Reimagining Classic Strategies (Part 18): Searching For Candlestick Patterns
This article helps new community members search for and discover their own candlestick patterns. Describing these patterns can be daunting, as it requires manually searching and creatively identifying improvements. Here, we introduce the engulfing candlestick pattern and show how it can be enhanced for more profitable trading applications.
Automating Trading Strategies in MQL5 (Part 48): Order Blocks, Inducement, Break of Structure
We implement an MQL5 expert advisor that detects order blocks formed after consolidation breakouts and confirms them with fair value gaps. Each zone is validated by a break of structure and a preceding inducement, then filtered by the higher-timeframe trend. The program adds mitigation tracking, risk-based lot sizing, and two trailing stop modes, providing clear on-chart visuals and backtest-ready trade execution logic.
Multibot in MetaTrader (Part II): Improved dynamic template
Developing the theme of the previous article, I decided to create a more flexible and functional template that has greater capabilities and can be effectively used both in freelancing and as a base for developing multi-currency and multi-period EAs with the ability to integrate with external solutions.
Data Science and Machine Learning (Part 05): Decision Trees
Decision trees imitate the way humans think to classify data. Let's see how to build trees and use them to classify and predict some data. The main goal of the decision trees algorithm is to separate the data with impurity and into pure or close to nodes.
Automating Trading Strategies in MQL5 (Part 31): Creating a Price Action 3 Drives Harmonic Pattern System
In this article, we develop a 3 Drives Pattern system in MQL5 that identifies bullish and bearish 3 Drives harmonic patterns using pivot points and Fibonacci ratios, executing trades with customizable entry, stop loss, and take-profit levels based on user-selected options. We enhance trader insight with visual feedback through chart objects.
Creating an EA that works automatically (Part 08): OnTradeTransaction
In this article, we will see how to use the event handling system to quickly and efficiently process issues related to the order system. With this system the EA will work faster, so that it will not have to constantly search for the required data.
Build Self Optimizing Expert Advisors With MQL5 And Python
In this article, we will discuss how we can build Expert Advisors capable of autonomously selecting and changing trading strategies based on prevailing market conditions. We will learn about Markov Chains and how they can be helpful to us as algorithmic traders.
Deep Learning GRU model with Python to ONNX with EA, and GRU vs LSTM models
We will guide you through the entire process of DL with python to make a GRU ONNX model, culminating in the creation of an Expert Advisor (EA) designed for trading, and subsequently comparing GRU model with LSTM model.
Rebuy algorithm: Multicurrency trading simulation
In this article, we will create a mathematical model for simulating multicurrency pricing and complete the study of the diversification principle as part of the search for mechanisms to increase the trading efficiency, which I started in the previous article with theoretical calculations.
Automating The Market Sentiment Indicator
In this article, we automate a custom market sentiment indicator that classifies market conditions into bullish, bearish, risk-on, risk-off, and neutral. The Expert Advisor delivers real-time insights into prevailing sentiment while streamlining the analysis process for current market trends or direction.
Trading strategy based on the improved Doji candlestick pattern recognition indicator
The metabar-based indicator detected more candles than the conventional one. Let's check if this provides real benefit in the automated trading.
Other classes in DoEasy library (Part 68): Chart window object class and indicator object classes in the chart window
In this article, I will continue the development of the chart object class. I will add the list of chart window objects featuring the lists of available indicators.
Understanding MQL5 Object-Oriented Programming (OOP)
As developers, we need to learn how to create and develop software that can be reusable and flexible without duplicated code especially if we have different objects with different behaviors. This can be smoothly done by using object-oriented programming techniques and principles. In this article, we will present the basics of MQL5 Object-Oriented programming to understand how we can use principles and practices of this critical topic in our software.
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
Creating an EA that works automatically (Part 09): Automation (I)
Although the creation of an automated EA is not a very difficult task, however, many mistakes can be made without the necessary knowledge. In this article, we will look at how to build the first level of automation, which consists in creating a trigger to activate breakeven and a trailing stop level.
