Articles on manual and algorithmic trading in MetaTrader 5

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.

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.

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.

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.

The article deals with realization of charts without skipped bars.

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.

This article proposes another original approach to creating trading systems based on machine learning, using clustering and trade labeling for mean reversion strategies.

The article guides in demonstrating an automated algorithm based on EMA Crossovers for MetaTrader 5. Detailed information on all aspects of demonstrating an Expert Advisor in MQL5 and testing it in MetaTrader 5 - from analyzing price range behaviors to risk management.

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.

Create a trading journal using MetaTrader and Google Sheets! You will learn how to sync your trading data via HTTP POST and retrieve it using HTTP requests. In the end, You have a trading journal that will help you keep track of your trades effectively and efficiently.

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

This article teaches beginners how to build an Expert Advisor (EA) in MQL5 that trades based on chart pattern recognition using trend line breakouts and reversals. By learning how to retrieve trend line values dynamically and compare them with price action, readers will be able to develop EAs capable of identifying and trading chart patterns such as ascending and descending trend lines, channels, wedges, triangles, and more.

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.

This article explains the design of a prop-firm Expert Advisor for GOLD, featuring breakout filters, multi-timeframe analysis, robust risk management, and strict drawdown protection. The EA helps traders pass prop-firm challenges by avoiding rule breaches and stabilizing trade execution under volatile market conditions.

In this article, we enhance our Zone Recovery System by introducing trailing stops and multi-basket trading capabilities. We explore how the improved architecture uses dynamic trailing stops to lock in profits and a basket management system to handle multiple trade signals efficiently. Through implementation and backtesting, we demonstrate a more robust trading system tailored for adaptive market performance.