Articles on the MQL5 programming and use of trading robots

As a continuation of the neural network topic, I propose considering convolutional neural networks. This type of neural network are usually applied to analyzing visual imagery. In this article, we will consider the application of these networks in the financial markets.

This article provides programmatic definition of one of the movement continuation models. The main idea is defining two waves — the main and the correction one. For extreme points, I apply fractals as well as "potential" fractals - extreme points that have not yet formed as fractals.

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.

Finding rules for a trade system and programming them in an Expert Advisor is a half of the job. Somehow, you need to correct the operation of the Expert Advisor as it accumulates the results of trading. This article describes one of approaches, which allows improving performance of an Expert Advisor through creation of a feedback that measures slope of the balance curve.

Developers of trading robots no longer need to market their services to traders that require Expert Advisors - as now they will find you. Already, thousands of traders place orders to MQL5 freelance developers, and pay for work in on MQL5.com. For 4 years, this service facilitated three thousand traders to pay for more than 10 000 jobs performed. And the activity of traders and developers is constantly growing!

This article is a continuation of the series of articles about deep neural networks. Here we will consider selecting samples (removing noise), reducing the dimensionality of input data and dividing the data set into the train/val/test sets during data preparation for training the neural network.

Today's article shows intermediate MQL5 programmers how they can get more profit from their linear trading systems (Fixed Lot) by easily implementing the so-called technique of exponentiation. This is because the resulting equity curve growth is then geometric, or exponential, taking the form of a parabola. Specifically, we will implement a practical MQL5 variant of the Fixed Fractional position sizing developed by Ralph Vince.

What is social trading? It is a mutually beneficial cooperation of traders and investors whereby successful traders allow monitoring of their trading and potential investors take the opportunity to monitor their performance and copy trades of those who look more promising.

In the previous articles of this series, we have seen two reinforced learning algorithms. Each of them has its own advantages and disadvantages. As often happens in such cases, next comes the idea to combine both methods into an algorithm, using the best of the two. This would compensate for the shortcomings of each of them. One of such methods will be discussed in this article.

The article considers the methodology for developing trading algorithms, in which a consistent scientific approach is used to analyze possible price patterns and to build trading algorithms based on these patterns. Development ideals are demonstrated using examples.

This article presents an alternative method of GUI creation based on layouts and containers, using one layout manager — the CGrid class. The CGrid class is an auxiliary control that acts as a container for other containers and controls using a grid layout.

Today we will learn how to link an MetaTrader 5 terminal with Twitter so that you can tweet your EAs' trading signals. We are developing a Social Decision Support System in PHP based on a RESTful web service. This idea comes from a particular conception of automatic trading called computer-assisted trading. We want the cognitive abilities of human traders to filter those trading signals which otherwise would be automatically placed on the market by the Expert Advisors.

The present article develops the idea of using Kohonen Maps in MetaTrader 5, covered in some previous publications. The improved and enhanced classes provide tools to solve application tasks.

This time we are going to create a multi-currency Expert Advisor with a trading algorithm based on work with the pending orders Buy Stop and Sell Stop. This article considers the following matters: trading in a specified time range, placing/modifying/deleting pending orders, checking if the last position was closed at Take Profit or Stop Loss and control of the deals history for each symbol.

The optimization process can require significant resources of your computer or even of the MQL5 Cloud Network test agents. This article comprises some simple ideas that I use for work facilitation and improvement of the MetaTrader 5 Strategy Tester. I got these ideas from the documentation, forum and articles.

An automated system will not be successful without proper security. However, security will not be ensured without a good understanding of certain things. In this article, we will explore why achieving maximum security in automated systems is such a challenge.

In order to develop an expert to participate in Automated Trading Championship 2010, let's use a template of ready expert advisor. Even novice MQL5 programmer will be capable of this task, because for your strategies the basic classes, functions, templates are already developed. It's enough to write a minimal amount of code to implement your trading idea.

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.

We have earlier discussed some types of neural network implementations. In the considered networks, the same operations are repeated for each neuron. A logical further step is to utilize multithreaded computing capabilities provided by modern technology in an effort to speed up the neural network learning process. One of the possible implementations is described in this article.

If you think automated systems are simple, then you probably don't fully understand what it takes to create them. In this article, we will talk about the problem that kills a lot of Expert Advisors. The indiscriminate triggering of orders is a possible solution to this problem.

Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. Our EA in its current state can work in any situation but it is not yet ready for automation. We still have to work on a few points.