Articles on the MQL5 programming and use of trading robots

The main advantage of trading robots lies in the ability to work 24 hours a day on a remote VPS server. But sometimes it is necessary to intervene in their work, while there may be no direct access to the server. Is it possible to manage EAs remotely? The article proposes one of the options for controlling EAs via external commands.

This class library can be added to an MetaTrader 5 Expert Advisor to enable it to be written with an order-centric approach broadly similar to MetaTrader 4, in comparison to the position-based approach of MetaTrader 5. It does this by keeping track of virtual orders at the MetaTrader 5 client terminal, while maintaining a protective broker stop for each position for disaster protection.

For a long time multi-currency analysis and multi-currency trading has been of interest to people. The opportunity to implement a full fledged multi-currency regime became possible only with the public release of MetaTrader 5 and the MQL5 programming language. In this article we propose a way to analyze and process all incoming ticks for several symbols. As an illustration, let's consider a multi-currency RSI indicator of the USDx dollar index.

This article's objective is to study profitability of algorithms with different entries into trades and exits using trailing stop. Entry types to be used are random entry and reverse entry. Stop orders to be used are trailing stop and trailing take. The article demonstrates money-making algorithms with a profitability of about 30% per annum.

The Strategy Tester in the MetaTrader 5 trading platform provides only two optimization options: complete search of parameters and genetic algorithm. This article proposes a new method for optimizing trading strategies — Simulated annealing. The method's algorithm, its implementation and integration into any Expert Advisor are considered. The developed algorithm is tested on the Moving Average EA.

Time has been a great value throughout the history of mankind, and we strive not to waste it unnecessarily. This article will tell you how to accelerate the work of your Expert Advisor if your computer has a multi-core processor. Moreover, the implementation of the proposed method does not require the knowledge of any other languages besides MQL5.

In this article, we demonstrate features of botbrains.app - a no-code platform for trading robots development. To create a trading robot you don't need to write any code - just drag and drop the necessary blocks onto the scheme, set their parameters, and establish connections between them.

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.

In the article, we will apply Reinforcement learning to develop self-learning Expert Advisors. In the previous article, we considered the Random Decision Forest algorithm and wrote a simple self-learning EA based on Reinforcement learning. The main advantages of such an approach (trading algorithm development simplicity and high "training" speed) were outlined. Reinforcement learning (RL) is easily incorporated into any trading EA and speeds up its optimization.

This article discusses the CSignal and CSignals classes which will be used in cross-platform expert advisors. It examines the differences between MQL4 and MQL5 on how particular data needed for evaluation of trade signals are accessed to ensure that the code written will be compatible with both compilers.

Functions and code snippets that simplify and clarify the handling of time, broker offset, and the changes to summer or winter time. Accurate timing may be a crucial element in trading. At the current hour, is the stock exchange in London or New York already open or not yet open, when does the trading time for Forex trading start and end? For a trader who trades manually and live, this is not a big problem.

In previous articles within this series, we tried various methods for creating a more or less profitable grid Expert Advisor. Now we will try to increase the EA profitability through diversification. Our ultimate goal is to reach 100% profit per year with the maximum balance drawdown no more than 20%.

The article gives a description of ways of use of the multiple regression analysis for development of trading systems. It demonstrates the use of the regression analysis for strategy search automation. A regression equation generated and integrated in an EA without requiring high proficiency in programming is given as an example.

This article discusses the implementation of various methods of time filtering a cross-platform expert advisor. The time filter classes are responsible for checking whether or not a given time falls under a certain time configuration setting.

The article dwells on gaps — significant differences between a close price of a previous timeframe and an open price of the next one, as well as on forecasting a daily bar direction. Applying the GetOpenFileName function by the system DLL is considered as well.

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.

In this article we are going to analyze the NRTR indicator and create a trading system based on this indicator. We are going to develop a module of trading signals that can be used in creating strategies based on a combination of NRTR with additional trend confirmation indicators.

Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode.

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.

