In this article, I will define the animation principles to be used in some parts of the library. I will also develop a class for copying a part of the image and pasting it to a specified form object location while preserving and restoring the part of the form background the image is to be superimposed on.
In this article, I will describe the concept of building various library GUI design themes, create the Form object, which is a descendant of the graphical element class object, and prepare data for creating shadows of the library graphical objects, as well as for further development of the functionality.
In this article, I will continue the development of the basic graphical element class of all library graphical objects powered by the CCanvas Standard Library class. I will create the methods for drawing graphical primitives and for displaying a text on a graphical element object.
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.
The article opens up a new large section of the library for working with graphics. In the current article, I will create the mouse status object, the base object of all graphical elements and the class of the form object of the library graphical elements.
In this article, I will create a separate class for the shadow object, which is a descendant of the graphical element object, as well as add the ability to fill the object background with a gradient fill.
This is the must-read article for anyone wanting to improve their programming career. This article series is aimed at making you the best programmer you can possibly be, no matter how experienced you are. The discussed ideas work for MQL5 programming newbies as well as professionals.
A logical continuation of the earlier discussed topic would be the development of multifunctional mathematical models for trading tasks. In this article, I will describe the entire process related to the development of the first mathematical model describing fractals, from scratch. This model should become an important building block and be multifunctional and universal. It will build up our theoretical basis for further development of this idea.
In this series of article, we will try to find a practical application of probability theory to describe trading and pricing processes. In the first article, we will look into the basics of combinatorics and probability, and will analyze the first example of how to apply fractals in the framework of the probability theory.
This is the must read article for anyone wanting to improve their programming career. This article series is aimed at making you the best programmer you can possibly be, no matter how experienced you are. The discussed ideas work for MQL5 programming newbies as well as professionals.
In this article, we will continue to study fractals and will pay special attention to summarizing all the material. To do this, I will try to bring all earlier developments into a compact form which would be convenient and understandable for practical application in trading.
This article considers typical chart events and includes examples of their processing. We will focus on mouse events, keystrokes, creation/modification/removal of a graphical object, mouse click on a chart and on a graphical object, moving a graphical object with a mouse, finish editing of text in a text field, as well as on chart modification events. A sample of an MQL5 program is provided for each type of event considered.
There are a lot of bad habits that newbies and even advanced programmers are doing that are keeping them from becoming the best they can be to their coding career. We are going to discuss and address them in this article. This article is a must read for everyone who wants to become successful developer in MQL5.
In this article I will try to expand the classic concept of swap trading methods. I will explain why I have come to the conclusion that this concept deserves special attention and is absolutely recommended for study.
MQL5.community Services offer great opportunities for traders as well as for the developers of applications for the MetaTrader terminal. In this article, we explain how payments for MQL5 services are performed, how the earned money can be withdraw, and how the operation security is ensured.
This is the first article in a series related to reversal patterns in the framework of algorithmic trading. We will begin with the most interesting pattern family, which originate from the Double Top and Double Bottom patterns.
Ever wanted to access tweets and/or post your trade signals on Twitter ? Search no more, these on-going article series will show you how to do it without using any DLL. Enjoy the journey of implementing Twitter API using MQL. In this first part, we will follow the glory path of authentication and authorization in accessing Twitter API.
These are some tips from a professional programmer about methods, techniques and auxiliary tools which can make programming easier. We will discuss parameters which can be restored after terminal restart (shutdown). All examples are real working code segments from my Cayman project.
The article provides the description of the technology aimed at increasing the effectiveness of any automated trading system. It provides a brief explanation of the idea, as well as its underlying basics, possibilities and disadvantages.
The article presents an improved brute force version, based on the goals set in the previous article. I will try to cover this topic as broadly as possible using Expert Advisors with settings obtained using this method. A new program version is attached to this article.
The article discusses a popular MVC pattern, as well as the possibilities, pros and cons of its usage in MQL programs. The idea is to split an existing code into three separate components: Model, View and Controller.
The popularity of these two methods grows, so a lot of libraries have been developed in Matlab, R, Python, C++ and others, which receive a training set as input and automatically create an appropriate network for the problem. Let us try to understand how the basic neural network type works (including single-neuron perceptron and multilayer perceptron). We will consider an exciting algorithm which is responsible for network training - gradient descent and backpropagation. Existing complex models are often based on such simple network models.
In this article I will demonstrate some very interesting and useful techniques for automated trading. Some of them may be familiar to you. I will try to cover the most interesting methods and will explain why they are worth using. Furthermore, I will show what these techniques are apt to in practice. We will create Expert Advisors and test all the described techniques using historic quotes.
This article provides a continuation to the brute force topic, and it introduces new opportunities for market analysis into the program algorithm, thereby accelerating the speed of analysis and improving the quality of results. New additions enable the highest-quality view of global patterns within this approach.
In this article we will continue discussing the brute force approach. I will try to provide a better explanation of the pattern using the new improved version of my application. I will also try to find the difference in stability using different time intervals and timeframes.
In this article, I will continue the development of the topic by improving the flexibility of the previously created algorithm. The algorithm became more stable with an increase in the number of candles in the analysis window or with an increase in the threshold percentage of the overweight of falling or growing candles. I had to make a compromise and set a larger sample size for analysis or a larger percentage of the prevailing candle excess.
This article describes the machine learning technique applied to grid and martingale trading. Surprisingly, this approach has little to no coverage in the global network. After reading the article, you will be able to create your own trading bots.
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.
Perhaps one of the most advanced models among currently existing language neural networks is GPT-3, the maximal variant of which contains 175 billion parameters. Of course, we are not going to create such a monster on our home PCs. However, we can view which architectural solutions can be used in our work and how we can benefit from them.
It is impossible to get a truly stable algorithm if we use optimization based on historical data to select parameters. A stable algorithm should be aware of what parameters are needed when working on any trading instrument at any time. It should not forecast or guess, it should know for sure.
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.
Have you ever felt the need to add a graphical panel to your indicator or Expert Advisor for greater speed and convenience? In this article, you will find out how to implement the dialog panel with the input parameters into your MQL4/MQL5 program step by step.
Do you need more than awkward graphics of moving averages? Do you want to draw something more beautiful than a simple filled rectangle in your terminal? Attractive graphics can be drawn in the terminal. This can be implemented through the CСanvas class, which is used for creating custom graphics. With this class you can implement transparency, blend colors and produce the illusion of transparency by means of overlapping and blending colors.
The "area method" trading system works based on unusual interpretation of the RSI oscillator readings. The indicator that visualizes the area method, and the Expert Advisor that trades using this system are detailed here. The article is also supplemented with detailed findings of testing the Expert Advisor for various symbols, time frames and values of the area.
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.
The calculator of signals operates directly from the MetaTrader 5 terminal, which is a serious advantage, since the terminal provides a preliminary selection and sorts out signals. This way, users can see in the terminal only the signals that ensure a maximum compatibility with their trading accounts.
The article considers the creation of machine learning models with time filters and discusses the effectiveness of this approach. The human factor can be eliminated now by simply instructing the model to trade at a certain hour of a certain day of the week. Pattern search can be provided by a separate algorithm.
We have already passed a long way and the code in our library is becoming bigger and bigger. This makes it difficult to keep track of all connections and dependencies. Therefore, I suggest creating documentation for the earlier created code and to keep it updating with each new step. Properly prepared documentation will help us see the integrity of our work.
In this article, I will try to test the assumption that any system with even a small understanding of the market can operate on a global scale. I will not invent any theories or patterns, but I will only use known facts, gradually translating these facts into the language of mathematical analysis.
