Algorithmic Trading Articles — Guides & Examples

In Part 5 of our MQL5 AI trading system series, we enhance the ChatGPT-integrated Expert Advisor by introducing a collapsible sidebar, improving navigation with small and large history popups for seamless chat selection, while maintaining multiline input handling, persistent encrypted chat storage, and AI-driven trade signal generation from chart data.

From Novice to Expert: Time Filtered Trading

Just because ticks are constantly flowing in doesn’t mean every moment is an opportunity to trade. Today, we take an in-depth study into the art of timing—focusing on developing a time isolation algorithm to help traders identify and trade within their most favorable market windows. Cultivating this discipline allows retail traders to synchronize more closely with institutional timing, where precision and patience often define success. Join this discussion as we explore the science of timing and selective trading through the analytical capabilities of MQL5.

Markets Positioning Codex in MQL5 (Part 1): Bitwise Learning for Nvidia

We commence a new article series that builds upon our earlier efforts laid out in the MQL5 Wizard series, by taking them further as we step up our approach to systematic trading and strategy testing. Within these new series, we’ll concentrate our focus on Expert Advisors that are coded to hold only a single type of position - primarily longs. Focusing on just one market trend can simplify analysis, lessen strategy complexity and expose some key insights, especially when dealing in assets beyond forex. Our series, therefore, will investigate if this is effective in equities and other non-forex assets, where long only systems usually correlate well with smart money or institution strategies.

Integrating MQL5 with Data Processing Packages (Part 6): Merging Market Feedback with Model Adaptation

In this part, we focus on how to merge real-time market feedback—such as live trade outcomes, volatility changes, and liquidity shifts—with adaptive model learning to maintain a responsive and self-improving trading system.

Mastering Log Records (Part 10): Avoiding Log Replay by Implementing a Suppression

We created a log suppression system in the Logify library. It details how the CLogifySuppression class reduces console noise by applying configurable rules to avoid repetitive or irrelevant messages. We also cover the external configuration framework, validation mechanisms, and comprehensive testing to ensure robustness and flexibility in log capture during bot or indicator development.

Self Optimizing Expert Advisors in MQL5 (Part 17): Ensemble Intelligence

All algorithmic trading strategies are difficult to set up and maintain, regardless of complexity—a challenge shared by beginners and experts alike. This article introduces an ensemble framework where supervised models and human intuition work together to overcome their shared limitations. By aligning a moving average channel strategy with a Ridge Regression model on the same indicators, we achieve centralized control, faster self-correction, and profitability from otherwise unprofitable systems.

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.

Price Action Analysis Toolkit Development (Part 50): Developing the RVGI, CCI and SMA Confluence Engine in MQL5

Many traders struggle to identify genuine reversals. This article presents an EA that combines RVGI, CCI (±100), and an SMA trend filter to produce a single clear reversal signal. The EA includes an on-chart panel, configurable alerts, and the full source file for immediate download and testing.

Overcoming The Limitation of Machine Learning (Part 7): Automatic Strategy Selection

This article demonstrates how to automatically identify potentially profitable trading strategies using MetaTrader 5. White-box solutions, powered by unsupervised matrix factorization, are faster to configure, more interpretable, and provide clear guidance on which strategies to retain. Black-box solutions, while more time-consuming, are better suited for complex market conditions that white-box approaches may not capture. Join us as we discuss how our trading strategies can help us carefully identify profitable strategies under any circumstance.

Developing Trading Strategy: Pseudo Pearson Correlation Approach

Generating new indicators from existing ones offers a powerful way to enhance trading analysis. By defining a mathematical function that integrates the outputs of existing indicators, traders can create hybrid indicators that consolidate multiple signals into a single, efficient tool. This article introduces a new indicator built from three oscillators using a modified version of the Pearson correlation function, which we call the Pseudo Pearson Correlation (PPC). The PPC indicator aims to quantify the dynamic relationship between oscillators and apply it within a practical trading strategy.

Markets Positioning Codex in MQL5 (Part 2): Bitwise Learning, with Multi-Patterns for Nvidia

We continue our new series on Market-Positioning, where we study particular assets, with specific trade directions over manageable test windows. We started this by considering Nvidia Corp stock in the last article, where we covered 5 signal patterns from the complimentary pairing of the RSI and DeMarker oscillators. For this article, we cover the remaining 5 patterns and also delve into multi-pattern options that not only feature untethered combinations of all ten, but also specialized combinations of just a pair.

Neural Networks in Trading: Hierarchical Dual-Tower Transformer (Hidformer)

We invite you to get acquainted with the Hierarchical Double-Tower Transformer (Hidformer) framework, which was developed for time series forecasting and data analysis. The framework authors proposed several improvements to the Transformer architecture, which resulted in increased forecast accuracy and reduced computational resource consumption.

