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Creating Custom Indicators in MQL5 (Part 4): Smart WaveTrend Crossover with Dual Oscillators
Creating Custom Indicators in MQL5 (Part 4): Smart WaveTrend Crossover with Dual Oscillators
In this article, we develop a custom indicator in MQL5 called Smart WaveTrend Crossover, utilizing dual WaveTrend oscillators—one for generating crossover signals and another for trend filtering—with customizable parameters for channel, average, and moving average lengths. The indicator plots colored candles based on the trend direction, displays buy and sell arrow signals on crossovers, and includes options to enable trend confirmation and adjust visual elements like colors and offsets.
Optimizing Trend Strength: Trading in Trend Direction and Strength
Optimizing Trend Strength: Trading in Trend Direction and Strength
This is a specialized trend-following EA that makes both short and long-term analyses, trading decisions, and executions based on the overall trend and its strength. This article will explore in detail an EA that is specifically designed for traders who are patient, disciplined, and focused enough to only execute trades and hold their positions only when trading with strength and in the trend direction without changing their bias frequently, especially against the trend, until take-profit targets are hit.
Reimagining Classic Strategies (Part 21): Bollinger Bands And RSI Ensemble Strategy Discovery
Reimagining Classic Strategies (Part 21): Bollinger Bands And RSI Ensemble Strategy Discovery
This article explores the development of an ensemble algorithmic trading strategy for the EURUSD market that combines the Bollinger Bands and the Relative Strength Indicator (RSI). Initial rule-based strategies produced high-quality signals but suffered from low trade frequency and limited profitability. Multiple iterations of the strategy were evaluated, revealing flaws in our understanding of the market, increased noise, and degraded performance. By appropriately employing statistical learning algorithms, shifting the modeling target to technical indicators, applying proper scaling, and combining machine learning forecasts with classical trading rules, the final strategy achieved significantly improved profitability and trade frequency while maintaining acceptable signal quality.
Overcoming The Limitation of Machine Learning (Part 5): A Quick Recap of Time Series Cross Validation
Overcoming The Limitation of Machine Learning (Part 5): A Quick Recap of Time Series Cross Validation
In this series of articles, we look at the challenges faced by algorithmic traders when deploying machine-learning-powered trading strategies. Some challenges within our community remain unseen because they demand deeper technical understanding. Today’s discussion acts as a springboard toward examining the blind spots of cross-validation in machine learning. Although often treated as routine, this step can easily produce misleading or suboptimal results if handled carelessly. This article briefly revisits the essentials of time series cross-validation to prepare us for more in-depth insight into its hidden blind spots.
Creating Custom Indicators in MQL5 (Part 5): WaveTrend Crossover Evolution Using Canvas for Fog Gradients, Signal Bubbles, and Risk Management
Creating Custom Indicators in MQL5 (Part 5): WaveTrend Crossover Evolution Using Canvas for Fog Gradients, Signal Bubbles, and Risk Management
In this article, we enhance the Smart WaveTrend Crossover indicator in MQL5 by integrating canvas-based drawing for fog gradient overlays, signal boxes that detect breakouts, and customizable buy/sell bubbles or triangles for visual alerts. We incorporate risk management features with dynamic take-profit and stop-loss levels calculated via candle multipliers or percentages, displayed through lines and a table, alongside options for trend filtering and box extensions.
Statistical Arbitrage Through Cointegrated Stocks (Part 10): Detecting Structural Breaks
Statistical Arbitrage Through Cointegrated Stocks (Part 10): Detecting Structural Breaks
This article presents the Chow test for detecting structural breaks in pair relationships and the application of the Cumulative Sum of Squares - CUSUM - for structural breaks monitoring and early detection. The article uses the Nvidia/Intel partnership announcement and the US Gov foreign trade tariff announcement as examples of slope inversion and intercept shift, respectively. Python scripts for all the tests are provided.