Many researchers do not pay enough attention to determining the price behavior. At the same time, complex methods are used, which very often are simply “black boxes”, such as machine learning or neural networks. The most important question arising in that case is what data to submit for training a particular model.

Efficiency of any trading robot depends on the correct selection of its parameters (optimization). However, parameters that are considered optimal for one time interval may not retain their effectiveness in another period of trading history. Besides, EAs showing profit during tests turn out to be loss-making in real time. The issue of continuous optimization comes to the fore here. When facing plenty of routine work, humans always look for ways to automate it. In this article, I propose a non-standard approach to solving this issue.

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.

The article arranges the work of an account object on a new base object of all library objects, improves the CBaseObj base object and tests setting tracked parameters, as well as receiving events for any library objects.

Today, many traders switch to automated trading systems which can require additional setup or can be fully automated and ready to use. However, there is a considerable part of traders who prefer trading manually, in the old fashioned way. In this article, we will create toolkit for quick manual trading, using hotkeys, and for performing typical trading actions in one click.

Is it allowed to trade this symbol on Monday? Is there enough money to open position? How big is the loss if Stop Loss triggers? How to limit the number of pending orders? Was the trade operation executed at the current bar or at the previous one? If a trade robot cannot perform this kind of verifications, then any trade strategy can turn into a losing one. This article shows the examples of verifications that are useful in any Expert Advisor.

It is essential to detect whether a market is flat or not for many strategies. Using the well known ADX we demonstrate how we can use the Strategy Tester not only to optimize this indicator for our specific purpose, but as well we can decide whether this indicator will meet our needs and get to know the average range of the flat and trend markets which might be quite important to determine stops and targets of the markets.

The article deals with a simple approach to creating an automated trading system based on the chart linear markup and offers a ready-made Expert Advisor using the standard properties of the MetaTrader 4 and 5 objects and supporting the main trading operations.

In the first part of the article, I have described a modified ZigZag indicator and a class for receiving data of that type of indicators. Here, I will show how to develop indicators based on these tools and write an EA for tests that features making deals according to signals formed by ZigZag indicator. As an addition, the article will introduce a new version of the EasyAndFast library for developing graphical user interfaces.

The article provides a description of a universal method for analyzing and converting data from HTML documents based on CSS selectors. Trading reports, tester reports, your favorite economic calendars, public signals, account monitoring and additional online quote sources will become available straight from MQL.

This article describes the construction of the custom optimization criterion R-squared. This criterion can be used to estimate the quality of a strategy's balance curve and to select the most smoothly growing and stable strategies. The work discusses the principles of its construction and statistical methods used in estimation of properties and quality of this metric.

The article provides a critical examination of regular divergence and efficiency of various indicators. In addition, it contains filtering options for an increased analysis accuracy and features description of non-standard solutions. As a result, we will create a new tool for solving the technical task.

In this article, I will share with you one of the methods of how to trade bands. This time we will consider Envelopes and will see how easy it is to create some strategies based on the Envelopes.

The article discusses the methods for building and training ensembles of neural networks with bagging structure. It also determines the peculiarities of hyperparameter optimization for individual neural network classifiers that make up the ensemble. The quality of the optimized neural network obtained in the previous article of the series is compared with the quality of the created ensemble of neural networks. Possibilities of further improving the quality of the ensemble's classification are considered.

The article compares the time and results of Expert Advisors' optimization using genetic algorithms and those obtained by simple search.

The generator of trading strategies of the MQL5 Wizard greatly simplifies testing of trading ideas. The article describes how to develop a custom risk and money management module and enable it in the MQL5 Wizard. As an example we've considered a money management algorithm, in which the size of the trade volume is determined by the results of the previous deal. The structure and format of description of the created class for the MQL5 Wizard are also discussed in the article.

In this article, we will continue our series about designing a trading system using the most popular indicators and we will talk about the average directional index (ADX) indicator. We will learn this indicator in detail to understand it well and we will learn how we to use it through a simple strategy. By learning something deeply we can get more insights and we can use it better.