. Furthermore, basic MQL5 knowledge is enough — this is exactly my level. Therefore, I hope that the article will serve as a good tutorial for a broad audience, assisting those interested in evaluating machine learning capabilities and in implementing them in their programs.
![Learn how to design a trading system by Volumes](https://c.mql5.com/2/49/learnhow_volumes_600x314.jpg)
Learn how to design a trading system by Volumes
Here is a new article from our series about learning how to design a trading system based on the most popular technical indicators. The current article will be devoted to the Volumes indicator. Volume as a concept is one of the very important factors in financial markets trading and we have to pay attention to it. Through this article, we will learn how to design a simple trading system by Volumes indicator.
![Learn how to design a trading system by Alligator](https://c.mql5.com/2/49/trading-system-by-Alligator_600x314.jpg)
Learn how to design a trading system by Alligator
In this article, we'll complete our series about how to design a trading system based on the most popular technical indicator. We'll learn how to create a trading system based on the Alligator indicator.
![The Player of Trading Based on Deal History](https://c.mql5.com/2/0/MQL5_Trade_Player.png)
![The Player of Trading Based on Deal History](https://c.mql5.com/i/articles/overlay.png)
The Player of Trading Based on Deal History
The player of trading. Only four words, no explanation is needed. Thoughts about a small box with buttons come to your mind. Press one button - it plays, move the lever - the playback speed changes. In reality, it is pretty similar. In this article, I want to show my development that plays trade history almost like it is in real time. The article covers some nuances of OOP, working with indicators and managing charts.
![Creating an EA that works automatically (Part 02): Getting started with the code](https://c.mql5.com/2/50/Aprendendo-a-construindo_part_II_600x314.jpg)
Creating an EA that works automatically (Part 02): Getting started with the code
Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. In the previous article, we discussed the first steps that anyone needs to understand before proceeding to creating an Expert Advisor that trades automatically. We considered the concepts and the structure.
![Neural networks made easy (Part 10): Multi-Head Attention](https://c.mql5.com/2/49/Neural_Networks_Easy_009_600x314.jpg)
Neural networks made easy (Part 10): Multi-Head Attention
We have previously considered the mechanism of self-attention in neural networks. In practice, modern neural network architectures use several parallel self-attention threads to find various dependencies between the elements of a sequence. Let us consider the implementation of such an approach and evaluate its impact on the overall network performance.