Articles on manual and algorithmic trading in MetaTrader 5

The main point of this article is to show a practical way to implement an effective MM. This can be achieved only by using a certain kind of strategies that we need to identify and describe first. In the following we’ll cover the basic concepts of how to build such a strategy and we’ll point out the common mistakes which always end up in draining a trader’s account.

Mean reversion is a type of contrarian trading where the trader expects the price to return to some form of equilibrium which is generally measured by a mean or another central tendency statistic.

Finding rules for a trade system and programming them in an Expert Advisor is a half of the job. Somehow, you need to correct the operation of the Expert Advisor as it accumulates the results of trading. This article describes one of approaches, which allows improving performance of an Expert Advisor through creation of a feedback that measures slope of the balance curve.

The article deals with realization of charts without skipped bars.

This article considers BookEvent - a Depth of Market event, and the principle of its processing. An MQL program, handling states of Depth of Market, serves as an example. It is written using the object-oriented approach. Results of handling are displayed on the screen as a panel and Depth of Market levels.

The MetaTrader 5 platform allows developing and testing trading robots that simultaneously trade multiple financial instruments. The built-in Strategy Tester automatically downloads required tick history from the broker's server taking into account contract specifications, so the developer does not need to do anything manually. This makes it possible to easily and reliably reproduce trading environment conditions, including even millisecond intervals between the arrival of ticks on different symbols. In this article we will demonstrate the development and testing of a spread strategy on two Moscow Exchange futures.

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.

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.

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.

In this article, we build an MQL5 EA that detects regular RSI divergences using swing points with strength, bar limits, and tolerance checks. It executes trades on bullish or bearish signals with fixed lots, SL/TP in pips, and optional trailing stops. Visuals include colored lines on charts and labeled swings for better strategy insights.

We continue to study machine learning methods. With this article, we begin another big topic, Reinforcement Learning. This approach allows the models to set up certain strategies for solving the problems. We can expect that this property of reinforcement learning will open up new horizons for building trading strategies.

Trading Signals service recently introduced in MetaTrader 5 allows traders to copy trading operations of any signals provider. Users can select any signal, subscribe to it and all deals will be copied at their accounts. Signals providers can set their subscription prices and receive a fixed monthly fee from their subscribers.

In this article we will check the well-known statement that "The whole day trading depends on how the Asian session is traded".

In this article, we will consider the emission of indicators - a new approach to the market research. The calculation of emission is based on the intersection of different indicators: more and more points with different colors and shapes appear after each tick. They form numerous clusters like nebulae, clouds, tracks, lines, arcs, etc. These shapes help to detect the invisible springs and forces that affect the movement of market prices.

What is social trading? It is a mutually beneficial cooperation of traders and investors whereby successful traders allow monitoring of their trading and potential investors take the opportunity to monitor their performance and copy trades of those who look more promising.

In the previous article, we developed the visual part of the application, as well as the basic interaction of GUI elements. This time we are going to add internal logic and the algorithm of trading signal data preparation, as well us the ability to set up signals, to search them and to visualize them in the monitor.