Articles on trading system automation in MQL5

In this article, we will learn a new tool from our series: we will learn how to design a trading system based on one of the most popular technical indicators Moving Average Convergence Divergence (MACD).

The article aims to describe the main features of Forex trading as simply and quickly as possible, as well as share some basic ideas with beginners. It also attempts to answer the most tantalizing questions in the trading community along with showcasing the development of a simple indicator.

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.

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.

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.

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 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.

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.

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 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.

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.

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.

Support Vector Machines have long been used in fields such as bioinformatics and applied mathematics to assess complex data sets and extract useful patterns that can be used to classify data. This article looks at what a support vector machine is, how they work and why they can be so useful in extracting complex patterns. We then investigate how they can be applied to the market and potentially used to advise on trades. Using the Support Vector Machine Learning Tool, the article provides worked examples that allow readers to experiment with their own trading.

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.

How to create a trading signal generator based on a custom indicator? How to create a custom indicator? How to get access to custom indicator data? Why do we need the IS_PATTERN_USAGE(0) structure and model 0?

The article describes the automation of trend lines plotting based on the Fractals indicator using MQL4 and MQL5. The article structure provides a comparative view of the solution for two languages. Trend lines are plotted using two last known fractals.

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.

The knowledge of programming languages is no longer a prerequisite for creating trading robots. Earlier lack of programming skills was an impassable obstacle to the implementation of one's own trading strategies, but with the emergence of the MQL5 Wizard, the situation radically changed. Novice traders can stop worrying because of the lack of programming experience - with the new Wizard, which allows you to generate Expert Advisor code, it is not necessary.

In this article, we finish testing the patterns that can be detected when trading currency pair baskets. Here we present the results of testing the patterns tracking the movement of pair's currencies relative to each other.

In the previous article, we considered application of Merrill patterns to various data, such as to a price value on a currency symbol chart and values of standard MetaTrader 5 indicators: ATR, WPR, CCI, RSI, among others. Now, let us try to create a strategy construction set based on Merrill patterns.

While analyzing a huge number of trading strategies, orders for development of applications for MetaTrader 5 and MetaTrader 4 terminals and various MetaTrader websites, I came to the conclusion that all this diversity is based mostly on the same elementary functions, actions and values appearing regularly in different programs. This resulted in DoEasy cross-platform library for easy and quick development of МetaТrader 5 and МetaТrader 4 applications.

In this article, we will consider creation of a symbol collection based on the abstract symbol object developed in the previous article. The abstract symbol descendants are to clarify a symbol data and define the availability of the basic symbol object properties in a program. Such symbol objects are to be distinguished by their affiliation with groups.

In this article, we start the development of the indicator buffer classes for the DoEasy library. We will create the base class of the abstract buffer which is to be used as a foundation for the development of different class types of indicator buffers.

In this article, I will tell you how to successfully trade by merging a very well-known strategy and a neural network. It will be about the Thomas DeMark's Sequential strategy with the use of an artificial intelligence system. Only the first part of the strategy will be applied, using the Setup and Intersection signals.

Markets dropped down by more that 30% within one month. It seems to be the best time for testing grid- and martingale-based Expert Advisors. This article is an unplanned continuation of the series "Creating a Cross-Platform Grid EA". The current market provides an opportunity to arrange a stress rest for the grid EA. So, let's use this opportunity and test our Expert Advisor.

In this article we are going to show how to explore the Standard Library of Trading Strategy Classes and how to add Custom Strategies and Filters/Signals using the Patterns-and-Models logic of the MQL5 Wizard. In the end you will be able easily add your own strategies using MetaTrader 5 standard indicators, and MQL5 Wizard will create a clean and powerful code and fully functional Expert Advisor.

If we thoroughly examine any complex trading system, we will see that it is based on a set of simple trading signals. Therefore, there is no need for novice developers to start writing complex algorithms immediately. This article provides an example of a trading system that uses semaphore indicators to perform deals.

The article deals with storing data in the program's source code and creating audio and graphical files out of them. When developing an application, we often need audio and images. The MQL language features several methods of using such data.

In this article we will consider in detail the martingale system. We will review whether this system can be applied in trading and how to use it in order to minimize risks. The main disadvantage of this simple system is the probability of losing the entire deposit. This fact must be taken into account, if you decide to trade using the martingale technique.

The aim of this article is to investigate the possibilities of trade automation and the analysis, on the basis of some ideas from a book by James Hyerczyk "Pattern, Price & Time: Using Gann Theory in Trading Systems" in the form of indicators and Expert Advisor. Without claiming to be exhaustive, here we investigate only the Model - the first part of the Gann theory.

The article considers three methods which can be used to increase the classification quality of bagging ensembles, and their efficiency is estimated. The effects of optimization of the ELM neural network hyperparameters and postprocessing parameters are evaluated.

We continue the development of the functionality allowing users to trade using pending requests. In this article, we are going to implement the ability to place pending orders under certain conditions.

EA Tree is the first drag and drop MetaTrader MQL5 Expert Advisor builder. You can create complex MQL5 using a very easy to use graphical user interface. In EA Tree, Expert Advisors are created by connecting boxes together. Boxes may contain MQL5 functions, technical indicators, custom indicators, or values. Using the "tree of boxes", EA Tree generates the MQL5 code of the Expert Advisor.

There are lots of chart types that provide information on the current market situation. Many of them, such as Point and Figure chart, are the legacy of the remote past. The article describes an example of Point and Figure charting using a real time indicator.

In the previous articles, we checked the concept of pending trading requests. A pending request is, in fact, a common trading order executed by a certain condition. In this article, we are going to create full-fledged classes of pending request objects — a base request object and its descendants.

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.