MQL5 Trading Tools (Part 13): Creating a Canvas-Based Price Dashboard with Graph and Stats Panels
MQL5 Trading Tools (Part 13): Creating a Canvas-Based Price Dashboard with Graph and Stats Panels
In this article, we develop a canvas-based price dashboard in MQL5 using the CCanvas class to create interactive panels for visualizing recent price graphs and account statistics, with support for background images, fog effects, and gradient fills. The system includes draggable and resizable features via mouse event handling, theme toggling between dark and light modes with dynamic color adjustments, and minimize/maximize controls for efficient chart space management.
Python-MetaTrader 5 Strategy Tester (Part 04): Tester 101
Python-MetaTrader 5 Strategy Tester (Part 04): Tester 101
In this fascinating article, we build our very first trading robot in the simulator and run a strategy testing action that resembles how the MetaTrader 5 strategy tester works, then compare the outcome produced in a custom simulation against our favorite terminal.
MQL5 Trading Tools (Part 14): Pixel-Perfect Scrollable Text Canvas with Antialiasing and Rounded Scrollbar
MQL5 Trading Tools (Part 14): Pixel-Perfect Scrollable Text Canvas with Antialiasing and Rounded Scrollbar
In this article, we enhance the canvas-based price dashboard in MQL5 by adding a pixel-perfect scrollable text panel for usage guides, overcoming native scrolling limitations through custom antialiasing and a rounded scrollbar design with hover-expand functionality. The text panel supports themed backgrounds with opacity, dynamic line wrapping for content like instructions and contacts, and interactive navigation via up/down buttons, slider dragging, and mouse wheel scrolling within the body area.
Creating Custom Indicators in MQL5 (Part 6): Evolving RSI Calculations with Smoothing, Hue Shifts, and Multi-Timeframe Support
Creating Custom Indicators in MQL5 (Part 6): Evolving RSI Calculations with Smoothing, Hue Shifts, and Multi-Timeframe Support
In this article, we build a versatile RSI indicator in MQL5 supporting multiple variants, data sources, and smoothing methods for improved analysis. We add hue shifts for color visuals, dynamic boundaries for overbought/oversold zones, and notifications for trend alerts. It includes multi-timeframe support with interpolation, offering us a customizable RSI tool for diverse strategies.
MetaTrader 5 on Linux
MetaTrader 5 on Linux
In this article, we demonstrate an easy way to install MetaTrader 5 on popular Linux versions — Ubuntu and Debian. These systems are widely used on server hardware as well as on traders’ personal computers.
Automating Trading Strategies in MQL5 (Part 47): Nick Rypock Trailing Reverse (NRTR) with Hedging Features
Automating Trading Strategies in MQL5 (Part 47): Nick Rypock Trailing Reverse (NRTR) with Hedging Features
In this article, we develop a Nick Rypock Trailing Reverse (NRTR) trading system in MQL5 that uses channel indicators for reversal signals, enabling trend-following entries with hedging support for buys and sells. We incorporate risk management features like auto lot sizing based on equity or balance, fixed or dynamic stop-loss and take-profit levels using ATR multipliers, and position limits.
Graph Theory: Traversal Breadth-First Search (BFS) Applied in Trading
Graph Theory: Traversal Breadth-First Search (BFS) Applied in Trading
Breadth First Search (BFS) uses level-order traversal to model market structure as a directed graph of price swings evolving through time. By analyzing historical bars or sessions layer by layer, BFS prioritizes recent price behavior while still respecting deeper market memory.
From Novice to Expert: Statistical Validation of Supply and Demand Zones
From Novice to Expert: Statistical Validation of Supply and Demand Zones
Today, we uncover the often overlooked statistical foundation behind supply and demand trading strategies. By combining MQL5 with Python through a Jupyter Notebook workflow, we conduct a structured, data-driven investigation aimed at transforming visual market assumptions into measurable insights. This article covers the complete research process, including data collection, Python-based statistical analysis, algorithm design, testing, and final conclusions. To explore the methodology and findings in detail, read the full article.
