The MQL5 Standard Library Explorer (Part 9): Using ALGLIB to Filter Excessive MA Crossover Signals
During sideways price movements, traders face excessive signals from multiple moving average crossovers. Today, we discuss how ALGLIB preprocesses raw price data to produce filtered crossover layers, which can also generate alerts when they occur. Join this discussion to learn how a mathematical library can be leveraged in MQL5 programs.
Building a Candlestick Trend Constraint Model (Part 8): Expert Advisor Development (I)
In this discussion, we will create our first Expert Advisor in MQL5 based on the indicator we made in the prior article. We will cover all the features required to make the process automatic, including risk management. This will extensively benefit the users to advance from manual execution of trades to automated systems.
Price Action Analysis Toolkit Development (Part 74): Building an MQL5 Expert Advisor from Indicator Buffers
This article implements an MQL5 Expert Advisor that connects to a weekend gap indicator via iCustom and CopyBuffer, reading six buffers for buy/sell signals and SL/TP. It validates broker stop-distance rules, handles closed-bar confirmation and duplicate-signal control, and executes orders with a configurable magic number. The EA also includes midpoint stop-loss management and a backtesting procedure so you can verify behavior and adapt parameters to your setup.
Volumetric neural network analysis as a key to future trends
The article explores the possibility of improving price forecasting based on trading volume analysis by integrating technical analysis principles with LSTM neural network architecture. Particular attention is paid to the detection and interpretation of anomalous volumes, the use of clustering and the creation of features based on volumes and their definition in the context of machine learning.
Expert System 'Commentator'. Practical Use of Embedded Indicators in an MQL4 Program
The article describes the use of technical indicators in programming on MQL4.
Neural networks made easy (Part 33): Quantile regression in distributed Q-learning
We continue studying distributed Q-learning. Today we will look at this approach from the other side. We will consider the possibility of using quantile regression to solve price prediction tasks.
Mastering PD Arrays: Optimizing Trading from Imbalances in PD Arrays
This is an article about a specialized trend-following EA that aims to clearly elaborate how to frame and utilize trading setups that occur from imbalances found in PD arrays. This article will explore in detail an EA that is specifically designed for traders who are keen on optimizing and utilizing PD arrays and imbalances as entry criteria for their trades and trading decisions. It will also explore how to correctly determine and profile premium and discount arrays and how to validate and utilize each of them when they occur in their respective market conditions, thus trying to maximize opportunities that occur from such scenarios.
Neural Networks in Trading: A Multimodal, Tool-Augmented Agent for Financial Markets (FinAgent)
We invite you to explore FinAgent, a multimodal financial trading agent framework designed to analyze various types of data reflecting market dynamics and historical trading patterns.
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
Automating Trading Strategies in MQL5 (Part 28): Creating a Price Action Bat Harmonic Pattern with Visual Feedback
In this article, we develop a Bat Pattern system in MQL5 that identifies bullish and bearish Bat harmonic patterns using pivot points and Fibonacci ratios, triggering trades with precise entry, stop loss, and take-profit levels, enhanced with visual feedback through chart objects
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.
Timeseries in DoEasy library (part 52): Cross-platform nature of multi-period multi-symbol single-buffer standard indicators
In the article, consider creation of multi-symbol multi-period standard indicator Accumulation/Distribution. Slightly improve library classes with respect to indicators so that, the programs developed for outdated platform MetaTrader 4 based on this library could work normally when switching over to MetaTrader 5.
SP500 Trading Strategy in MQL5 For Beginners
Discover how to leverage MQL5 to forecast the S&P 500 with precision, blending in classical technical analysis for added stability and combining algorithms with time-tested principles for robust market insights.
Introduction to MQL5 (Part 18): Introduction to Wolfe Wave Pattern
This article explains the Wolfe Wave pattern in detail, covering both the bearish and bullish variations. It also breaks down the step-by-step logic used to identify valid buy and sell setups based on this advanced chart pattern.
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.
Price Action Analysis Toolkit Development (Part 65): Building an MQL5 System to Monitor and Analyze Manually Drawn Fibonacci Levels
The Fibonacci retracement tool is an essential component of price action analysis, providing critical levels for potential market reactions. However, its effectiveness is often limited by the need for continuous human monitoring, which can lead to missed setups. In this part of our series, we introduce a tool that synchronizes and actively monitors manually drawn Fibonacci levels using MQL5, combining discretionary insight with automated oversight.
