Articles on trading system automation in MQL5

In this article, we implement an adaptive Linear Regression Channel system in MQL5 that automatically calculates the regression line and standard deviation channel over a user-defined period, only activates when the slope exceeds a minimum threshold to confirm a clear trend, and dynamically recreates or extends the channel when the price breaks out by a configurable percentage of channel width.

The article presents an improved brute force version, based on the goals set in the previous article. I will try to cover this topic as broadly as possible using Expert Advisors with settings obtained using this method. A new program version is attached to this article.

In this article, we develop a London Session Breakout System that identifies pre-London range breakouts and places pending orders with customizable trade types and risk settings. We incorporate features like trailing stops, risk-to-reward ratios, maximum drawdown limits, and a control panel for real-time monitoring and management.

An inverse fair value gap(IFVG) occurs when price returns to a previously identified fair value gap and, instead of showing the expected supportive or resistive reaction, fails to respect it. This failure can signal a potential shift in market direction and offer a contrarian trading edge. In this article, I'm going to introduce my self-developed approach to quantifying and utilizing inverse fair value gap as a strategy for MetaTrader 5 expert advisors.

In this article, we will consider pair trading, namely what its principles are and if there are any prospects for its practical application. We will also try to create a pair trading strategy.

The article discusses, in a detailed perspective, the steps that need to be implemented towards the creation of an expert advisor based on the Zone Recovery trading algorithm. This helps aotomate the system saving time for algotraders.

This article is the first installment in a two-part series designed to impart practical skills and best practices for writing custom indicators in MQL5. Using Heikin Ashi as a working example, the article explores the theory behind Heikin Ashi charts, explains how Heikin Ashi candlesticks are calculated, and demonstrates their application in technical analysis. The centerpiece is a step-by-step guide to developing a fully functional Heikin Ashi indicator from scratch, with clear explanations to help readers understand what to code and why. This foundational knowledge sets the stage for Part Two, where we will build an expert advisor that trades based on Heikin Ashi logic.

A new article in our series about learning how to design a trading system by the most popular technical indicators by MQL5 to be used in the MetaTrader 5. In this article, we will learn how to design a trading system by the Williams' %R indicator.

In this article, you will find your way to deal with the most important lines like trendlines, support, and resistance by MQL5.

Stop loss and take profit can have a significant impact on trading results. In this article, we will look at several ways to find optimal stop order values.

This article introduces a VWMA crossover signal tool for MetaTrader 5, designed to help traders identify potential bullish and bearish reversals by combining price action with trading volume. The EA generates clear buy and sell signals directly on the chart, features an informative panel, and allows for full user customization, making it a practical addition to your trading strategy.

In this article, we will search for market patterns, create Expert Advisors based on the identified patterns, and check how long these patterns remain valid, if they ever retain their validity.

In this article, we enhance the AI-powered trading system's modularity by separating UI components into a dedicated include file. The system now automates trade execution based on AI-generated signals, parsing JSON responses for BUY/SELL/NONE with entry/SL/TP, visualizing patterns like engulfing or divergences on charts with arrows, lines, and labels, and optional auto-signal checks on new bars.

In this article, I will use experimentation and non-standard approaches to develop a profitable trading system and check whether neural networks can be of any help for traders.

This is a new article to continue our series for beginners about how to design a trading system based on some of the popular indicators. We will learn a new indicator that is On Balance Volume (OBV), and we will learn how we can use it and design a trading system based on it.

In this article, we will develop a graphical order system of the "look what happens" type. Please note that we are not starting from scratch this time, but we will modify the existing system by adding more objects and events on the chart of the asset we are trading.

Smart Money Concept (Break Of Structure) coupled with the RSI Indicator to make informed automated trading decisions based on the market structure.

A new article from our series about how to create simple trading systems by the most popular technical indicators. We will learn about a new one which is the Accelerator Oscillator indicator and we will learn how to design a trading system using it.

The Multi-Currency Expert Advisor in this article is 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 1 symbol pair only from one symbol chart. This time we will use only 1 indicator, namely Parabolic SAR or iSAR in multi-timeframes starting from PERIOD_M15 to PERIOD_D1.

This article outlines the steps to create an Expert Advisor (EA) that capitalizes on price breakouts after consolidation periods. By identifying consolidation ranges and setting breakout levels, traders can automate their trading decisions based on this strategy. The Expert Advisor aims to provide clear entry and exit points while avoiding false breakouts

In this article, we develop an Expert Advisor in MQL5 for the Trend Flat Momentum Strategy. We combine a two moving averages crossover with RSI and CCI momentum filters to generate trade signals. We also cover backtesting and potential enhancements for real-world performance.

Successfully employing algorithmic trading requires continuous, interdisciplinary learning. However, the infinite range of possibilities can consume years of effort without yielding tangible results. To address this, we propose a framework that gradually introduces complexity, allowing traders to refine their strategies iteratively rather than committing indefinite time to uncertain outcomes.

In this article, we examine the Profitunity System by Bill Williams, breaking down its core components and unique approach to trading within market chaos. We guide readers through implementing the system in MQL5, focusing on automating key indicators and entry/exit signals. Finally, we test and optimize the strategy, providing insights into its performance across various market scenarios.

In this article, we automate the Midnight Range Breakout with Break of Structure strategy in MQL5, detailing code for breakout detection and trade execution. We define precise risk parameters for entries, stops, and profits. Backtesting and optimization are included for practical trading.