Learn how to design a trading system by Accumulation/Distribution (AD)
Welcome to the new article from our series about learning how to design trading systems based on the most popular technical indicators. In this article, we will learn about a new technical indicator called Accumulation/Distribution indicator and find out how to design an MQL5 trading system based on simple AD trading strategies.
Experiments with neural networks (Part 6): Perceptron as a self-sufficient tool for price forecast
The article provides an example of using a perceptron as a self-sufficient price prediction tool by showcasing general concepts and the simplest ready-made Expert Advisor followed by the results of its optimization.
Price Action Analysis Toolkit Development (Part 52): Master Market Structure with Multi-Timeframe Visual Analysis
This article presents the Multi‑Timeframe Visual Analyzer, an MQL5 Expert Advisor that reconstructs and overlays higher‑timeframe candles directly onto your active chart. It explains the implementation, key inputs, and practical outcomes, supported by an animated demo and chart examples showing instant toggling, multi‑timeframe confirmation, and configurable alerts. Read on to see how this tool can make chart analysis faster, clearer, and more efficient.
Other classes in DoEasy library (Part 70): Expanding functionality and auto updating the chart object collection
In this article, I will expand the functionality of chart objects and arrange navigation through charts, creation of screenshots, as well as saving and applying templates to charts. Also, I will implement auto update of the collection of chart objects, their windows and indicators within them.
MQL5 Cloud Network: Are You Still Calculating?
It will soon be a year and a half since the MQL5 Cloud Network has been launched. This leading edge event ushered in a new era of algorithmic trading - now with a couple of clicks, traders can have hundreds and thousands of computing cores at their disposal for the optimization of their trading strategies.
Graphics in DoEasy library (Part 80): "Geometric animation frame" object class
In this article, I will optimize the code of classes from the previous articles and create the geometric animation frame object class allowing us to draw regular polygons with a given number of vertices.
Automating Trading Strategies in MQL5 (Part 23): Zone Recovery with Trailing and Basket Logic
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.
How to Develop a Reliable and Safe Trade Robot in MQL 4
The article deals with the most common errors that occur in developing and using of an Expert Advisor. An exemplary safe automated trading system is described, as well.
Universal regression model for market price prediction (Part 2): Natural, technological and social transient functions
This article is a logical continuation of the previous one. It highlights the facts that confirm the conclusions made in the first article. These facts were revealed within ten years after its publication. They are centered around three detected dynamic transient functions describing the patterns in market price changes.
Developing a trading robot in Python (Part 3): Implementing a model-based trading algorithm
We continue the series of articles on developing a trading robot in Python and MQL5. In this article, we will create a trading algorithm in Python.
Population optimization algorithms: Particle swarm (PSO)
In this article, I will consider the popular Particle Swarm Optimization (PSO) algorithm. Previously, we discussed such important characteristics of optimization algorithms as convergence, convergence rate, stability, scalability, as well as developed a test stand and considered the simplest RNG algorithm.
Filtering Signals Based on Statistical Data of Price Correlation
Is there any correlation between the past price behavior and its future trends? Why does the price repeat today the character of its previous day movement? Can the statistics be used to forecast the price dynamics? There is an answer, and it is positive. If you have any doubt, then this article is for you. I'll tell how to create a working filter for a trading system in MQL5, revealing an interesting pattern in price changes.
Interview with Juan Pablo Alonso Escobar (ATC 2012)
"Everyone who is struggling with programming and who were not able to participate in this year's competition, know that it becomes a lot easier in time", said Juan Pablo Alonso Escobar (JPAlonso), the hero of today's interview.
Better Programmer (Part 04): How to become a faster developer
Every developer wants to be able to write code faster, and being able to code faster and effective is not some kind of special ability that only a few people are born with. It's a skill that can be learned by every coder, regardless of years of experience on the keyboard.
Integration of Broker APIs with Expert Advisors using MQL5 and Python
In this article, we will discuss the implementation of MQL5 in partnership with Python to perform broker-related operations. Imagine having a continuously running Expert Advisor (EA) hosted on a VPS, executing trades on your behalf. At some point, the ability of the EA to manage funds becomes paramount. This includes operations such as topping up your trading account and initiating withdrawals. In this discussion, we will shed light on the advantages and practical implementation of these features, ensuring seamless integration of fund management into your trading strategy. Stay tuned!
