Algorithmic Trading Articles for Experts

Risk Management (Part 5): Integrating the Risk Management System into an Expert Advisor

In this article, we will implement the risk management system developed in previous publications and add the Order Blocks indicator described in other articles. In addition, we will run a backtest so we can compare results with the risk management system enabled and evaluate the impact of dynamic risk.

In this article we are implementing ARIMA forecasting indicator in MQL5. It examines how the ARIMA model generates forecasts, its applicability to the Forex market and the stock market in general. It also explains what AR autoregression is, how autoregressive models are used for forecasting, and how the autoregression mechanism works.

Larry Williams Market Secrets (Part 8): Combining Volatility, Structure and Time Filters

An in-depth walkthrough of building a Larry Williams inspired volatility breakout Expert Advisor in MQL5, combining swing structure, volatility-based entries, trade day of the week filtering, time filters, and flexible risk management, with a complete implementation and reproducible test setup.

Neural Networks in Trading: Two-Dimensional Connection Space Models (Final Part)

We continue to explore the innovative Chimera framework – a two-dimensional state-space model that uses neural network technologies to analyze multidimensional time series. This method provides high forecasting accuracy with low computational cost.

Neural Networks in Trading: Multi-Task Learning Based on the ResNeXt Model (Final Part)

We continue exploring a multi-task learning framework based on ResNeXt, which is characterized by modularity, high computational efficiency, and the ability to identify stable patterns in data. Using a single encoder and specialized "heads" reduces the risk of model overfitting and improves the quality of forecasts.

Neural Networks in Trading: Multi-Task Learning Based on the ResNeXt Model

A multi-task learning framework based on ResNeXt optimizes the analysis of financial data, taking into account its high dimensionality, nonlinearity, and time dependencies. The use of group convolution and specialized heads allows the model to effectively extract key features from the input data.

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

We continue to build the Hidformer hierarchical dual-tower transformer model designed for analyzing and forecasting complex multivariate time series. In this article, we will bring the work we started earlier to its logical conclusion — we will test the model on real historical data.

How can century-old functions update your trading strategies?

This article considers the Rademacher and Walsh functions. We will explore ways to apply these functions to financial time series analysis and also consider various applications for them in trading.

Introduction to MQL5 (Part 23): Automating Opening Range Breakout Strategy

This article explores how to build an Opening Range Breakout (ORB) Expert Advisor in MQL5. It explains how the EA identifies breakouts from the market’s initial range and opens trades accordingly. You’ll also learn how to control the number of positions opened and set a specific cutoff time to stop trading automatically.

Reusing Invalidated Orderblocks As Mitigation Blocks (SMC)

In this article, we explore how previously invalidated orderblocks can be reused as mitigation blocks within Smart Money Concepts (SMC). These zones reveal where institutional traders re-enter the market after a failed orderblock, providing high-probability areas for trade continuation in the dominant trend.

Building AI-Powered Trading Systems in MQL5 (Part 4): Overcoming Multiline Input, Ensuring Chat Persistence, and Generating Signals

In this article, we enhance the ChatGPT-integrated program in MQL5 overcoming multiline input limitations with improved text rendering, introducing a sidebar for navigating persistent chat storage using AES256 encryption and ZIP compression, and generating initial trade signals through chart data integration.

Neural Networks in Trading: Models Using Wavelet Transform and Multi-Task Attention (Final Part)

In the previous article, we explored the theoretical foundations and began implementing the approaches of the Multitask-Stockformer framework, which combines the wavelet transform and the Self-Attention multitask model. We continue to implement the algorithms of this framework and evaluate their effectiveness on real historical data.

Neural Networks in Trading: Models Using Wavelet Transform and Multi-Task Attention

We invite you to explore a framework that combines wavelet transforms and a multi-task self-attention model, aimed at improving the responsiveness and accuracy of forecasting in volatile market conditions. The wavelet transform allows asset returns to be decomposed into high and low frequencies, carefully capturing long-term market trends and short-term fluctuations.

Post-Factum trading analysis: Selecting trailing stops and new stop levels in the strategy tester

We continue the topic of analyzing completed deals in the strategy tester to improve the quality of trading. Let's see how using different trailing stops can change our existing trading results.

Using JSON Data API in your MQL projects

Imagine that you can use data that is not found in MetaTrader, you only get data from indicators by price analysis and technical analysis. Now imagine that you can access data that will take your trading power steps higher. You can multiply the power of the MetaTrader software if you mix the output of other software, macro analysis methods, and ultra-advanced tools through the API data. In this article, we will teach you how to use APIs and introduce useful and valuable API data services.

Neural Networks in Trading: A Hybrid Trading Framework with Predictive Coding (Final Part)

We continue our examination of the StockFormer hybrid trading system, which combines predictive coding and reinforcement learning algorithms for financial time series analysis. The system is based on three Transformer branches with a Diversified Multi-Head Attention (DMH-Attn) mechanism that enables the capturing of complex patterns and interdependencies between assets. Previously, we got acquainted with the theoretical aspects of the framework and implemented the DMH-Attn mechanisms. Today, we will talk about the model architecture and training.

