Articles on manual and algorithmic trading in MetaTrader 5

In this article, we consider the creation of an interactive graphical interface for an MQL program, which is designed for the processing of account history and trading reports using OLAP techniques. To obtain a visual result, we will use maximizable and scalable windows, an adaptive layout of rubber controls and a new control for displaying diagrams. To provide the visualization functionality, we will implement a GUI with the selection of variables along coordinate axes, as well as with the selection of aggregate functions, diagram types and sorting options.

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.

MQL programming language allows implementing the concept of modular development of trading strategies. The article shows an example of developing a multi-module Expert Advisor consisting of separately compiled file modules.

The article describes the examples of creating directories, copying data, filing, working with the symbols in Market Watch or the common list, as well as the examples of handling errors, etc. All these elements can eventually be gathered in a single script for filing the data in a user-defined format.

Let's now shape the PHP-based Twitter idea which was introduced in the first part of this article. We are assembling the different parts of the SDSS. Regarding the client side of the system architecture, we are relying on the new MQL5 WebRequest() function for sending trading signals via HTTP.

The article shows the workability of graphics in creation of a convenient interface to manage trading.

Many traders speak about neural networks, but what they are and what they really can is known to few people. This article sheds some light on the world of artificial intelligence. It describes, how to prepare correctly the data for the network. Here you will also find an example of forecasting using means of the program Matlab.

In this article, we develop a Trendline Breakout System in MQL5 that identifies support and resistance trendlines using swing points, validated by R-squared goodness of fit and angle constraints, to automate breakout trades. Our plan is to detect swing highs and lows within a specified lookback period, construct trendlines with a minimum number of touch points, and validate them using R-squared metrics and angle constraints to ensure reliability.

Volatility based breakout system identifies market ranges, then trades when price breaks above or below those levels, filtered by volatility measures such as ATR. This approach helps capture strong directional moves.

In the previous two articles, we discussed the application of Merrill patterns to various data types. An application was developed to test the presented ideas. In this article, we will continue working with the Strategy Builder, to improve its efficiency and to implement new features and capabilities.

We continue testing the patterns and trying the methods described in the articles about trading currency pair baskets. Let's consider in practice, whether it is possible to use the patterns of the combined WPR graph crossing the moving average. If the answer is yes, we should consider the appropriate usage methods.

Just over a year ago joo, in his article "Genetic Algorithms - It's Easy!", gave us a tool for implementation of the genetic algorithm in MQL5. Now utilizing the tool we will create an Expert Advisor that will genetically optimize its own parameters upon certain boundary conditions...

The article deals with convenient and efficient methods of information storage and viewing. Alternatives to the terminal standard log file and the Comment() function are considered here.

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.

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.

This article describes the econometric methods of analysis, the autocorrelation analysis and the analysis of conditional variance in particular. What is the benefit of the approach described here? Use of the non-linear GARCH models allows representing the analyzed series formally from the mathematical point of view and creating a forecast for a specified number of steps.

In this article, I decided to highlight the well-known Bernoulli scheme and to show how it can be used to describe trading-related data arrays. All this will then be used to create a self-adapting trading system. We will also look for a more generic algorithm, a special case of which is the Bernoulli formula, and will find an application for it.

In this article, we explore how to use the MQL5 Economic Calendar for trading by first understanding its core functionalities. We then implement key functions of the Economic Calendar in MQL5 to extract relevant news data for trading decisions. Finally, we conclude by showcasing how to utilize this information to enhance trading strategies effectively.

This article considers BookEvent - a Depth of Market event, and the principle of its processing. An MQL program, handling states of Depth of Market, serves as an example. It is written using the object-oriented approach. Results of handling are displayed on the screen as a panel and Depth of Market levels.