Algorithmic Trading Articles for Experts

Trading with the MQL5 Economic Calendar (Part 8): Optimizing News-Driven Backtesting with Smart Event Filtering and Targeted Logs

In this article, we optimize our economic calendar with smart event filtering and targeted logging for faster, clearer backtesting in live and offline modes. We streamline event processing and focus logs on critical trade and dashboard events, enhancing strategy visualization. These improvements enable seamless testing and refinement of news-driven trading strategies.

Automating Trading Strategies in MQL5 (Part 17): Mastering the Grid-Mart Scalping Strategy with a Dynamic Dashboard

In this article, we explore the Grid-Mart Scalping Strategy, automating it in MQL5 with a dynamic dashboard for real-time trading insights. We detail its grid-based Martingale logic and risk management features. We also guide backtesting and deployment for robust performance.

Raw Code Optimization and Tweaking for Improving Back-Test Results

Enhance your MQL5 code by optimizing logic, refining calculations, and reducing execution time to improve back-test accuracy. Fine-tune parameters, optimize loops, and eliminate inefficiencies for better performance.

Forecasting exchange rates using classic machine learning methods: Logit and Probit models

In the article, an attempt is made to build a trading EA for predicting exchange rate quotes. The algorithm is based on classical classification models - logistic and probit regression. The likelihood ratio criterion is used as a filter for trading signals.

MQL5 Trading Tools (Part 2): Enhancing the Interactive Trade Assistant with Dynamic Visual Feedback

In this article, we upgrade our Trade Assistant Tool by adding drag-and-drop panel functionality and hover effects to make the interface more intuitive and responsive. We refine the tool to validate real-time order setups, ensuring accurate trade configurations relative to market prices. We also backtest these enhancements to confirm their reliability.

Neural Networks in Trading: Hierarchical Feature Learning for Point Clouds

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.

MQL5 Trading Tools (Part 1): Building an Interactive Visual Pending Orders Trade Assistant Tool

In this article, we introduce the development of an interactive Trade Assistant Tool in MQL5, designed to simplify placing pending orders in Forex trading. We outline the conceptual design, focusing on a user-friendly GUI for setting entry, stop-loss, and take-profit levels visually on the chart. Additionally, we detail the MQL5 implementation and backtesting process to ensure the tool’s reliability, setting the stage for advanced features in the preceding parts.

Neural Networks in Trading: Hierarchical Vector Transformer (HiVT)

We invite you to get acquainted with the Hierarchical Vector Transformer (HiVT) method, which was developed for fast and accurate forecasting of multimodal time series.

Neural Networks in Trading: Unified Trajectory Generation Model (UniTraj)

Understanding agent behavior is important in many different areas, but most methods focus on just one of the tasks (understanding, noise removal, or prediction), which reduces their effectiveness in real-world scenarios. In this article, we will get acquainted with a model that can adapt to solving various problems.

Implementing a Rapid-Fire Trading Strategy Algorithm with Parabolic SAR and Simple Moving Average (SMA) in MQL5

In this article, we develop a Rapid-Fire Trading Expert Advisor in MQL5, leveraging the Parabolic SAR and Simple Moving Average (SMA) indicators to create a responsive trading strategy. We detail the strategy’s implementation, including indicator usage, signal generation, and the testing and optimization process.

This MetaTrader 5 Expert Advisor implements a Scalping OrderFlow strategy with advanced risk management. It uses multiple technical indicators to identify trading opportunities based on order flow imbalances. Backtesting shows potential profitability but highlights the need for further optimization, especially in risk management and trade outcome ratios. Suitable for experienced traders, it requires thorough testing and understanding before live deployment.

Creating Dynamic MQL5 Graphical Interfaces through Resource-Driven Image Scaling with Bicubic Interpolation on Trading Charts

In this article, we explore dynamic MQL5 graphical interfaces, using bicubic interpolation for high-quality image scaling on trading charts. We detail flexible positioning options, enabling dynamic centering or corner anchoring with custom offsets.

Build Self Optimizing Expert Advisors With MQL5 And Python (Part II): Tuning Deep Neural Networks

Machine learning models come with various adjustable parameters. In this series of articles, we will explore how to customize your AI models to fit your specific market using the SciPy library.

Building a Custom Market Regime Detection System in MQL5 (Part 2): Expert Advisor

This article details building an adaptive Expert Advisor (MarketRegimeEA) using the regime detector from Part 1. It automatically switches trading strategies and risk parameters for trending, ranging, or volatile markets. Practical optimization, transition handling, and a multi-timeframe indicator are included.