Automating Trading Strategies in MQL5 (Part 36): Supply and Demand Trading with Retest and Impulse Model

In this article, we create a supply and demand trading system in MQL5 that identifies supply and demand zones through consolidation ranges, validates them with impulsive moves, and trades retests with trend confirmation and customizable risk parameters. The system visualizes zones with dynamic labels and colors, supporting trailing stops for risk management.

Building AI-Powered Trading Systems in MQL5 (Part 3): Upgrading to a Scrollable Single Chat-Oriented UI

In this article, we upgrade the ChatGPT-integrated program in MQL5 to a scrollable single chat-oriented UI, enhancing conversation history display with timestamps and dynamic scrolling. The system builds on JSON parsing to manage multi-turn messages, supporting customizable scrollbar modes and hover effects for improved user interaction.

Building a Professional Trading System with Heikin Ashi (Part 2): Developing an EA

This article explains how to develop a professional Heikin Ashi-based Expert Advisor (EA) in MQL5. You will learn how to set up input parameters, enumerations, indicators, global variables, and implement the core trading logic. You will also be able to run a backtest on gold to validate your work.

Visual assessment and adjustment of trading in MetaTrader 5

The strategy tester allows you to do more than just optimize your trading robot's parameters. I will show how to evaluate your account's trading history post-factum and make adjustments to your trading in the tester by changing the stop-losses of your open positions.

Reimagining Classic Strategies (Part 16): Double Bollinger Band Breakouts

This article walks the reader through a reimagined version of the classical Bollinger Band breakout strategy. It identifies key weaknesses in the original approach, such as its well-known susceptibility to false breakouts. The article aims to introduce a possible solution: the Double Bollinger Band trading strategy. This relatively lesser known approach supplements the weaknesses of the classical version and offers a more dynamic perspective on financial markets. It helps us overcome the old limitations defined by the original rules, providing traders with a stronger and more adaptive framework.

Automating Trading Strategies in MQL5 (Part 35): Creating a Breaker Block Trading System

In this article, we create a Breaker Block Trading System in MQL5 that identifies consolidation ranges, detects breakouts, and validates breaker blocks with swing points to trade retests with defined risk parameters. The system visualizes order and breaker blocks with dynamic labels and arrows, supporting automated trading and trailing stops.

From Novice to Expert: Animated News Headline Using MQL5 (III) — Indicator Insights

In this article, we’ll advance the News Headline EA by introducing a dedicated indicator insights lane—a compact, on-chart display of key technical signals generated from popular indicators such as RSI, MACD, Stochastic, and CCI. This approach eliminates the need for multiple indicator subwindows on the MetaTrader 5 terminal, keeping your workspace clean and efficient. By leveraging the MQL5 API to access indicator data in the background, we can process and visualize market insights in real-time using custom logic. Join us as we explore how to manipulate indicator data in MQL5 to create an intelligent and space-saving scrolling insights system, all within a single horizontal lane on your trading chart.

MQL5 Trading Tools (Part 9): Developing a First Run User Setup Wizard for Expert Advisors with Scrollable Guide

In this article, we develop an MQL5 First Run User Setup Wizard for Expert Advisors, featuring a scrollable guide with an interactive dashboard, dynamic text formatting, and visual controls like buttons and a checkbox allowing users to navigate instructions and configure trading parameters efficiently. Users of the program get to have insight of what the program is all about and what to do on the first run, more like an orientation model.

From Novice to Expert: Animated News Headline Using MQL5 (II)

Today, we take another step forward by integrating an external news API as the source of headlines for our News Headline EA. In this phase, we’ll explore various news sources—both established and emerging—and learn how to access their APIs effectively. We'll also cover methods for parsing the retrieved data into a format optimized for display within our Expert Advisor. Join the discussion as we explore the benefits of accessing news headlines and the economic calendar directly on the chart, all within a compact, non-intrusive interface.

Automating Trading Strategies in MQL5 (Part 34): Trendline Breakout System with R-Squared Goodness of Fit

In this article, we develop a Trendline Breakout System in MQL5 that identifies support and resistance trendlines using swing points, validated by R-squared goodness of fit and angle constraints, to automate breakout trades. Our plan is to detect swing highs and lows within a specified lookback period, construct trendlines with a minimum number of touch points, and validate them using R-squared metrics and angle constraints to ensure reliability.