Design Patterns in software development and MQL5 (Part 3): Behavioral Patterns 1
A new article from Design Patterns articles and we will take a look at one of its types which is behavioral patterns to understand how we can build communication methods between created objects effectively. By completing these Behavior patterns we will be able to understand how we can create and build a reusable, extendable, tested software.
Building A Candlestick Trend Constraint Model (Part 9): Multiple Strategies Expert Advisor (I)
Today, we will explore the possibilities of incorporating multiple strategies into an Expert Advisor (EA) using MQL5. Expert Advisors provide broader capabilities than just indicators and scripts, allowing for more sophisticated trading approaches that can adapt to changing market conditions. Find, more in this article discussion.
Neural networks made easy (Part 55): Contrastive intrinsic control (CIC)
Contrastive training is an unsupervised method of training representation. Its goal is to train a model to highlight similarities and differences in data sets. In this article, we will talk about using contrastive training approaches to explore different Actor skills.
Creating an MQL5-Telegram Integrated Expert Advisor (Part 6): Adding Responsive Inline Buttons
In this article, we integrate interactive inline buttons into an MQL5 Expert Advisor, allowing real-time control via Telegram. Each button press triggers specific actions and sends responses back to the user. We also modularize functions for handling Telegram messages and callback queries efficiently.
Automating Trading Strategies in MQL5 (Part 39): Statistical Mean Reversion with Confidence Intervals and Dashboard
In this article, we develop an MQL5 Expert Advisor for statistical mean reversion trading, calculating moments like mean, variance, skewness, kurtosis, and Jarque-Bera statistics over a specified period to identify non-normal distributions and generate buy/sell signals based on confidence intervals with adaptive thresholds
Neural Networks in Trading: Enhancing Transformer Efficiency by Reducing Sharpness (SAMformer)
Training Transformer models requires large amounts of data and is often difficult since the models are not good at generalizing to small datasets. The SAMformer framework helps solve this problem by avoiding poor local minima. This improves the efficiency of models even on limited training datasets.
Swing Extremes and Pullbacks in MQL5 (Part 3): Defining Structural Validity Beyond Simple Highs/Lows
This article presents an MQL5 Expert Advisor that upgrades raw swing detection to a rule-based Structural Validation Engine. Swings are confirmed by a break of structure, displacement, liquidity sweeps, or time-based respect, then linked to a liquidity map and a structural state machine. The result is context-aware entries and stops anchored to validated levels, helping filter noise and systematize execution.
Neural Networks in Trading: A Parameter-Efficient Transformer with Segmented Attention (PSformer)
This article introduces the new PSformer framework, which adapts the architecture of the vanilla Transformer to solving problems related to multivariate time series forecasting. The framework is based on two key innovations: the Parameter Sharing (PS) mechanism and the Segment Attention (SegAtt).
Developing a Replay System — Market simulation (Part 20): FOREX (I)
The initial goal of this article is not to cover all the possibilities of Forex trading, but rather to adapt the system so that you can perform at least one market replay. We'll leave simulation for another moment. However, if we don't have ticks and only bars, with a little effort we can simulate possible trades that could happen in the Forex market. This will be the case until we look at how to adapt the simulator. An attempt to work with Forex data inside the system without modifying it leads to a range of errors.
Price Action Analysis Toolkit Development (Part 54): Filtering Trends with EMA and Smoothed Price Action
This article explores a method that combines Heikin‑Ashi smoothing with EMA20 High and Low boundaries and an EMA50 trend filter to improve trade clarity and timing. It demonstrates how these tools can help traders identify genuine momentum, filter out noise, and better navigate volatile or trending markets.
Neural Networks in Trading: Integrating Chaos Theory into Time Series Forecasting (Attraos)
The Attraos framework integrates chaos theory into long-term time series forecasting, treating them as projections of multidimensional chaotic dynamic systems. Exploiting attractor invariance, the model uses phase space reconstruction and dynamic multi-resolution memory to preserve historical structures.