Self Optimizing Expert Advisors in MQL5 (Part 9): Double Moving Average Crossover
This article outlines the design of a double moving average crossover strategy that uses signals from a higher timeframe (D1) to guide entries on a lower timeframe (M15), with stop-loss levels calculated from an intermediate risk timeframe (H4). It introduces system constants, custom enumerations, and logic for trend-following and mean-reverting modes, while emphasizing modularity and future optimization using a genetic algorithm. The approach allows for flexible entry and exit conditions, aiming to reduce signal lag and improve trade timing by aligning lower-timeframe entries with higher-timeframe trends.
Understanding Programming Paradigms (Part 1): A Procedural Approach to Developing a Price Action Expert Advisor
Learn about programming paradigms and their application in MQL5 code. This article explores the specifics of procedural programming, offering hands-on experience through a practical example. You'll learn how to develop a price action expert advisor using the EMA indicator and candlestick price data. Additionally, the article introduces you to the functional programming paradigm.
How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 7): ZigZag with Awesome Oscillator Indicators Signal
The multi-currency expert advisor in this article is an expert advisor or automated trading that uses ZigZag indicator which are filtered with the Awesome Oscillator or filter each other's signals.
Creating an EA that works automatically (Part 04): Manual triggers (I)
Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode.
Adaptive Smart Money Architecture (ASMA): Merging SMC Logic With Market Sentiment for Dynamic Strategy Switching
This topic explores how to build an Adaptive Smart Money Architecture (ASMA)—an intelligent Expert Advisor that merges Smart Money Concepts (Order Blocks, Break of Structure, Fair Value Gaps) with real-time market sentiment to automatically choose the best trading strategy depending on current market conditions.
Creating a "Snake" Game in MQL5
This article describes an example of "Snake" game programming. In MQL5, the game programming became possible primarily due to event handling features. The object-oriented programming greatly simplifies this process. In this article, you will learn the event processing features, the examples of use of the Standard MQL5 Library classes and details of periodic function calls.
Introduction to MQL5 (Part 9): Understanding and Using Objects in MQL5
Learn to create and customize chart objects in MQL5 using current and historical data. This project-based guide helps you visualize trades and apply MQL5 concepts practically, making it easier to build tools tailored to your trading needs.
Other classes in DoEasy library (Part 71): Chart object collection events
In this article, I will create the functionality for tracking some chart object events — adding/removing symbol charts and chart subwindows, as well as adding/removing/changing indicators in chart windows.
Forecasting with ARIMA models in MQL5
In this article we continue the development of the CArima class for building ARIMA models by adding intuitive methods that enable forecasting.
Developing a multi-currency Expert Advisor (Part 1): Collaboration of several trading strategies
There are quite a lot of different trading strategies. So, it might be useful to apply several strategies working in parallel to diversify risks and increase the stability of trading results. But if each strategy is implemented as a separate Expert Advisor (EA), then managing their work on one trading account becomes much more difficult. To solve this problem, it would be reasonable to implement the operation of different trading strategies within a single EA.
Calculating mathematical expressions (Part 2). Pratt and shunting yard parsers
In this article, we consider the principles of mathematical expression parsing and evaluation using parsers based on operator precedence. We will implement Pratt and shunting-yard parser, byte-code generation and calculations by this code, as well as view how to use indicators as functions in expressions and how to set up trading signals in Expert Advisors based on these indicators.
Automated grid trading using limit orders on Moscow Exchange (MOEX)
The article considers the development of an MQL5 Expert Advisor (EA) for MetaTrader 5 aimed at working on MOEX. The EA is to follow a grid strategy while trading on MOEX using MetaTrader 5 terminal. The EA involves closing positions by stop loss and take profit, as well as removing pending orders in case of certain market conditions.
Automating Trading Strategies in MQL5 (Part 15): Price Action Harmonic Cypher Pattern with Visualization
In this article, we explore the automation of the Cypher harmonic pattern in MQL5, detailing its detection and visualization on MetaTrader 5 charts. We implement an Expert Advisor that identifies swing points, validates Fibonacci-based patterns, and executes trades with clear graphical annotations. The article concludes with guidance on backtesting and optimizing the program for effective trading.
