Articles with examples of indicators developed in MQL5

This project aims to leverage the MQL5 algorithm to develop a comprehensive set of analysis tools for MetaTrader 5. These tools—ranging from scripts and indicators to AI models and expert advisors—will automate the market analysis process. At times, this development will yield tools capable of performing advanced analyses with no human involvement and forecasting outcomes to appropriate platforms. No opportunity will ever be missed. Join me as we explore the process of building a robust market analysis custom tools' chest. We will begin by developing a simple MQL5 program that I have named, Chart Projector.

Price action is a fundamental approach for identifying profitable trading setups. However, manually monitoring price movements and patterns can be challenging and time-consuming. To address this, we are developing tools that analyze price action automatically, providing timely signals whenever potential opportunities are detected. This article introduces a robust tool that leverages fractal breakouts alongside EMA 14 and EMA 200 to generate reliable trading signals, helping traders make informed decisions with greater confidence.

While some concepts may seem straightforward at first glance, bringing them to life in practice can be quite challenging. In the article below, we'll take you on a journey through our innovative approach to automating an Expert Advisor (EA) that skillfully analyzes the market using a mean reversion strategy. Join us as we unravel the intricacies of this exciting automation process.

Moving from a simple trading script to a fully functioning Expert Advisor (EA) can significantly enhance your trading experience. Imagine having a system that automatically monitors your charts, performs essential calculations in the background, and provides regular updates every two hours. This EA would be equipped to analyze key metrics that are crucial for making informed trading decisions, ensuring that you have access to the most current information to adjust your strategies effectively.

In Part 38, we build a production-grade MT5 monitoring panel that converts raw ticks into actionable signals. The EA buffers tick data to compute tick-level VWAP, a short-window imbalance (flow) metric, and ATR-based position sizing. It then visualizes spread, ATR, and flow with low-flicker bars. The system calculates a suggested lot size and a 1R stop, and issues configurable alerts for tight spreads, strong flow, and edge conditions. Auto-trading is intentionally disabled; the focus remains on robust signal generation and a clean user experience.

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.

Aligned with our goal of developing practical price-action tools, this article explores the creation of an EA that detects pin bar and engulfing patterns, using RSI divergence as a confirmation trigger before generating any trading signals.

The article offers a new perspective on indicator interfaces. I am going to focus on convenience. Having tried dozens of different trading strategies over the years, as well as having tested hundreds of different indicators, I have come to some conclusions I want to share with you in this article.

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).

Learn how to build a Supertrend-driven Expert Advisor in MQL5 from the ground up. The article covers embedding the indicator as a resource, reading buffer values on closed bars, detecting confirmed flips, aligning and switching positions, and configuring stop-loss modes and position sizing. It concludes with Strategy Tester setup and reproducible tests, leaving you with a configurable EA and a clear framework for further research and extensions.

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.

Build a non‑repainting Supertrend in MQL5 for MetaTrader 5 from first principles. We use an iATR handle and CopyBuffer for volatility, bind buffers with SetIndexBuffer, and configure plots (DRAWCOLORCANDLES plus two line bands) via PlotIndexSetInteger. The logic updates only on closed bars with EMPTY_VALUE to suppress inactive bands, exposing atrPeriod and atrMultiplier inputs. You get a clean, EA‑ready overlay with documented buffers for strategies and signals.

In this reference article, we will look at standard indicators from the Trend Indicators category. We will create ready-to-use templates for indicator use in EAs - declaring and setting parameters, indicator initialization and deinitialization, as well as receiving data and signals from indicator buffers in EAs.

Using simple examples, we will examine the principles of calculating moving averages, as well as learn about the ways to optimize indicator calculations, including moving averages.

Higher-timeframe CRT ranges are informative, yet traders often execute on lower timeframes without that context. We implement an MQL5 indicator that reads higher-timeframe OHLC, projects the full candle range, body, and wicks onto the active lower-timeframe chart, and marks entries, stops, and targets. This improves situational awareness and removes the need to switch windows.

The article takes a quick look at the ALGLIB 3.19 numerical analysis library, its applications and new algorithms that can improve the efficiency of financial data analysis.

This is a continuation of the series for beginners. In this article, we'll look at how to create constants and variables, write dates, colors, and other useful data. We will learn how to create enumerations like days of the week or line styles (solid, dotted, etc.). Variables and expressions are the basis of programming. They are definitely present in 99% of programs, so understanding them is critical. Therefore, if you are new to programming, this article can be very useful for you. Required programming knowledge level: very basic, within the limits of my previous article (see the link at the beginning).

In this article I'll introduce a method for creating custom indicators whose drawings are made using the class CCanvas from standard library and see charts properties for coordinates conversion. I'll approach specially indicators which need to fill the area between two lines using transparency.

In this article, we take the first step in MQL5 programming, even for complete beginners. We'll show you how to transform familiar candlestick patterns into a fully functional custom indicator. Candlestick patterns are valuable as they reflect real price action and signal market shifts. Instead of manually scanning charts—an approach prone to errors and inefficiencies—we'll discuss how to automate the process with an indicator that identifies and labels patterns for you. Along the way, we’ll explore key concepts like indexing, time series, Average True Range (for accuracy in varying market volatility), and the development of a custom reusable Candlestick Pattern library for use in future projects.

We will create an indicator based on the Gann's Square of 9, built by squaring time and price. We will prepare the code and test the indicator in the platform on different time intervals.

This article presents the design and MetaTrader 5 implementation of the Candle Pressure Index (CPI)—a CLV-based overlay that visualizes intra-Bar buying and selling pressure directly on price charts. The discussion focuses on candle structure, pressure classification, visualization mechanics, and a non-repainting, transition-based alert system designed for consistent behavior across timeframes and instruments.

The extent of liquidity zones and the magnitude of the breakout range are key variables that substantially affect the probability of a retest occurring. In this discussion, we outline the complete process for developing an indicator that incorporates these ratios.