Articles on manual and algorithmic trading in MetaTrader 5
This category features articles on all aspects of trading - from manual to fully automatic trading, from Expert Advisor ideas to trading robot creation using the MQL5 Wizard. Position management, processing of trade events and money management - these integral parts of trading are covered in theses articles.
Learn how to copy trading signals and how to provide around-the-clock operation of Expert Advisors, how to create a trading robot and how to run MetaTrader on Linux and MacOS, what social trading is and how to order a trading robot.
Add a new article
You are missing trading opportunities:
- Free trading apps
- Over 8,000 signals for copying
- Economic news for exploring financial markets
Registration
Log in
You agree to website policy and terms of use
If you do not have an account, please register
Creating an EA that works automatically (Part 12): Automation (IV)
If you think automated systems are simple, then you probably don't fully understand what it takes to create them. In this article, we will talk about the problem that kills a lot of Expert Advisors. The indiscriminate triggering of orders is a possible solution to this problem.
MQL5 Trading Tools (Part 3): Building a Multi-Timeframe Scanner Dashboard for Strategic Trading
In this article, we build a multi-timeframe scanner dashboard in MQL5 to display real-time trading signals. We plan an interactive grid interface, implement signal calculations with multiple indicators, and add a close button. The article concludes with backtesting and strategic trading benefits
Developing a trading Expert Advisor from scratch (Part 31): Towards the future (IV)
We continue to remove separate parts from our EA. This is the last article within this series. And the last thing to be removed is the sound system. This can be a bit confusing if you haven't followed these article series.
Creating an EA that works automatically (Part 06): Account types (I)
Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. Our EA in its current state can work in any situation but it is not yet ready for automation. We still have to work on a few points.
Automating Trading Strategies in MQL5 (Part 22): Creating a Zone Recovery System for Envelopes Trend Trading
In this article, we develop a Zone Recovery System integrated with an Envelopes trend-trading strategy in MQL5. We outline the architecture for using RSI and Envelopes indicators to trigger trades and manage recovery zones to mitigate losses. Through implementation and backtesting, we show how to build an effective automated trading system for dynamic markets
Learn how to design a trading system by Force Index
Welcome to a new article in our series about how to design a trading system by the most popular technical indicators. In this article, we will learn about a new technical indicator and how to create a trading system using the Force Index indicator.
Formulating Dynamic Multi-Pair EA (Part 5): Scalping vs Swing Trading Approaches
This part explores how to design a Dynamic Multi-Pair Expert Advisor capable of adapting between Scalping and Swing Trading modes. It covers the structural and algorithmic differences in signal generation, trade execution, and risk management, allowing the EA to intelligently switch strategies based on market behavior and user input.
Data Science and Machine Learning (Part 04): Predicting Current Stock Market Crash
In this article I am going to attempt to use our logistic model to predict the stock market crash based upon the fundamentals of the US economy, the NETFLIX and APPLE are the stocks we are going to focus on, Using the previous market crashes of 2019 and 2020 let's see how our model will perform in the current dooms and glooms.
Trading with the MQL5 Economic Calendar (Part 1): Mastering the Functions of the MQL5 Economic Calendar
In this article, we explore how to use the MQL5 Economic Calendar for trading by first understanding its core functionalities. We then implement key functions of the Economic Calendar in MQL5 to extract relevant news data for trading decisions. Finally, we conclude by showcasing how to utilize this information to enhance trading strategies effectively.
Learn how to design a trading system by DeMarker
Here is a new article in our series about how to design a trading system by the most popular technical indicators. In this article, we will present how to create a trading system by the DeMarker indicator.
Building A Candlestick Trend Constraint Model(Part 2): Merging Native Indicators
This article focuses on taking advantage of in-built meta trader 5 indicators to screen out off-trend signals. Advancing from the previous article we will explore how to do it using MQL5 code to communicate our idea to the final program.