Automating Trading Strategies in MQL5 (Part 33): Creating a Price Action Shark Harmonic Pattern System

In this article, we develop a Shark pattern system in MQL5 that identifies bullish and bearish Shark harmonic patterns using pivot points and Fibonacci ratios, executing trades with customizable entry, stop-loss, and take-profit levels based on user-selected options. We enhance trader insight with visual feedback through chart objects like triangles, trendlines, and labels to clearly display the X-A-B-C-D pattern structure

The MQL5 Standard Library Explorer (Part 1): Introduction with CTrade, CiMA, and CiATR

The MQL5 Standard Library plays a vital role in developing trading algorithms for MetaTrader 5. In this discussion series, our goal is to master its application to simplify the creation of efficient trading tools for MetaTrader 5. These tools include custom Expert Advisors, indicators, and other utilities. We begin today by developing a trend-following Expert Advisor using the CTrade, CiMA, and CiATR classes. This is an especially important topic for everyone—whether you are a beginner or an experienced developer. Join this discussion to discover more.

Creating a Trading Administrator Panel in MQL5 (Part XII): Integration of a Forex Values Calculator

Accurate calculation of key trading values is an indispensable part of every trader’s workflow. In this article, we will discuss, the integration of a powerful utility—the Forex Calculator—into the Trade Management Panel, further extending the functionality of our multi-panel Trading Administrator system. Efficiently determining risk, position size, and potential profit is essential when placing trades, and this new feature is designed to make that process faster and more intuitive within the panel. Join us as we explore the practical application of MQL5 in building advanced, trading panels.

Automating Trading Strategies in MQL5 (Part 2): The Kumo Breakout System with Ichimoku and Awesome Oscillator

In this article, we create an Expert Advisor (EA) that automates the Kumo Breakout strategy using the Ichimoku Kinko Hyo indicator and the Awesome Oscillator. We walk through the process of initializing indicator handles, detecting breakout conditions, and coding automated trade entries and exits. Additionally, we implement trailing stops and position management logic to enhance the EA's performance and adaptability to market conditions.

Automating The Market Sentiment Indicator

In this article, we automate a custom market sentiment indicator that classifies market conditions into bullish, bearish, risk-on, risk-off, and neutral. The Expert Advisor delivers real-time insights into prevailing sentiment while streamlining the analysis process for current market trends or direction.

Building AI-Powered Trading Systems in MQL5 (Part 2): Developing a ChatGPT-Integrated Program with User Interface

In this article, we develop a ChatGPT-integrated program in MQL5 with a user interface, leveraging the JSON parsing framework from Part 1 to send prompts to OpenAI’s API and display responses on a MetaTrader 5 chart. We implement a dashboard with an input field, submit button, and response display, handling API communication and text wrapping for user interaction.

Price Action Analysis Toolkit Development (Part 41): Building a Statistical Price-Level EA in MQL5

Statistics has always been at the heart of financial analysis. By definition, statistics is the discipline that collects, analyzes, interprets, and presents data in meaningful ways. Now imagine applying that same framework to candlesticks—compressing raw price action into measurable insights. How helpful would it be to know, for a specific period of time, the central tendency, spread, and distribution of market behavior? In this article, we introduce exactly that approach, showing how statistical methods can transform candlestick data into clear, actionable signals.

Developing a Volatility Based Breakout System

Volatility based breakout system identifies market ranges, then trades when price breaks above or below those levels, filtered by volatility measures such as ATR. This approach helps capture strong directional moves.

From Novice to Expert: Animated News Headline Using MQL5 (XI)—Correlation in News Trading

In this discussion, we will explore how the concept of Financial Correlation can be applied to improve decision-making efficiency when trading multiple symbols during major economic events announcement. The focus is on addressing the challenge of heightened risk exposure caused by increased volatility during news releases.

Building AI-Powered Trading Systems in MQL5 (Part 1): Implementing JSON Handling for AI APIs

In this article, we develop a JSON parsing framework in MQL5 to handle data exchange for AI API integration, focusing on a JSON class for processing JSON structures. We implement methods to serialize and deserialize JSON data, supporting various data types like strings, numbers, and objects, essential for communicating with AI services like ChatGPT, enabling future AI-driven trading systems by ensuring accurate data handling and manipulation.

Introduction to MQL5 (Part 21): Automating Harmonic Pattern Detection

Learn how to detect and display the Gartley harmonic pattern in MetaTrader 5 using MQL5. This article explains each step of the process, from identifying swing points to applying Fibonacci ratios and plotting the full pattern on the chart for clear visual confirmation.

Neural Networks in Trading: An Ensemble of Agents with Attention Mechanisms (Final Part)

In the previous article, we introduced the multi-agent adaptive framework MASAAT, which uses an ensemble of agents to perform cross-analysis of multimodal time series at different data scales. Today we will continue implementing the approaches of this framework in MQL5 and bring this work to a logical conclusion.

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

Automating Trading Strategies in MQL5 (Part 32): Creating a Price Action 5 Drives Harmonic Pattern System

In this article, we develop a 5 Drives pattern system in MQL5 that identifies bullish and bearish 5 Drives harmonic patterns using pivot points and Fibonacci ratios, executing trades with customizable entry, stop loss, and take-profit levels based on user-selected options. We enhance trader insight with visual feedback through chart objects like triangles, trendlines, and labels to clearly display the A-B-C-D-E-F pattern structure.