MQL5 Wizard Techniques you should know (Part 83): Using Patterns of Stochastic Oscillator and the FrAMA — Behavioral Archetypes
The Stochastic Oscillator and the Fractal Adaptive Moving Average are another indicator pairing that could be used for their ability to compliment each other within an MQL5 Expert Advisor. We look at the Stochastic for its ability to pinpoint momentum shifts, while the FrAMA is used to provide confirmation of the prevailing trends. In exploring this indicator pairing, as always, we use the MQL5 wizard to build and test out their potential.
Developing a trading Expert Advisor from scratch (Part 20): New order system (III)
We continue to implement the new order system. The creation of such a system requires a good command of MQL5, as well as an understanding of how the MetaTrader 5 platform actually works and what resources it provides.
Creating Custom Indicators in MQL5 (Part 2): Building a Gauge-Style RSI Display with Canvas and Needle Mechanics
In this article, we develop a gauge-style RSI indicator in MQL5 that visualizes Relative Strength Index values on a circular scale with a dynamic needle, color-coded ranges for overbought and oversold levels, and customizable legends. We utilize the Canvas class to draw elements like arcs, ticks, and pies, ensuring smooth updates on new RSI data.
Triangular arbitrage with predictions
This article simplifies triangular arbitrage, showing you how to use predictions and specialized software to trade currencies smarter, even if you're new to the market. Ready to trade with expertise?
Price Action Analysis Toolkit Development (Part 5): Volatility Navigator EA
Determining market direction can be straightforward, but knowing when to enter can be challenging. As part of the series titled "Price Action Analysis Toolkit Development", I am excited to introduce another tool that provides entry points, take profit levels, and stop loss placements. To achieve this, we have utilized the MQL5 programming language. Let’s delve into each step in this article.
Expert Advisors Based on Popular Trading Systems and Alchemy of Trading Robot Optimization (Part V)
In this article the author offers ways to improve trading systems described in his previous articles. The article will be interesting for traders that already have some experience of writing Expert Advisors.
Fast trading strategy tester in Python using Numba
The article implements a fast strategy tester for machine learning models using Numba. It is 50 times faster than the pure Python strategy tester. The author recommends using this library to speed up mathematical calculations, especially the ones involving loops.
Price Action Analysis Toolkit Development (Part 68): Price-Attached RSI Panel in MQL5
We present a chart-embedded RSI panel that removes the need for a separate window by attaching momentum directly to live price. The article explains the design and MQL5 code: real-time RSI retrieval, slope-based signal classification, and adaptive positioning. Traders get RSI value, state, and signal strength where decisions are made, improving clarity across timeframes.
Creating an Interactive Graphical User Interface in MQL5 (Part 2): Adding Controls and Responsiveness
Enhancing the MQL5 GUI panel with dynamic features can significantly improve the trading experience for users. By incorporating interactive elements, hover effects, and real-time data updates, the panel becomes a powerful tool for modern traders.
Developing a Replay System (Part 38): Paving the Path (II)
Many people who consider themselves MQL5 programmers do not have the basic knowledge that I will outline in this article. Many people consider MQL5 to be a limited tool, but the actual reason is that they do not have the required knowledge. So, if you don't know something, don't be ashamed of it. It's better to feel ashamed for not asking. Simply forcing MetaTrader 5 to disable indicator duplication in no way ensures two-way communication between the indicator and the Expert Advisor. We are still very far from this, but the fact that the indicator is not duplicated on the chart gives us some confidence.
MQL5 Wizard Techniques you should know (Part 42): ADX Oscillator
The ADX is another relatively popular technical indicator used by some traders to gauge the strength of a prevalent trend. Acting as a combination of two other indicators, it presents as an oscillator whose patterns we explore in this article with the help of MQL5 wizard assembly and its support classes.
Price Action Analysis Toolkit Development (Part 12): External Flow (III) TrendMap
The flow of the market is determined by the forces between bulls and bears. There are specific levels that the market respects due to the forces acting on them. Fibonacci and VWAP levels are especially powerful in influencing market behavior. Join me in this article as we explore a strategy based on VWAP and Fibonacci levels for signal generation.
Trading Insights Through Volume: Trend Confirmation
The Enhanced Trend Confirmation Technique combines price action, volume analysis, and machine learning to identify genuine market movements. It requires both price breakouts and volume surges (50% above average) for trade validation, while using an LSTM neural network for additional confirmation. The system employs ATR-based position sizing and dynamic risk management, making it adaptable to various market conditions while filtering out false signals.