MQL5 Cookbook — Services
The article describes the versatile capabilities of services — MQL5 programs that do not require binding graphs. I will also highlight the differences of services from other MQL5 programs and emphasize the nuances of the developer's work with services. As examples, the reader is offered various tasks covering a wide range of functionality that can be implemented as a service.
MQL4 Language for Newbies. Difficult Questions in Simple Phrases.
This is the second article from the series "MQL4 Language for Newbies". Now we will examine more complex and advanced constructions of the language, learn new options and see, how they can be applied in everyday practice. You will get acquainted with a new cycle type 'while', new condition type 'switch', operators 'break' and 'continue'. Besides you will learn to write your own functions and work with multidimensional arrays. And for a dessert I have prepared an explanation about a preprocessor.
Creating an EA that works automatically (Part 03): New functions
Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. In the previous article, we started to develop an order system that we will use in our automated EA. However, we have created only one of the necessary functions.
Introduction to MQL5 (Part 26): Building an EA Using Support and Resistance Zones
This article teaches you how to build an MQL5 Expert Advisor that automatically detects support and resistance zones and executes trades based on them. You’ll learn how to program your EA to identify these key market levels, monitor price reactions, and make trading decisions without manual intervention.
MQL5 Wizard techniques you should know (Part 06): Fourier Transform
The Fourier transform introduced by Joseph Fourier is a means of deconstructing complex data wave points into simple constituent waves. This feature could be resourceful to traders and this article takes a look at that.
Library for easy and quick development of MetaTrader programs (part IX): Compatibility with MQL4 - Preparing data
In the previous articles, we started creating a large cross-platform library simplifying the development of programs for MetaTrader 5 and MetaTrader 4 platforms. In the eighth part, we implemented the class for tracking order and position modification events. Here, we will improve the library by making it fully compatible with MQL4.
Analytical Volume Profile Trading (AVPT): Liquidity Architecture, Market Memory, and Algorithmic Execution
Analytical Volume Profile Trading (AVPT) explores how liquidity architecture and market memory shape price behavior, enabling more profound insight into institutional positioning and volume-driven structure. By mapping POC, HVNs, LVNs, and Value Areas, traders can identify acceptance, rejection, and imbalance zones with precision.
Automating Trading Strategies in MQL5 (Part 20): Multi-Symbol Strategy Using CCI and AO
In this article, we create a multi-symbol trading strategy using CCI and AO indicators to detect trend reversals. We cover its design, MQL5 implementation, and backtesting process. The article concludes with tips for performance improvement.
Understanding functions in MQL5 with applications
Functions are critical things in any programming language, it helps developers apply the concept of (DRY) which means do not repeat yourself, and many other benefits. In this article, you will find much more information about functions and how we can create our own functions in MQL5 with simple applications that can be used or called in any system you have to enrich your trading system without complicating things.
Alan Andrews and his methods of time series analysis
Alan Andrews is one of the most famous "educators" of the modern world in the field of trading. His "pitchfork" is included in almost all modern quote analysis programs. But most traders do not use even a fraction of the opportunities that this tool provides. Besides, Andrews' original training course includes a description not only of the pitchfork (although it remains the main tool), but also of some other useful constructions. The article provides an insight into the marvelous chart analysis methods that Andrews taught in his original course. Beware, there will be a lot of images.
Drawing Horizontal Break-Through Levels Using Fractals
The article describes creation of an indicator that would display the support/resistance levels using up/down fractals.
MetaTrader 5 Machine Learning Blueprint (Part 2): Labeling Financial Data for Machine Learning
In this second installment of the MetaTrader 5 Machine Learning Blueprint series, you’ll discover why simple labels can lead your models astray—and how to apply advanced techniques like the Triple-Barrier and Trend-Scanning methods to define robust, risk-aware targets. Packed with practical Python examples that optimize these computationally intensive techniques, this hands-on guide shows you how to transform noisy market data into reliable labels that mirror real-world trading conditions.
