Join us in Part III of the "Improve Your Trading Charts With Interactive GUIs in MQL5" series as we explore the integration of interactive GUIs into movable trading dashboards in MQL5. This article builds on the foundations set in Parts I and II, guiding readers to transform static trading dashboards into dynamic, movable ones.
Presenting the RSI Deep Three Move Trading Technique in MetaTrader 5. This article is based on a new series of studies that showcase a few trading techniques based on the RSI, a technical analysis indicator used to measure the strength and momentum of a security, such as a stock, currency, or commodity.
Mean reversion is a type of contrarian trading where the trader expects the price to return to some form of equilibrium which is generally measured by a mean or another central tendency statistic.
Any Program in any programming language has a specific structure. In this article, you will learn essential parts of the MQL5 program structure by understanding the programming basics of every part of the MQL5 program structure that can be very helpful when creating our MQL5 trading system or trading tool that can be executable in the MetaTrader 5.
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.
Are you looking for a cutting-edge approach to trading that can help you navigate complex and ever-changing markets? Look no further than Kohonen maps, an innovative form of artificial neural networks that can help you uncover hidden patterns and trends in market data. In this article, we'll explore how Kohonen maps work, and how they can be used to develop smarter, more effective trading strategies. Whether you're a seasoned trader or just starting out, you won't want to miss this exciting new approach to trading.
This article continues the series on category theory implementation in MQL5. Here we introduce monoids as domain (set) that sets category theory apart from other data classification methods by including rules and an identity element.
Do you know what a flowchart is? Can you use it? Do you think flowcharts are for beginners? I suggest that we proceed to this new article and learn how to work with flowcharts.
Old trading strategies. This article presents one of the strategies used to follow the trend in a purely technical way. The strategy is purely technical and uses a few technical indicators and tools to deliver signals and targets. The components of the strategy are as follows: A 14-period stochastic oscillator. A 5-period stochastic oscillator. A 200-period moving average. A Fibonacci projection tool (for target setting).
Here is a new article about how to create a custom indicator. This time we will work with the True Strength Index (TSI) and will create an Expert Advisor based on it.
Combinations of strategies may offer better opportunities. We can combine indicators or patterns together, or even better, indicators with patterns, so that we get an extra confirmation factor. Moving averages help us confirm and ride the trend. They are the most known technical indicators and this is because of their simplicity and their proven track record of adding value to analyses.
Unlock the potential of dynamic data representation in your trading strategies and utilities with our in-depth guide to creating movable GUIs in MQL5. Delve into the fundamental principles of object-oriented programming and discover how to design and implement single or multiple movable GUIs on the same chart with ease and efficiency.
In this article, we will provide a simple and easy guide to anyone who needs to create one of the most valuable and helpful tools in trading which is the graphical panel to simplify and ease doing tasks around trading which helps to save time and focus more on your trading process itself without any distractions.
This article reports the first attempts in the development of a native MQTT client for MQL5. MQTT is a Client Server publish/subscribe messaging transport protocol. It is lightweight, open, simple, and designed to be easy to implement. These characteristics make it ideal for use in many situations.
In this article, we will create a mathematical model for simulating multicurrency pricing and complete the study of the diversification principle as part of the search for mechanisms to increase the trading efficiency, which I started in the previous article with theoretical calculations.
As developers, we need to learn how to create and develop software that can be reusable and flexible without duplicated code especially if we have different objects with different behaviors. This can be smoothly done by using object-oriented programming techniques and principles. In this article, we will present the basics of MQL5 Object-Oriented programming to understand how we can use principles and practices of this critical topic in our software.
To complete this series of articles on automation, we will continue discussing the topic of the previous article. We will see how everything will fit together, making the EA run like clockwork.
In this article, I will complete working with chart object classes and their collection. I will also implement auto tracking of changes in chart properties and their windows, as well as saving new parameters to the object properties. Such a revision allows the future implementation of an event functionality for the entire chart collection.
In this article, I will create the functionality for tracking some chart object events — adding/removing symbol charts and chart subwindows, as well as adding/removing/changing indicators in chart windows.
With this article, I start the development of the chart object collection class. The class will store the collection list of chart objects with their subwindows and indicators providing the ability to work with any selected charts and their subwindows or with a list of several charts at once.
In this article, I will continue the development of the chart object class. I will add the list of chart window objects featuring the lists of available indicators.
In this article, I will create the chart object class (of a single trading instrument chart) and improve the collection class of MQL5 signal objects so that each signal object stored in the collection updates all its parameters when updating the list.
In this article, I will create the signal collection class of the MQL5.com Signals service with the functions for managing signals. Besides, I will improve the Depth of Market snapshot object class for displaying the total DOM buy and sell volumes.
In this article, I will create two classes (the class of DOM snapshot object and the class of DOM snapshot series object) and test creation of the DOM data series.
In this article, we will put into practice all the knowledge from this series. We will finally build a 100% automated and functional system. But before that, we still have to learn one last detail.
In this article, I will implement updating tick data in real time and prepare the symbol object class for working with Depth of Market (DOM itself is to be implemented in the next article).
From this article on, start creating library functionality to work with price data. Today, create an object class which will store all price data which arrived with yet another tick.
In conclusion of the topic of working with timeseries organise storage, search and sort of data stored in indicator buffers which will allow to further perform the analysis based on values of the indicators to be created on the library basis in programs. The general concept of all collection classes of the library allows to easily find necessary data in the corresponding collection. Respectively, the same will be possible in the class created today.
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.
In the article, develop an object which will contain all data of one buffer for one indicator. Such objects will be necessary for storing serial data of indicator buffers. With their help, it will be possible to sort and compare buffer data of any indicators, as well as other similar data with each other.
The article considers creation of the custom indicator object for the use in EAs. Let’s slightly improve library classes and add methods to get data from indicator objects in EAs.
In this article, we will provide a method to detect price actions patterns automatically by MQL5, like trends (Uptrend, Downtrend, Sideways), Chart patterns (Double Tops, Double Bottoms).
In this article, we will use the rebuy algorithm for a deeper understanding of the efficiency of trading systems and start working on the general principles of improving trading efficiency using mathematics and logic, as well as apply the most non-standard methods of increasing efficiency in terms of using absolutely any trading system.
There are many technical tools that can be used to visualize a channel surrounding prices, One of these tools is the Donchian Channel indicator. In this article, we will learn how to create the Donchian Channel indicator and how we can trade it as a custom indicator using EA.
The article provides an example of using a perceptron as a self-sufficient price prediction tool by showcasing general concepts and the simplest ready-made Expert Advisor followed by the results of its optimization.
In this article, we will continue our series of creating a trading system based on the most popular technical indicator. Here is a new technical tool which is the Fibonacci and we will learn how to design a trading system based on this technical indicator.
Neural networks are an ultimate tool in traders' toolkit. Let's check if this assumption is true. MetaTrader 5 is approached as a self-sufficient medium for using neural networks in trading. A simple explanation is provided.