Developing a trading Expert Advisor from scratch (Part 16): Accessing data on the web (II)
Knowing how to input data from the Web into an Expert Advisor is not so obvious. It is not so easy to do without understanding all the possibilities offered by MetaTrader 5.
Developing a Trading Strategy: Using a Volume-Bound Approach
In the world of technical analysis, price often takes center stage. Traders meticulously map out support, resistance, and patterns, yet frequently ignore the critical force that drives these movements: volume. This article delves into a novel approach to volume analysis: the Volume Boundary indicator. This transformation, utilizing sophisticated smoothing functions like the butterfly and triple sine curves, allows for clearer interpretation and the development of systematic trading strategies.
Other classes in DoEasy library (Part 69): Chart object collection class
With this article, I start the development of the chart object collection class. The class will store the collection list of chart objects with their subwindows and indicators providing the ability to work with any selected charts and their subwindows or with a list of several charts at once.
Building a Smart Trade Manager in MQL5: Automate Break-Even, Trailing Stop, and Partial Close
Learn how to build a Smart Trade Manager Expert Advisor in MQL5 that automates trade management with break-even, trailing stop, and partial close features. A practical, step-by-step guide for traders who want to save time and improve consistency through automation.
Automating Trading Strategies in MQL5 (Part 30): Creating a Price Action AB-CD Harmonic Pattern with Visual Feedback
In this article, we develop an AB=CD Pattern EA in MQL5 that identifies bullish and bearish AB=CD harmonic patterns using pivot points and Fibonacci ratios, executing trades with precise entry, stop loss, and take-profit levels. We enhance trader insight with visual feedback through chart objects.
Introduction to MQL5 (Part 4): Mastering Structures, Classes, and Time Functions
Unlock the secrets of MQL5 programming in our latest article! Delve into the essentials of structures, classes, and time functions, empowering your coding journey. Whether you're a beginner or an experienced developer, our guide simplifies complex concepts, providing valuable insights for mastering MQL5. Elevate your programming skills and stay ahead in the world of algorithmic trading!
Optimizing Long-Term Trades: Engulfing Candles and Liquidity Strategies
This is a high-timeframe-based EA that makes long-term analyses, trading decisions, and executions based on higher-timeframe analyses of W1, D1, and MN. This article will explore in detail an EA that is specifically designed for long-term traders who are patient enough to withstand and hold their positions during tumultuous lower time frame price action without changing their bias frequently until take-profit targets are hit.
From Novice to Expert: Navigating Market Irregularities
Market rules are continuously evolving, and many once-reliable principles gradually lose their effectiveness. What worked in the past no longer works consistently over time. Today’s discussion focuses on probability ranges and how they can be used to navigate market irregularities. We will leverage MQL5 to develop an algorithm capable of trading effectively even in the choppiest market conditions. Join this discussion to find out more.
Price Movement: Mathematical Models and Technical Analysis
Forecasting the movements of currency pairs is an important factor in trading success. This article explores various price movement models, analyzes their advantages and disadvantages, and explores their practical application in trading strategies. We will consider approaches that allow us to identify hidden patterns and improve the accuracy of forecasts.
MQL5 Wizard techniques you should know (Part 03): Shannon's Entropy
Todays trader is a philomath who is almost always looking up new ideas, trying them out, choosing to modify them or discard them; an exploratory process that should cost a fair amount of diligence. These series of articles will proposition that the MQL5 wizard should be a mainstay for traders.
The Blue Monkey (BM) Algorithm
The article presents an implementation of the Blue Monkey metaheuristic algorithm, which is based on a model of the social behavior of blue monkeys. The article examines the key mechanisms of the algorithm — the group structure of the population, following local leaders, and generational renewal through the replacement of the worst adults with the best offspring — and analyzes the test results.
Building AI-Powered Trading Systems in MQL5 (Part 1): Implementing JSON Handling for AI APIs
In this article, we develop a JSON parsing framework in MQL5 to handle data exchange for AI API integration, focusing on a JSON class for processing JSON structures. We implement methods to serialize and deserialize JSON data, supporting various data types like strings, numbers, and objects, essential for communicating with AI services like ChatGPT, enabling future AI-driven trading systems by ensuring accurate data handling and manipulation.