Developing a Trading Strategy: The Triple Sine Mean Reversion Method
This article introduces the Triple Sine Mean Reversion Method, a trading strategy built upon a new mathematical indicator — the Triple Sine Oscillator (TSO). The TSO is derived from the sine cube function, which oscillates between –1 and +1, making it suitable for identifying overbought and oversold market conditions. Overall, the study demonstrates how mathematical functions can be transformed into practical trading tools.
Creating an MQL5 Expert Advisor Based on the PIRANHA Strategy by Utilizing Bollinger Bands
In this article, we create an Expert Advisor (EA) in MQL5 based on the PIRANHA strategy, utilizing Bollinger Bands to enhance trading effectiveness. We discuss the key principles of the strategy, the coding implementation, and methods for testing and optimization. This knowledge will enable you to deploy the EA in your trading scenarios effectively
Developing a Trading Strategy: The Triple Sine Mean Reversion Method
This article introduces the Triple Sine Mean Reversion Method, a trading strategy built upon a new mathematical indicator — the Triple Sine Oscillator (TSO). The TSO is derived from the sine cube function, which oscillates between –1 and +1, making it suitable for identifying overbought and oversold market conditions. Overall, the study demonstrates how mathematical functions can be transformed into practical trading tools.
Expert Advisors Based on Popular Trading Systems and Alchemy of Trading Robot Optimization (Part II)
In this article the author continues to analyze implementation algorithms of simplest trading systems and describes some relevant details of using optimization results. The article will be useful for beginning traders and EA writers.
Trade transactions. Request and response structures, description and logging
The article considers handling trade request structures, namely creating a request, its preliminary verification before sending it to the server, the server's response to a trade request and the structure of trade transactions. We will create simple and convenient functions for sending trading orders to the server and, based on everything discussed, create an EA informing of trade transactions.
From Novice to Expert: Support and Resistance Strength Indicator (SRSI)
In this article, we will share insights on how to leverage MQL5 programming to pinpoint market levels—differentiating between weaker and strongest price levels. We will fully develop a working, Support and Resistance Strength Indicator (SRSI).
What Is a Martingale?
A short description of various illusions that come up when people trade using martingale betting strategies or misuse spiking and the like approaches.
Building an Interactive Application to Display RSS Feeds in MetaTrader 5
In this article we look at the possibility of creating an application for the display of RSS feeds. The article will show how aspects of the Standard Library can be used to create interactive programs for MetaTrader 5.
Introduction to MQL5 (Part 17): Building Expert Advisors for Trend Reversals
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.
Price Action Analysis Toolkit Development (Part 47): Tracking Forex Sessions and Breakouts in MetaTrader 5
Global market sessions shape the rhythm of the trading day, and understanding their overlap is vital to timing entries and exits. In this article, we’ll build an interactive trading sessions EA that brings those global hours to life directly on your chart. The EA automatically plots color‑coded rectangles for the Asia, Tokyo, London, and New York sessions, updating in real time as each market opens or closes. It features on‑chart toggle buttons, a dynamic information panel, and a scrolling ticker headline that streams live status and breakout messages. Tested on different brokers, this EA combines precision with style—helping traders see volatility transitions, identify cross‑session breakouts, and stay visually connected to the global market’s pulse.
From Novice to Expert: Developing a Liquidity Strategy
Liquidity zones are commonly traded by waiting for the price to return and retest the zone of interest, often through the placement of pending orders within these areas. In this article, we leverage MQL5 to bring this concept to life, demonstrating how such zones can be identified programmatically and how risk management can be systematically applied. Join the discussion as we explore both the logic behind liquidity-based trading and its practical implementation.
Automating Trading Strategies with Parabolic SAR Trend Strategy in MQL5: Crafting an Effective Expert Advisor
In this article, we will automate the trading strategies with Parabolic SAR Strategy in MQL5: Crafting an Effective Expert Advisor. The EA will make trades based on trends identified by the Parabolic SAR indicator.
Neural networks made easy (Part 14): Data clustering
It has been more than a year since I published my last article. This is quite a lot time to revise ideas and to develop new approaches. In the new article, I would like to divert from the previously used supervised learning method. This time we will dip into unsupervised learning algorithms. In particular, we will consider one of the clustering algorithms—k-means.