Articles on the MQL5 programming and use of trading robots

Is it possible to develop an Expert Advisor able to optimize position open and close conditions at regular intervals according to the code commands? What happens if we implement a neural network (multilayer perceptron) in the form of a module to analyze history and provide strategy? We can make the EA optimize a neural network monthly (weekly, daily or hourly) and continue its work afterwards. Thus, we can develop a self-optimizing EA.

MetaTrader 4 and MetaTrader 5 uses different conventions in processing trade requests. This article discusses the possibility of using a class object that can be used to represent the trades processed by the server, in order for a cross-platform expert advisor to further work on them, regardless of the version of the trading platform and mode being used.

The article describes the process of developing and implementing a class for sending signals based on the moving channels. Each of the signal version is followed by a trading strategy with testing results. Classes of the Standard Library are used for creating derived classes.

When you subscribe to signals, such situation may occur: your trade account has a leverage of 1:100, the provider has a leverage of 1:500 and trades using the minimal lot, and your trade balances are virtually equal — but the copy ratio will comprise only 10% to 15%. This article describes how to increase the copy rate in such cases.

There exists some components in the MQL5 Standard Library that may prove to be useful in the MQL4 version of cross-platform expert advisors. This article deals with a method of making certain components of the MQL5 Standard Library compatible with the MQL4 compiler.

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.

Before any product is published in the Market, it must undergo compulsory preliminary checks in order to ensure a uniform quality standard. This article considers the most frequent errors made by developers in their technical indicators and trading robots. An also shows how to self-test a product before sending it to the Market.

Many traders on Moscow Exchange would like to automate their trading algorithms, but they do not know where to start. The MQL5 language offers a huge range of trading functions, and it additionally provides ready classes that help users to make their first steps in algo trading.

The number of trading robots used on the currency markets has significantly increased recently. They employ various concepts and strategies, however, none of them has yet succeeded to create a win-win sample of artificial intelligence. Therefore, many traders remain committed to manual trading. But even for such specialists, robotic assistants or, so called, trading panels, are created. This article is yet another example of creating a trading panel from scratch.

This article covers the main principles set fourth in evolutionary algorithms, their variety and features. We will conduct an experiment with a simple Expert Advisor used as an example to show how our trading system benefits from optimization. We will consider software programs that implement genetic, evolutionary and other types of optimization, and provide examples of application when optimizing a predictor set and parameters of the trading system.

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.

The article describes the rules of the trading system by Bill Williams, the procedure of application for a developed MQL5 module to search and mark patterns of this system on the chart, automated trading with found patterns, and also presents the results of testing on various trading instruments.

A logically complete market theory that would cover all types and varieties of markets for goods and services, micro and macro markets like Forex, hasn't been available until now. This article covers the essence of a new market theory based on the profit analysis, reveals patterns of the current price change and the principle of the mechanism operation that allows the price to find its most optimal value by forming a chain of virtual prices that can develop the controlling influence on the actual price. Mechanisms of formation and change of market trends are also identified here.

What should your program do, if graphic control panels have been removed or modified by someone else? In this article we will show you how not to have "ownerless" objects on the chart, and how not to lose control over them in cases of renaming or deleting programmatically created objects after the application is deleted.

This article focuses on specifics of choice, preconditioning and evaluation of the input variables (predictors) for use in machine learning models. New approaches and opportunities of deep predictor analysis and their influence on possible overfitting of models will be considered. The overall result of using models largely depends on the result of this stage. We will analyze two packages offering new and original approaches to the selection of predictors.

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.

This step-by-step guide provides tips and tricks for better understanding and searching for a required product. The article makes an attempt to puzzle out different methods of searching for an appropriate product, sorting out unwanted products, determining product efficiency and essentiality for you.

This article describes a new approach to hedging of positions and draws the line in the debates between users of MetaTrader 4 and MetaTrader 5 about this matter. It is a continuation of the first part: "Bi-Directional Trading and Hedging of Positions in MetaTrader 5 Using the HedgeTerminal Panel, Part 1". In the second part, we discuss integration of custom Expert Advisors with HedgeTerminalAPI, which is a special visualization library designed for bi-directional trading in a comfortable software environment providing tools for convenient position management.

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.

In this article we look at the possibility of creating an application for the display of RSS feeds. The article will show how aspects of the Standard Library can be used to create interactive programs for MetaTrader 5.

This article is dedicated to a new and perspective direction in machine learning - deep learning or, to be precise, deep neural networks. This is a brief review of second generation neural networks, the architecture of their connections and main types, methods and rules of learning and their main disadvantages followed by the history of the third generation neural network development, their main types, peculiarities and training methods. Conducted are practical experiments on building and training a deep neural network initiated by the weights of a stacked autoencoder with real data. All the stages from selecting input data to metric derivation are discussed in detail. The last part of the article contains a software implementation of a deep neural network in an Expert Advisor with a built-in indicator based on MQL4/R.

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.

This article describes the MQL5 Standard Library extension, which allows to create Expert Advisors, place orders, Stop Losses and Take Profits using the MQL5 Wizard by the prices received from included modules. This approach does not apply any additional restrictions on the number of modules and does not cause conflicts in their joint work.

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.

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!

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.

A few weeks ago we published the infographic on Freelance service. We also promised to reveal some statistics of the MetaTrader Market. Now, we invite you to examine the data we have gathered.

On the occasion of the MQL5 Freelance Service fourth birthday, we have prepared an info-graphic demonstrating the service results for the entire time of its existence. The figures speak for themselves: more than 10 000 orders worth about $600,000 in total have been executed to date, while 3 000 customers and 300 developers have already used the service.

Algorithmic trading becomes more popular and needed, which naturally led to a demand for exotic algorithms and unusual tasks. To some extent, such complex applications are available in the Code Base or in the Market. Although traders have simple access to those apps in a couple of clicks, these apps may not satisfy all needs in full. In this case, traders look for developers who can write a desired application in the MQL5 Freelance section and assign an order.

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.

There is currently a fair number of means for a comfortable remote monitoring of a trading account: mobile terminals, push notifications, working with ICQ. But it all requires Internet connection. This article describes the process of creating an Expert Advisor that will allow you to stay in touch with your trading terminal even when mobile Internet is not available, through calls and text messaging.

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.

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.

The article describes a method of automated creation of neural network EAs using MQL5 Wizard and Hlaiman EA Generator. It shows you how you can easily start working with neural networks, without having to learn the entire body of theoretical information and writing your own code.

This is the continuation of Another MQL5 OOP class article which showed you how to build a simple OO EA from scratch and gave you some tips on object-oriented programming. Today I am showing you the technical basics needed to develop an EA able to trade the news. My goal is to keep on giving you ideas about OOP and also cover a new topic in this series of articles, working with the file system.

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.

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.

This article provides a small example demonstrating the implementation of an Expert Advisor whose parameters can be controlled from the user panel. When changing the parameters "on the fly", the Expert Advisor writes the values obtained from the info panel to a file to further read them from the file and display accordingly on the panel. This article may be relevant to those who trade manually or in semi-automatic mode.

This article centers around strategies that actively use pending orders, a metalanguage that can be created to formally describe such strategies and the use of a multi-purpose Expert Advisor whose operation is based on those descriptions

Nowadays, every trader must have heard of neural networks and knows how cool it is to use them. The majority believes that those who can deal with neural networks are some kind of superhuman. In this article, I will try to explain to you the neural network architecture, describe its applications and show examples of practical use.