Articles on manual and algorithmic trading in MetaTrader 5

In this article, we will discuss how to develop a trading robot with minimum programming. Of course, MetaTrader 5 provides a high level of control over trading positions. However, using only the manual ability to place orders can be quite difficult and risky for less experienced users.

In this article, we will learn about Bollinger Bands which is one of the most popular indicators in the trading world. We will consider technical analysis and see how to design an algorithmic trading system based on the Bollinger Bands indicator.

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.

In this article, I decided to highlight the well-known Bernoulli scheme and to show how it can be used to describe trading-related data arrays. All this will then be used to create a self-adapting trading system. We will also look for a more generic algorithm, a special case of which is the Bernoulli formula, and will find an application for it.

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.

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.

Do you wish to become a successful Freelance developer on MQL5? If the answer is yes, this article is right for you.

Determing the broker offset and GMT automatically. Instead of asking the support of your broker, from whom you will probably receive an insufficient answer (who would be willing to explain a missing hour), we simply look ourselves how they time their prices in the weeks of the time changes — but not cumbersome by hand, we let a program do it — why do we have a PC after all.

A logical continuation of the earlier discussed topic would be the development of multifunctional mathematical models for trading tasks. In this article, I will describe the entire process related to the development of the first mathematical model describing fractals, from scratch. This model should become an important building block and be multifunctional and universal. It will build up our theoretical basis for further development of this idea.

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 this article, we will continue to study fractals and will pay special attention to summarizing all the material. To do this, I will try to bring all earlier developments into a compact form which would be convenient and understandable for practical application in trading.

In this article I will try to expand the classic concept of swap trading methods. I will explain why I have come to the conclusion that this concept deserves special attention and is absolutely recommended for study.

The article provides the description of the technology aimed at increasing the effectiveness of any automated trading system. It provides a brief explanation of the idea, as well as its underlying basics, possibilities and disadvantages.

I continue filling the algorithm with the minimum necessary functionality and testing the results. The profitability is quite low but the articles demonstrate the model of the fully automated profitable trading on completely different instruments traded on fundamentally different markets.

It is impossible to get a truly stable algorithm if we use optimization based on historical data to select parameters. A stable algorithm should be aware of what parameters are needed when working on any trading instrument at any time. It should not forecast or guess, it should know for sure.

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.

In the upcoming series of articles, I will demonstrate the development of self-adapting algorithms considering most market factors, as well as show how to systematize these situations, describe them in logic and take them into account in your trading activity. I will start with a very simple algorithm that will gradually acquire theory and evolve into a very complex project.

The article describes the basic principles and methods that allow you to analyze any strategy using spreadsheets (Excel, Calc, Google). The obtained results are compared with MetaTrader 5 tester.

Thomas DeMark Sequential is good at showing balance changes in the price movement. This is especially evident if we combine its signals with a level indicator, for example, Murray levels. The article is intended mostly for beginners and those who still cannot find their "Grail". I will also display some features of building levels that I have not seen on other forums. So, the article will probably be useful for advanced traders as well... Suggestions and reasonable criticism are welcome...

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.

The article considers the methodology for developing trading algorithms, in which a consistent scientific approach is used to analyze possible price patterns and to build trading algorithms based on these patterns. Development ideals are demonstrated using examples.

Traders often talk about trends and flats but very few of them really understand what a trend/flat really is and even fewer are able to clearly explain these concepts. Discussing these basic terms is often beset by a solid set of prejudices and misconceptions. However, if we want to make profit, we need to understand the mathematical and logical meaning of these concepts. In this article, I will take a closer look at the essence of trend and flat, as well as try to define whether the market structure is based on trend, flat or something else. I will also consider the most optimal strategies for making profit on trend and flat markets.

In this article, we consider encryption/decryption of objects in MetaTrader and in external applications. Our purpose is to determine the conditions under which the same results will be obtained with the same initial data.

In this article, we will expand the capabilities of the toolkit: we will add the ability to close trade positions upon specific conditions and will create tables for controlling market and pending orders, with the ability to edit these orders.

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.

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.

In the fifth article related to the creation of a trading signal monitor, we will consider composite signals and will implement the necessary functionality. In earlier versions, we used simple signals, such as RSI, WPR and CCI, and we also introduced the possibility to use custom indicators.

In this part, we expand the trading signal searching and editing system, as well as introduce the possibility to use custom indicators and add program localization. We have previously created a basic system for searching signals, but it was based on a small set of indicators and a simple set of search rules.