MQL4 and MQL5 Programming Articles

This article is a logical continuation of the previous one. It highlights the facts that confirm the conclusions made in the first article. These facts were revealed within ten years after its publication. They are centered around three detected dynamic transient functions describing the patterns in market price changes.

The article deals with the most common errors that occur in developing and using of an Expert Advisor. An exemplary safe automated trading system is described, as well.

"Everyone who is struggling with programming and who were not able to participate in this year's competition, know that it becomes a lot easier in time", said Juan Pablo Alonso Escobar (JPAlonso), the hero of today's interview.

In this article, I will expand the functionality of chart objects and arrange navigation through charts, creation of screenshots, as well as saving and applying templates to charts. Also, I will implement auto update of the collection of chart objects, their windows and indicators within them.

Is there any correlation between the past price behavior and its future trends? Why does the price repeat today the character of its previous day movement? Can the statistics be used to forecast the price dynamics? There is an answer, and it is positive. If you have any doubt, then this article is for you. I'll tell how to create a working filter for a trading system in MQL5, revealing an interesting pattern in price changes.

This is the second article from the series "MQL4 Language for Newbies". Now we will examine more complex and advanced constructions of the language, learn new options and see, how they can be applied in everyday practice. You will get acquainted with a new cycle type 'while', new condition type 'switch', operators 'break' and 'continue'. Besides you will learn to write your own functions and work with multidimensional arrays. And for a dessert I have prepared an explanation about a preprocessor.

It will soon be a year and a half since the MQL5 Cloud Network has been launched. This leading edge event ushered in a new era of algorithmic trading - now with a couple of clicks, traders can have hundreds and thousands of computing cores at their disposal for the optimization of their trading strategies.

In this article the author continues to analyze implementation algorithms of simplest trading systems and describes some relevant details of using optimization results. The article will be useful for beginning traders and EA writers.

We will begin the journey to explore the steps and workflow on how to base development for MetaTrader 5 platform solely on Linux system in which the final product works seamlessly on both Windows and Linux system. We will get to know Wine, and Mingw; both are the essential tools to make cross-platform development works. Especially Mingw for its threading implementations (POSIX, and Win32) that we need to consider in choosing which one to go with. We then build a proof-of-concept DLL and consume it in MQL5 code, finally compare the performance of both threading implementations. All for your foundation to expand further on your own. You should be comfortable building MT related tools on Linux after reading this article.

In the previous articles, we started creating a large cross-platform library simplifying the development of programs for MetaTrader 5 and MetaTrader 4 platforms. In the eighth part, we implemented the class for tracking order and position modification events. Here, we will improve the library by making it fully compatible with MQL4.

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.

The article describes creation of an indicator that would display the support/resistance levels using up/down fractals.

Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. In the previous article, we started to develop an order system that we will use in our automated EA. However, we have created only one of the necessary functions.

The construction of various types of diagrams is an essential part of the analyses of the market situation and the testing of a trading system. Frequently, in order to construct a nice looking diagram, it is necessary to organize the data output into a file, after which it is used in applications such as MS Excel. This is not very convenient and deprives us of the ability to dynamically update the data. Google Charts API provided the means for creating charts in online modes, by sending a special request to the server. In this article we attempt to automate the process of creating such a request and obtaining a chart from the Google server.

A short description of various illusions that come up when people trade using martingale betting strategies or misuse spiking and the like approaches.

Description of a step-by-step Linux-desktop setup using a non-emulator wine for running MetaTrader 4 Client Terminal on it.

In this article, I will create the list for storing tick data of a single symbol and check its creation and retrieval of required data in an EA. Tick data lists that are individual for each used symbol will further constitute a collection of tick data.

Indicator emissions are a little-studied area of market research. Primarily, this is due to the difficulty of analysis that is caused by the processing of very large arrays of time-varying data. Existing graphical analysis is too resource intensive and has therefore triggered the development of a parsimonious algorithm that uses time series of emissions. This article demonstrates how visual (intuitive image) analysis can be replaced with the study of integral characteristics of emissions. It can be of interest to both traders and developers of automated trading systems.