MQL4 and MQL5 Programming Articles

Most of traders agree that the current market state analysis starts with the evaluation of higher chart timeframes. The analysis is performed downwards to lower timeframes until the one, at which deals are performed. This analysis method seems to be a mandatory part of professional approach for successful trading. In this article, we will discuss multi-timeframe indicators and their creation ways, as well as we will provide MQL5 code examples. In addition to the general evaluation of advantages and disadvantages, we will propose a new indicator approach using the MTF mode.

The article describes how to add the ability to work with Microsoft SQL Server database server to MQL5-based Expert Advisors. Import of functions from a DLL is used. The DLL is created using the Microsoft .NET platform and the C# language. The methods used in the article are also suitable for experts written in MQL4, with minor adjustments.

MetaTarder 4 build 600 features the new structure and location of the client terminal files. Now, MQL4 applications are placed in separate directories according to the program type (Expert Advisors, indicators or scripts). In most cases, the terminal data is now stored in a special data folder separated from the terminal installation location. In this article, we will describe in details how data is transferred, as well as the reasons for introducing the new storage system.

The article describes the Fibo levels-based trading system developed by Joe DiNapoli. The idea behind the system and the main concepts are explained, as well as a simple indicator is provided as an example for more clarity.

In early 2011 we released the first version of the MQL5 Wizard. This new application provides a simple and convenient tool to automatically generate trading robots. Any MetaTrader 5 user can create a custom Expert Advisor without even knowing how to program in MQL5.

This is the third article about the concept of pending requests. We are going to complete the tests of pending trading requests by creating the methods for closing positions, removing pending orders and modifying position and pending order parameters.

The complex codes consist of a set of simple codes. If you are familiar with them, it doesn't look so complicated. In this article, we will consider how to create an indicator with multiple indicator buffers. As an example, the Aroon indicator is analyzed in details, and two different versions of the code are presented.

This is the third article about the concept of pending requests. We are going to complete the tests of pending trading requests by creating the methods for closing positions, removing pending orders and modifying position and pending order parameters.

The article familiarizes the reader with exponential smoothing models used for short-term forecasting of time series. In addition, it touches upon the issues related to optimization and estimation of the forecast results and provides a few examples of scripts and indicators. This article will be useful as a first acquaintance with principles of forecasting on the basis of exponential smoothing models.

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 demonstrates how to utilize Depth of Market (DOM) programmatically and describes the operation principle of CMarketBook class, that can expand the Standard Library of MQL5 classes and offer convenient methods of using DOM.

The article covers the problem of development of active control panels in MQL5. Interface elements are managed by the event handling mechanism. Besides, the option of a flexible setup of control elements properties is available. The active control panel allows working with positions, as well setting, modifying and deleting market and pending orders.

In this article, we create a fully customizable session-based Opening Range Breakout (ORB) system in MQL5 that lets us set any desired session start time and range duration, automatically calculates the high and low of that opening period, and trades only confirmed breakouts in the direction of the move.

The article explores the advantages and disadvantages of trading in flat periods. The ten strategies created and tested within this article are based on the tracking of price movements inside a channel. Each strategy is provided with a filtering mechanism, which is aimed at avoiding false market entry signals.

Ever wanted to access tweets and/or post your trade signals on Twitter ? Search no more, these on-going article series will show you how to do it without using any DLL. Enjoy the journey of implementing Twitter API using MQL. In this first part, we will follow the glory path of authentication and authorization in accessing Twitter API.

In this article, we create a fully customizable session-based Opening Range Breakout (ORB) system in MQL5 that lets us set any desired session start time and range duration, automatically calculates the high and low of that opening period, and trades only confirmed breakouts in the direction of the move.

In this article the author talks about evolutionary calculations with the use of a personally developed genetic algorithm. He demonstrates the functioning of the algorithm, using examples, and provides practical recommendations for its usage.

You don't need to know what are polymorphism, encapsulation, etc. all about in to use object-oriented programming (OOP)... you may simply use these features. This article covers the basics of OOP with hands-on examples.

There are many strategies that can be used to filter generated signals based on any strategy, even by using the moving average itself which is the subject of this article. So, the objective of this article is to share with you some of Moving Average Strategies and how to design an algorithmic trading system.

This article will describe advanced adaptive indicators and their implementation in MQL5: Adaptive Cyber Cycle, Adaptive Center of Gravity and Adaptive RVI. All indicators were originally presented in "Cybernetic Analysis for Stocks and Futures" by John F. Ehlers.