Automating Trading Strategies in MQL5 (Part 19): Envelopes Trend Bounce Scalping — Trade Execution and Risk Management (Part II)
In this article, we implement trade execution and risk management for the Envelopes Trend Bounce Scalping Strategy in MQL5. We implement order placement and risk controls like stop-loss and position sizing. We conclude with backtesting and optimization, building on Part 18’s foundation.
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.
Mastering Fair Value Gaps: Formation, Logic, and Automated Trading with Breakers and Market Structure Shifts
This is an article that I have written aimed to expound and explain Fair Value Gaps, their formation logic for occurring, and automated trading with breakers and market structure shifts.
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.
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.
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.
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.
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.
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.
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.
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.
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).
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.
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.
Learn how to design a trading system by Chaikin Oscillator
Welcome to our new article from our series about learning how to design a trading system by the most popular technical indicator. Through this new article, we will learn how to design a trading system by the Chaikin Oscillator indicator.
Gradient boosting in transductive and active machine learning
In this article, we will consider active machine learning methods utilizing real data, as well discuss their pros and cons. Perhaps you will find these methods useful and will include them in your arsenal of machine learning models. Transduction was introduced by Vladimir Vapnik, who is the co-inventor of the Support-Vector Machine (SVM).
Automating Trading Strategies in MQL5 (Part 26): Building a Pin Bar Averaging System for Multi-Position Trading
In this article, we develop a Pin Bar Averaging system in MQL5 that detects pin bar patterns to initiate trades and employs an averaging strategy for multi-position management, enhanced by trailing stops and breakeven adjustments. We incorporate customizable parameters with a dashboard for real-time monitoring of positions and profits.
Tips for Purchasing a Product on the Market. Step-By-Step Guide
This step-by-step guide provides tips and tricks for better understanding and searching for a required product. The article makes an attempt to puzzle out different methods of searching for an appropriate product, sorting out unwanted products, determining product efficiency and essentiality for you.
Creating a Daily Drawdown Limiter EA in MQL5
The article discusses, from a detailed perspective, how to implement the creation of an Expert Advisor (EA) based on the trading algorithm. This helps to automate the system in the MQL5 and take control of the Daily Drawdown.
Creating an EA that works automatically (Part 15): Automation (VII)
To complete this series of articles on automation, we will continue discussing the topic of the previous article. We will see how everything will fit together, making the EA run like clockwork.
Integrating AI model into already existing MQL5 trading strategy
This topic focuses on incorporating a trained AI model (such as a reinforcement learning model like LSTM or a machine learning-based predictive model) into an existing MQL5 trading strategy.
Rebuy algorithm: Math model for increasing efficiency
In this article, we will use the rebuy algorithm for a deeper understanding of the efficiency of trading systems and start working on the general principles of improving trading efficiency using mathematics and logic, as well as apply the most non-standard methods of increasing efficiency in terms of using absolutely any trading system.
Creating a mean-reversion strategy based on machine learning
This article proposes another original approach to creating trading systems based on machine learning, using clustering and trade labeling for mean reversion strategies.
How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 5): Bollinger Bands On Keltner Channel — Indicators Signal
The Multi-Currency Expert Advisor in this article is an Expert Advisor or Trading Robot that can trade (open orders, close orders and manage orders for example: Trailing Stop Loss and Trailing Profit) for more than one symbol pair from only one symbol chart. In this article we will use signals from two indicators, in this case Bollinger Bands® on Keltner Channel.
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 18): Envelopes Trend Bounce Scalping - Core Infrastructure and Signal Generation (Part I)
In this article, we build the core infrastructure for the Envelopes Trend Bounce Scalping Expert Advisor in MQL5. We initialize envelopes and other indicators for signal generation. We set up backtesting to prepare for trade execution in the next part.
Using cryptography with external applications
In this article, we consider encryption/decryption of objects in MetaTrader and in external applications. Our purpose is to determine the conditions under which the same results will be obtained with the same initial data.