MQL4 and MQL5 Programming Articles

In this article we will perform an experiment: we will color optimization results. The color is determined by three parameters: the levels of red, green and blue (RGB). There are other color coding methods, which also use three parameters. Thus, three testing parameters can be converted to one color, which visually represents the values. Read this article to find out if such a representation can be useful.

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.

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%.

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.

Let us consider the button control. We will discuss examples of several classes for creating a simple button, buttons with extended functionality (icon button and split button) and interconnected buttons (button groups and radio button). Added to that, we will introduce some additions to existing classes for controls to broaden their capability.

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.

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.

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.

Mini Market Emulator is an indicator designed for partial emulation of work in the terminal. Presumably, it can be used to test "manual" strategies of market analysis and trading.

The MQL5.com website brings together traders from all over the world. Users publish articles, share free codes, sell products in the Market, perform Freelance orders and copy trading signals. You can communicate with them on the Forum, in trader chats and in MetaTrader channels.

The article provides the description of a simple HTML code parsing library using third-party components. In particular, it covers the possibilities of accessing data which cannot be retrieved using GET and POST requests. We will select a website with not too large pages and will try to obtain interesting data from this site.

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

In this article, we will consider the main aspects of integration of neural networks and the trading terminal, with the purpose of creating a fully featured trading robot.

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 is the first article in a series, in which I am going to describe a toolkit which enables manual application of chart graphics by utilizing keyboard shortcuts. It is very convenient: you press one key and a trendline appears, you press another key — this will create a Fibonacci fan with the necessary parameters. It will also be possible to switch timeframes, to rearrange layers or to delete all objects from the chart.

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 the previous article, we created the application framework, which we will use as the basis for all further work. In this part, we will proceed with the development: we will create the visual part of the application and will configure basic interaction of interface elements.

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.

The article considers real-time update of timeseries data and sending messages about the "New bar" event to the control program chart from all timeseries of all symbols for the ability to handle these events in custom programs. The "New tick" class is used to determine the need to update timeseries for the non-current chart symbol and periods.

The Expert Advisor plots the channel lines. The upper and lower channel lines act as support and resistance levels. The Expert Advisor marks datum points, provides sound notification every time the price reaches or crosses the channel lines and draws the relevant marks. Upon fractal formation, the corresponding arrows appear on the last bars. Line breakouts may suggest the possibility of a growing trend. The Expert Advisor is extensively commented throughout.

The concept of diversification of assets on financial markets is quiet old, and has always attracted beginner traders. In this article, the author proposes a maximally simple approach to a construction of a multi-currency Expert Advisor, for an initial introduction to this direction of trading strategies.

It is possible to start making money on MQL5.com right now without having to be a seller of Market applications or a profitable signals provider. Select the products you like and post links to them on various web resources. Attract potential customers and the profit is yours!

This article is an introduction to a series of articles about programming. It is assumed here that the reader has never dealt with programming before. So, this series starts from the very basics. Programming knowledge level: Absolute Beginner.

In this article, we develop a Nick Rypock Trailing Reverse (NRTR) trading system in MQL5 that uses channel indicators for reversal signals, enabling trend-following entries with hedging support for buys and sells. We incorporate risk management features like auto lot sizing based on equity or balance, fixed or dynamic stop-loss and take-profit levels using ATR multipliers, and position limits.

A portrait of a trader's behavior on the financial market. Author's own menu from the book "Как играть и выигрывать на бирже" ("How to speculate on stock exchange and win") by A. Elder.

In this article, we will continue expanding the functionality of the utility. This time, we will add the ability to display data that simplifies our trading. In particular, we are going to add High and Low prices of the previous day, round levels, High and Low prices of the year, session start time, etc.

The article considers one of the variants for Expert Advisor practical realization to trade DiNapoli levels using MQL5 standard tools. Its performance is tested and conclusions are made.

The trade Signals service develops in leaps and bounds. Trusting our funds to a signal provider, we would like to minimize the risk of losing our deposit. So how to puzzle out in this forest of trade signals? How to find the one that would produce profits? This paper proposes to create a tool for visually analyzing the history of trades on trade signals in a symbol chart.

After we send a trading order to the server, we need to check the error codes or the absence of errors. In this article, we will consider handling errors returned by the trade server and prepare for creating pending trading requests.

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.

We continue our discussion of the patterns traders can come across while trading currency baskets. In this part, we will consider the patterns formed when using combined trend indicators. Indicators based on a currency index are to be used as the analytical tool.

In this article, we will continue analyzing the algorithms of the CStrategy trading engine. The third part of the series contains the detailed analysis of examples of how to develop specific trading strategies using this approach. Special attention is paid to auxiliary algorithms — Expert Advisor logging system and data access using a conventional indexer (Close[1], Open[0] etc.)

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.

This article describes the process of creating an extension for the MetaTrader terminal. The solution discussed helps to automate the optimization process by running optimizations in other terminals. A few more articles will be written concerning this topic. The extension has been developed using the C# language and design patterns, which additionally demonstrates the ability to expand the terminal capabilities by developing custom modules, as well as the ability to create custom graphical user interfaces using the functionality of a preferred programming language.