There has been a recent rise of interest in the cluster analyses of the FOREX market. MQL5 opens up new possibilities of researching the trends of the movement of currency pairs. A key feature of MQL5, differentiating it from MQL4, is the possibility of using an unlimited amount of indicator buffers. This article describes an example of the creation of a multi-currency indicator.

In this article, we will consider the creation of two indicators: the tick indicator, which plots the tick chart of the price and tick candle indicator, which plot candles with the specified number of ticks. Each of the indicators writes the incoming prices into a file, and uses the saved data after the restart of the indicator (these data also can be used by the other programs)

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.

There are a lot of measures that allow determining the effectiveness and profitability of a trade system. However, traders are always ready to put any system to a new crash test. The article tells how the statistics based on measures of effectiveness can be used for the MetaTrader 5 platform. It includes the class for transformation of the interpretation of statistics by deals to the one that doesn't contradict the description given in the "Statistika dlya traderov" ("Statistics for Traders") book by S.V. Bulashev. It also includes an example of custom function for optimization.

In this article, I will continue the development of the topic by improving the flexibility of the previously created algorithm. The algorithm became more stable with an increase in the number of candles in the analysis window or with an increase in the threshold percentage of the overweight of falling or growing candles. I had to make a compromise and set a larger sample size for analysis or a larger percentage of the prevailing candle excess.

Automation of trading strategies involving graphical patterns requires the ability to search for extreme points on the charts for further processing and interpretation. Existing tools do not always provide such an ability. The algorithms described in the article allow finding all extreme points on charts. The tools discussed here are equally efficient both during trends and flat movements. The obtained results are not strongly affected by a selected timeframe and are only defined by a specified scale.

The next version of the Easy And Fast library (version 3) is presented in this article. Fixed certain flaws and added new features. More details further in the article.

This article deals with the theory and practical use of the algorithm for forecasting time series, based on the empirical decomposition mode. It proposes the MQL implementation of this method and presents test indicators and Expert Advisors.

In this article, we will complete the description of the pending request trading concept and create the functionality for removing pending orders, as well as modifying orders and positions under certain conditions. Thus, we are going to have the entire functionality enabling us to develop simple custom strategies, or rather EA behavior logic activated upon user-defined conditions.

The article presents a simple and fast method of creating graphical windows using Visual Studio with subsequent integration into the Expert Advisor's MQL code. The article is meant for non-specialist audiences and does not require any knowledge of C# and .Net technology.

In this article, we will complete the description of the pending request trading concept and create the functionality for removing pending orders, as well as modifying orders and positions under certain conditions. Thus, we are going to have the entire functionality enabling us to develop simple custom strategies, or rather EA behavior logic activated upon user-defined conditions.

Scalping automatic systems are rightfully regarded the pinnacle of algorithmic trading, but at the same time their code is the most difficult to write. In this article we will show how to build strategies based on analysis of incoming ticks using the built-in debugging tools and visual testing. Developing rules for entry and exit often require years of manual trading. But with the help of MetaTrader 5, you can quickly test any such strategy on real history.

Most Java coders will be familiar with the auto-generated documentation that can be created with JavaDocs. The idea is to add comments into the code in a semi-structured way that can then be extracted into an easy to navigate help file. The C++ world also has a number of documentation auto-generators, with Microsoft's SandCastle and Doxygen being two leaders. The article describes the use of Doxygen to create HTML help file from structured comments in MQL5 code. The experiment worked very well and I believe the help documentation that Doxygen produces from MQL5 code will add a great deal of value.

This article is dedicated to the Three Line Break chart, suggested by Steve Nison in his book "Beyond Candlesticks". The greatest advantage of this chart is that it allows filtering minor fluctuations of a price in relation to the previous movement. We are going to discuss the principle of the chart construction, the code of the indicator and some examples of trading strategies based on it.

In this article we will view seasonal characteristics of financial time series using Boxplot diagrams. Each separate boxplot (or box-and-whiskey diagram) provides a good visualization of how values are distributed along the dataset. Boxplots should not be confused with the candlestick charts, although they can be visually similar.

The article deals with the algorithm of developing stock indicators based on real volumes using the CopyTicks() and CopyTicksRange() functions. Some subtle aspects of developing such indicators, as well as their operation in real time and in the strategy tester are also described.