Websockets for MetaTrader 5: Asynchronous client connections with the Windows API

This article details the development of a custom dynamically linked library designed to facilitate asynchronous websocket client connections for MetaTrader programs.

Implementing a Bollinger Bands Trading Strategy with MQL5: A Step-by-Step Guide

A step-by-step guide to implementing an automated trading algorithm in MQL5 based on the Bollinger Bands trading strategy. A detailed tutorial based on creating an Expert Advisor that can be useful for traders.

Automating Trading Strategies in MQL5 (Part 3): The Zone Recovery RSI System for Dynamic Trade Management

In this article, we create a Zone Recovery RSI EA System in MQL5, using RSI signals to trigger trades and a recovery strategy to manage losses. We implement a "ZoneRecovery" class to automate trade entries, recovery logic, and position management. The article concludes with backtesting insights to optimize performance and enhance the EA’s effectiveness.

Neural Networks in Trading: Exploring the Local Structure of Data

Effective identification and preservation of the local structure of market data in noisy conditions is a critical task in trading. The use of the Self-Attention mechanism has shown promising results in processing such data; however, the classical approach does not account for the local characteristics of the underlying structure. In this article, I introduce an algorithm capable of incorporating these structural dependencies.

Build Self Optimizing Expert Advisors in MQL5 (Part 3): Dynamic Trend Following and Mean Reversion Strategies

Financial markets are typically classified as either in a range mode or a trending mode. This static view of the market may make it easier for us to trade in the short run. However, it is disconnected from the reality of the market. In this article, we look to better understand how exactly financial markets move between these 2 possible modes and how we can use our new understanding of market behavior to gain confidence in our algorithmic trading strategies.

News Trading Made Easy (Part 6): Performing Trades (III)

In this article news filtration for individual news events based on their IDs will be implemented. In addition, previous SQL queries will be improved to provide additional information or reduce the query's runtime. Furthermore, the code built in the previous articles will be made functional.

Neural Networks in Trading: Scene-Aware Object Detection (HyperDet3D)

We invite you to get acquainted with a new approach to detecting objects using hypernetworks. A hypernetwork generates weights for the main model, which allows taking into account the specifics of the current market situation. This approach allows us to improve forecasting accuracy by adapting the model to different trading conditions.

Price Action Analysis Toolkit Development Part (4): Analytics Forecaster EA

We are moving beyond simply viewing analyzed metrics on charts to a broader perspective that includes Telegram integration. This enhancement allows important results to be delivered directly to your mobile device via the Telegram app. Join us as we explore this journey together in this article.

Mastering File Operations in MQL5: From Basic I/O to Building a Custom CSV Reader

This article focuses on essential MQL5 file-handling techniques, spanning trade logs, CSV processing, and external data integration. It offers both conceptual understanding and hands-on coding guidance. Readers will learn to build a custom CSV importer class step-by-step, gaining practical skills for real-world applications.

Neural Networks in Trading: Transformer for the Point Cloud (Pointformer)

In this article, we will talk about algorithms for using attention methods in solving problems of detecting objects in a point cloud. Object detection in point clouds is important for many real-world applications.

Building a Candlestick Trend Constraint Model (Part 9): Multiple Strategies Expert Advisor (III)

Welcome to the third installment of our trend series! Today, we’ll delve into the use of divergence as a strategy for identifying optimal entry points within the prevailing daily trend. We’ll also introduce a custom profit-locking mechanism, similar to a trailing stop-loss, but with unique enhancements. In addition, we’ll upgrade the Trend Constraint Expert to a more advanced version, incorporating a new trade execution condition to complement the existing ones. As we move forward, we’ll continue to explore the practical application of MQL5 in algorithmic development, providing you with more in-depth insights and actionable techniques.

Manual Backtesting Made Easy: Building a Custom Toolkit for Strategy Tester in MQL5

In this article, we design a custom MQL5 toolkit for easy manual backtesting in the Strategy Tester. We explain its design and implementation, focusing on interactive trade controls. We then show how to use it to test strategies effectively

Automating Trading Strategies in MQL5 (Part 14): Trade Layering Strategy with MACD-RSI Statistical Methods

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.

Creating a Trading Administrator Panel in MQL5 (Part IX): Code Organization (V): AnalyticsPanel Class

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.