From Novice to Expert: Developing a Liquidity Strategy
From Novice to Expert: Developing a Liquidity Strategy
Liquidity zones are commonly traded by waiting for the price to return and retest the zone of interest, often through the placement of pending orders within these areas. In this article, we leverage MQL5 to bring this concept to life, demonstrating how such zones can be identified programmatically and how risk management can be systematically applied. Join the discussion as we explore both the logic behind liquidity-based trading and its practical implementation.
Price Action Analysis Toolkit Development (Part 19): ZigZag Analyzer
Price Action Analysis Toolkit Development (Part 19): ZigZag Analyzer
Every price action trader manually uses trendlines to confirm trends and spot potential turning or continuation levels. In this series on developing a price action analysis toolkit, we introduce a tool focused on drawing slanted trendlines for easy market analysis. This tool simplifies the process for traders by clearly outlining key trends and levels essential for effective price action evaluation.
Forex arbitrage trading: A simple synthetic market maker bot to get started
Forex arbitrage trading: A simple synthetic market maker bot to get started
Today we will take a look at my first arbitrage robot — a liquidity provider (if you can call it that) for synthetic assets. Currently, this bot is successfully operating as a module in a large machine learning system, but I pulled up an old Forex arbitrage robot from the cloud, so let's take a look at it and think about what we can do with it today.
Integrating External Applications with MQL5 Community OAuth
Integrating External Applications with MQL5 Community OAuth
Learn how to add “Sign in with MQL5” to your Android app using the OAuth 2.0 authorization code flow. The guide covers app registration, endpoints, redirect URI, Custom Tabs, deep-link handling, and a PHP backend that exchanges the code for an access token over HTTPS. You will authenticate real MQL5 users and access profile data such as rank and reputation.
Employing Game Theory Approaches in Trading Algorithms
Employing Game Theory Approaches in Trading Algorithms
We are creating an adaptive self-learning trading expert advisor based on DQN machine learning, with multidimensional causal inference. The EA will successfully trade simultaneously on 7 currency pairs. And agents of different pairs will exchange information with each other.
Using Deep Reinforcement Learning to Enhance Ilan Expert Advisor
Using Deep Reinforcement Learning to Enhance Ilan Expert Advisor
We revisit the Ilan grid Expert Advisor and integrate Q-learning in MQL5 to build an adaptive version for MetaTrader 5. The article shows how to define state features, discretize them for a Q-table, select actions with ε-greedy, and shape rewards for averaging and exits. You will implement saving/loading the Q-table, tune learning parameters, and test on EURUSD/AUDUSD in the Strategy Tester to evaluate stability and drawdown risks.
Price Action Analysis Toolkit Development (Part 59): Using Geometric Asymmetry to Identify Precision Breakouts from Fractal Consolidation
Price Action Analysis Toolkit Development (Part 59): Using Geometric Asymmetry to Identify Precision Breakouts from Fractal Consolidation
While studying a wide range of breakout setups, I noticed that failed breakouts were rarely caused by a lack of volatility, but more often by weak internal structure. That observation led to the framework presented in this article. The approach identifies patterns where the final price leg shows superior length, steepness, and speed—clear signs of momentum accumulation ahead of directional expansion. By detecting these subtle geometric imbalances within consolidation, traders can anticipate higher-probability breakouts before price exits the range. Continue reading to see how this fractal-based, geometric framework translates structural imbalance into precise breakout signals.
Billiards Optimization Algorithm (BOA)
Billiards Optimization Algorithm (BOA)
The BOA method is inspired by the classic game of billiards and simulates the search for optimal solutions as a game with balls trying to fall into pockets representing the best results. In this article, we will consider the basics of BOA, its mathematical model, and its efficiency in solving various optimization problems.
Currency pair strength indicator in pure MQL5
Currency pair strength indicator in pure MQL5
We are going to develop a professional indicator for currency strength analysis in MQL5. This step-by-step guide will show you how to develop a powerful trading tool with a visual dashboard for MetaTrader 5. You will learn how to calculate the strength of currency pairs across multiple timeframes (H1, H4, D1), implement dynamic data updates, and create a user-friendly interface.