MQL5 Programs Market

In this article, we will finally solve the problems with the simulation of ticks on a one-minute bar so that they can coexist with real ticks. This will help us avoid problems in the future. The material presented here is for educational purposes only. Under no circumstances should the application be viewed for any purpose other than to learn and master the concepts presented.

In this article, we introduce a trade layering strategy that combines MACD and RSI indicators with statistical methods to automate dynamic trading in MQL5. We explore the architecture of this cascading approach, detail its implementation through key code segments, and guide readers on backtesting to optimize performance. Finally, we conclude by highlighting the strategy’s potential and setting the stage for further enhancements in automated trading.

We continue to study algorithms for extracting features from a point cloud. In this article, we will get acquainted with the mechanisms for increasing the efficiency of the PointNet method.

In this discussion, we explore how to retrieve real-time market data and trading account information, perform various calculations, and display the results on a custom panel. To achieve this, we will dive deeper into developing an AnalyticsPanel class that encapsulates all these features, including panel creation. This effort is part of our ongoing expansion of the New Admin Panel EA, introducing advanced functionalities using modular design principles and best practices for code organization.

In this article, you'll learn how to build a price action indicator in MQL5, focusing on key points like low (L), high (H), higher low (HL), higher high (HH), lower low (LL), and lower high (LH) for analyzing trends. You'll also explore how to identify the premium and discount zones, mark the 50% retracement level, and use the risk-reward ratio to calculate profit targets. The article also covers determining entry points, stop loss (SL), and take profit (TP) levels based on the trend structure.

Depth of Market is undoubtedly a very important element for executing fast trades, especially in High Frequency Trading (HFT) algorithms. In this series of articles, we will look at this type of trading events that can be obtained through a broker on many tradable symbols. We will start with an indicator, where you can customize the color palette, position and size of the histogram displayed directly on the chart. We will also look at how to generate BookEvent events to test the indicator under certain conditions. Other possible topics for future articles include how to store price distribution data and how to use it in a strategy tester.

This article describes the fundamentals of portfolio-level statistical arbitrage. Its goal is to facilitate the understanding of the principles of statistical arbitrage to readers without deep math knowledge and propose a starting point conceptual framework. The article includes a working Expert Advisor, some notes about its one-year backtest, and the respective backtest configuration settings (.ini file) for the reproduction of the experiment.