From Novice to Expert: Predictive Price Pathways

Fibonacci levels provide a practical framework that markets often respect, highlighting price zones where reactions are more likely. In this article, we build an expert advisor that applies Fibonacci retracement logic to anticipate likely future moves and trade retracements with pending orders. Explore the full workflow—from swing detection to level plotting, risk controls, and 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.

Building AI-Powered Trading Systems in MQL5 (Part 6): Introducing Chat Deletion and Search Functionality

In Part 6 of our MQL5 AI trading system series, we advance the ChatGPT-integrated Expert Advisor by introducing chat deletion functionality through interactive delete buttons in the sidebar, small/large history popups, and a new search popup, allowing traders to manage and organize persistent conversations efficiently while maintaining encrypted storage and AI-driven signals from chart data.

Automating Black-Scholes Greeks: Advanced Scalping and Microstructure Trading

Gamma and Delta were originally developed as risk-management tools for hedging options exposure, but over time they evolved into powerful instruments for advanced scalping, order-flow modeling, and microstructure trading. Today, they serve as real-time indicators of price sensitivity and liquidity behavior, enabling traders to anticipate short-term volatility with remarkable precision.

$Parafrac Oscillator: Combination of Parabolic and Fractal Indicator$

We will explore how the Parabolic SAR and the Fractal indicator can be combined to create a new oscillator-based indicator. By integrating the unique strengths of both tools, traders can aim at developing a more refined and effective trading strategy.

Introduction to MQL5 (Part 28): Mastering API and WebRequest Function in MQL5 (II)

This article teaches you how to retrieve and extract price data from external platforms using APIs and the WebRequest function in MQL5. You’ll learn how URLs are structured, how API responses are formatted, how to convert server data into readable strings, and how to identify and extract specific values from JSON responses.

Automating Trading Strategies in MQL5 (Part 41): Candle Range Theory (CRT) – Accumulation, Manipulation, Distribution (AMD)

In this article, we develop a Candle Range Theory (CRT) trading system in MQL5 that identifies accumulation ranges on a specified timeframe, detects breaches with manipulation depth filtering, and confirms reversals for entry trades in the distribution phase. The system supports dynamic or static stop-loss and take-profit calculations based on risk-reward ratios, optional trailing stops, and limits on positions per direction for controlled risk management.

Price Action Analysis Toolkit Development (Part 51): Revolutionary Chart Search Technology for Candlestick Pattern Discovery

This article is intended for algorithmic traders, quantitative analysts, and MQL5 developers interested in enhancing their understanding of candlestick pattern recognition through practical implementation. It provides an in‑depth exploration of the CandlePatternSearch.mq5 Expert Advisor—a complete framework for detecting, visualizing, and monitoring classical candlestick formations in MetaTrader 5. Beyond a line‑by‑line review of the code, the article discusses architectural design, pattern detection logic, GUI integration, and alert mechanisms, illustrating how traditional price‑action analysis can be automated efficiently.

Developing a Trading Strategy: The Flower Volatility Index Trend-Following Approach

The relentless quest to decode market rhythms has led traders and quantitative analysts to develop countless mathematical models. This article has introduced the Flower Volatility Index (FVI), a novel approach that transforms the mathematical elegance of Rose Curves into a functional trading tool. Through this work, we have shown how mathematical models can be adapted into practical trading mechanisms capable of supporting both analysis and decision-making in real market conditions.

Market Positioning Codex for VGT with Kendall's Tau and Distance Correlation

In this article, we look to explore how a complimentary indicator pairing can be used to analyze the recent 5-year history of Vanguard Information Technology Index Fund ETF. By considering two options of algorithms, Kendall’s Tau and Distance-Correlation, we look to select not just an ideal indicator pair for trading the VGT, but also suitable signal-pattern pairings of these two indicators.

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.

Mastering Kagi Charts in MQL5 (Part I): Creating the Indicator

Learn how to build a complete Kagi Chart engine in MQL5—constructing price reversals, generating dynamic line segments, and updating Kagi structures in real time. This first part teaches you how to render Kagi charts directly on MetaTrader 5, giving traders a clear view of trend shifts and market strength while preparing for automated Kagi-based trading logic in Part 2.

Implementing Practical Modules from Other Languages in MQL5 (Part 04): time, date, and datetime modules from Python

Unlike MQL5, Python programming language offers control and flexibility when it comes to dealing with and manipulating time. In this article, we will implement similar modules for better handling of dates and time in MQL5 as in Python.

Overcoming The Limitation of Machine Learning (Part 8): Nonparametric Strategy Selection

This article shows how to configure a black-box model to automatically uncover strong trading strategies using a data-driven approach. By using Mutual Information to prioritize the most learnable signals, we can build smarter and more adaptive models that outperform conventional methods. Readers will also learn to avoid common pitfalls like overreliance on surface-level metrics, and instead develop strategies rooted in meaningful statistical insight.