Trading with the MQL5 Economic Calendar (Part 4): Implementing Real-Time News Updates in the Dashboard

This article enhances our Economic Calendar dashboard by implementing real-time news updates to keep market information current and actionable. We integrate live data fetching techniques in MQL5 to update events on the dashboard continuously, improving the responsiveness of the interface. This update ensures that we can access the latest economic news directly from the dashboard, optimizing trading decisions based on the freshest data.

Neural Networks in Trading: Point Cloud Analysis (PointNet)

Direct point cloud analysis avoids unnecessary data growth and improves the performance of models in classification and segmentation tasks. Such approaches demonstrate high performance and robustness to perturbations in the original data.

Quantitative approach to risk management: Applying VaR model to optimize multi-currency portfolio using Python and MetaTrader 5

This article explores the potential of the Value at Risk (VaR) model for multi-currency portfolio optimization. Using the power of Python and the functionality of MetaTrader 5, we demonstrate how to implement VaR analysis for efficient capital allocation and position management. From theoretical foundations to practical implementation, the article covers all aspects of applying one of the most robust risk calculation systems – VaR – in algorithmic trading.

Neural Networks in Trading: Hierarchical Vector Transformer (Final Part)

We continue studying the Hierarchical Vector Transformer method. In this article, we will complete the construction of the model. We will also train and test it on real historical data.

Automating Trading Strategies in MQL5 (Part 13): Building a Head and Shoulders Trading Algorithm

In this article, we automate the Head and Shoulders pattern in MQL5. We analyze its architecture, implement an EA to detect and trade it, and backtest the results. The process reveals a practical trading algorithm with room for refinement.

Creating a Trading Administrator Panel in MQL5 (Part VII): Trusted User, Recovery and Cryptography

Security prompts, such as those triggered every time you refresh the chart, add a new pair to the chat with the Admin Panel EA, or restart the terminal, can become tedious. In this discussion, we will explore and implement a feature that tracks the number of login attempts to identify a trusted user. After a set number of failed attempts, the application will transition to an advanced login procedure, which also facilitates passcode recovery for users who may have forgotten it. Additionally, we will cover how cryptography can be effectively integrated into the Admin Panel to enhance security.

Creating a Trading Administrator Panel in MQL5 (Part VI):Trade Management Panel (II)

In this article, we enhance the Trade Management Panel of our multi-functional Admin Panel. We introduce a powerful helper function that simplifies the code, improving readability, maintainability, and efficiency. We will also demonstrate how to seamlessly integrate additional buttons and enhance the interface to handle a wider range of trading tasks. Whether managing positions, adjusting orders, or simplifying user interactions, this guide will help you develop a robust, user-friendly Trade Management Panel.

Build Self Optimizing Expert Advisors in MQL5 (Part 6): Self Adapting Trading Rules (II)

This article explores optimizing RSI levels and periods for better trading signals. We introduce methods to estimate optimal RSI values and automate period selection using grid search and statistical models. Finally, we implement the solution in MQL5 while leveraging Python for analysis. Our approach aims to be pragmatic and straightforward to help you solve potentially complicated problems, with simplicity.

Automating Trading Strategies in MQL5 (Part 12): Implementing the Mitigation Order Blocks (MOB) Strategy

In this article, we build an MQL5 trading system that automates order block detection for Smart Money trading. We outline the strategy’s rules, implement the logic in MQL5, and integrate risk management for effective trade execution. Finally, we backtest the system to assess its performance and refine it for optimal results.

Price Action Analysis Toolkit Development (Part 16): Introducing Quarters Theory (II) — Intrusion Detector EA

In our previous article, we introduced a simple script called "The Quarters Drawer." Building on that foundation, we are now taking the next step by creating a monitor Expert Advisor (EA) to track these quarters and provide oversight regarding potential market reactions at these levels. Join us as we explore the process of developing a zone detection tool in this article.

Price Action Analysis Toolkit Development (Part 15): Introducing Quarters Theory (I) — Quarters Drawer Script

Points of support and resistance are critical levels that signal potential trend reversals and continuations. Although identifying these levels can be challenging, once you pinpoint them, you’re well-prepared to navigate the market. For further assistance, check out the Quarters Drawer tool featured in this article, it will help you identify both primary and minor support and resistance levels.

Creating a Trading Administrator Panel in MQL5 (Part VI): Multiple Functions Interface (I)

The Trading Administrator's role goes beyond just Telegram communications; they can also engage in various control activities, including order management, position tracking, and interface customization. In this article, we’ll share practical insights on expanding our program to support multiple functionalities in MQL5. This update aims to overcome the current Admin Panel's limitation of focusing primarily on communication, enabling it to handle a broader range of tasks.