Developing a multi-currency Expert Advisor (Part 23): Putting in order the conveyor of automatic project optimization stages (II)

We aim to create a system for automatic periodic optimization of trading strategies used in one final EA. As the system evolves, it becomes increasingly complex, so it is necessary to look at it as a whole from time to time in order to identify bottlenecks and suboptimal solutions.

The MQL5 Standard Library Explorer (Part 4): Custom Signal Library

Today, we use the MQL5 Standard Library to build custom signal classes and let the MQL5 Wizard assemble a professional Expert Advisor for us. This approach simplifies development so that even beginner programmers can create robust EAs without in-depth coding knowledge, focusing instead on tuning inputs and optimizing performance. Join this discussion as we explore the process step by step.

Automating Trading Strategies in MQL5 (Part 42): Session-Based Opening Range Breakout (ORB) System

In this article, we create a fully customizable session-based Opening Range Breakout (ORB) system in MQL5 that lets us set any desired session start time and range duration, automatically calculates the high and low of that opening period, and trades only confirmed breakouts in the direction of the move.

Introduction to MQL5 (Part 29): Mastering API and WebRequest Function in MQL5 (III)

In this article, we continue mastering API and WebRequest in MQL5 by retrieving candlestick data from an external source. We focus on splitting the server response, cleaning the data, and extracting essential elements such as opening time and OHLC values for multiple daily candles, preparing the data for further analysis.

Price Action Analysis Toolkit Development (Part 53): Pattern Density Heatmap for Support and Resistance Zone Discovery

This article introduces the Pattern Density Heatmap, a price‑action mapping tool that transforms repeated candlestick pattern detections into statistically significant support and resistance zones. Rather than treating each signal in isolation, the EA aggregates detections into fixed price bins, scores their density with optional recency weighting, and confirms levels against higher‑timeframe data. The resulting heatmap reveals where the market has historically reacted—levels that can be used proactively for trade timing, risk management, and strategy confidence across any trading style.

The MQL5 Standard Library Explorer (Part 5): Multiple Signal Expert

In this session, we will build a sophisticated, multi-signal Expert Advisor using the MQL5 Standard Library. This approach allows us to seamlessly blend built-in signals with our own custom logic, demonstrating how to construct a powerful and flexible trading algorithm. For more, click to read further.

Automating Trading Strategies in MQL5 (Part 43): Adaptive Linear Regression Channel Strategy

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.

Overcoming The Limitation of Machine Learning (Part 3): A Fresh Perspective on Irreducible Error

This article takes a fresh perspective on a hidden, geometric source of error that quietly shapes every prediction your models make. By rethinking how we measure and apply machine learning forecasts in trading, we reveal how this overlooked perspective can unlock sharper decisions, stronger returns, and a more intelligent way to work with models we thought we already understood.

Building a Professional Trading System with Heikin Ashi (Part 1): Developing a custom indicator

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.

Automating Trading Strategies in MQL5 (Part 44): Change of Character (CHoCH) Detection with Swing High/Low Breaks

In this article, we develop a Change of Character (CHoCH) detection system in MQL5 that identifies swing highs and lows over a user-defined bar length, labels them as HH/LH for highs or LL/HL for lows to determine trend direction, and triggers trades on breaks of these swing points, indicating a potential reversal, and trades the breaks when the structure changes.

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.

Introduction to MQL5 (Part 30): Mastering API and WebRequest Function in MQL5 (IV)

Discover a step-by-step tutorial that simplifies the extraction, conversion, and organization of candle data from API responses within the MQL5 environment. This guide is perfect for newcomers looking to enhance their coding skills and develop robust strategies for managing market data efficiently.

Implementing Practical Modules from Other Languages in MQL5 (Part 05): The Logging module from Python, Log Like a Pro

Integrating Python's logging module with MQL5 empowers traders with a systematic logging approach, simplifying the process of monitoring, debugging, and documenting trading activities. This article explains the adaptation process, offering traders a powerful tool for maintaining clarity and organization in trading software development.

Statistical Arbitrage Through Cointegrated Stocks (Part 8): Rolling Windows Eigenvector Comparison for Portfolio Rebalancing

This article proposes using Rolling Windows Eigenvector Comparison for early imbalance diagnostics and portfolio rebalancing in a mean-reversion statistical arbitrage strategy based on cointegrated stocks. It contrasts this technique with traditional In-Sample/Out-of-Sample ADF validation, showing that eigenvector shifts can signal the need for rebalancing even when IS/OOS ADF still indicates a stationary spread. While the method is intended mainly for live trading monitoring, the article concludes that eigenvector comparison could also be integrated into the scoring system—though its actual contribution to performance remains to be tested.