Articles on the MQL5 programming and use of trading robots

In this article, we enhance the 3D binomial distribution graphing tool in MQL5 by adding a segmented 3D curve for improved depth perception of the probability mass function, integrating pan mode for view target shifting, and implementing an interactive view cube with hover zones and animations for quick orientation changes. We incorporate clickable sub-zones on the view cube for faces, edges, and corners to animate camera transitions to standard views, while maintaining switchable 2D/3D modes, real-time updates, and customizable parameters for immersive probabilistic analysis in trading.

Monitoring manually drawn trendlines requires constant chart observation, which can cause important price interactions to be missed. This article develops a trendline monitoring Expert Advisor that synchronizes manually drawn trendlines with automated monitoring logic in MQL5, generating alerts when price approaches, touches, or breaks a monitored line.

The DUET framework offers an innovative approach to time series analysis, combining temporal and channel clustering to uncover hidden patterns in the analyzed data. This allows models to adapt to changes over time and improve forecasting quality by eliminating noise.

In part 2, we extend the news filter to protect existing positions during news events. Instead of closing trades, we temporarily remove stop-loss and take-profit levels, storing them safely in memory. When the news window ends, stops are deterministically restored, adjusted if price has already crossed the original levels, while respecting broker minimum distance rules. The result is a mechanism that preserves trade integrity without interfering with entry logic, keeping the EA in control through volatility.

This article applies Depth-First Search to market structure by modeling swing highs and lows as graph nodes and tracking one structural path as deeply as conditions remain valid. When a key swing is broken, the algorithm backtracks and explores an alternative branch. Readers gain a practical framework to formalize structural bias and test whether the current path aligns with targets like liquidity pools or supply and demand zones.

This article details an MQL5 framework that restricts trading to an approved set of symbols. The solution combines a shared library, a configuration dashboard, and an enforcement Expert Advisor that validates each trade against a whitelist and logs blocked attempts. It includes fully functional code examples, a clear explanation of the structural design decisions, and validation tests that confirm reliable symbol filtering, controlled market exposure, and transparent monitoring of rule enforcement.

For maximum reliability and productivity in MetaTrader products built with MQL, this article advocates a development approach based on reusable “packages” managed by KnitPkg, a project manager for MQL5/MQL4. A package can be used as a building block for other packages or as the foundation for final artifacts that run directly on the MetaTrader platform, such as EAs, indicators, and more.

We have developed a system that enforces a daily trade limit to keep you aligned with your trading rules. It monitors all executed trades across the account and automatically intervenes once the defined limit is reached, preventing any further activity. By embedding control directly into the platform, the system ensures discipline is maintained even when market pressure rises.

The article builds a transparent MQL5 Expert Advisor for Larry Williams’ hidden smash day reversals. Signals are generated only on new bars: a setup bar is validated, then confirmed when the next session trades beyond its extreme. Risk is managed via ATR or structural stops with a defined risk-to-reward, position sizing can be fixed or balance-based, and direction filters plus a one-position policy ensure reproducible tests.

We continue to integrate methods proposed by the authors of the Attraos framework into trading models. Let me remind you that this framework uses concepts of chaos theory to solve time series forecasting problems, interpreting them as projections of multidimensional chaotic dynamic systems.

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.

In this article, we enhance the regression graphing tool in MQL5 by adding a cyberpunk theme mode with neon glows, animations, and holographic effects for immersive visualization. We integrate theme toggling, dynamic backgrounds with stars, glowing borders, and neon points/lines, while maintaining standard mode compatibility. This dual-theme system elevates pair analysis with futuristic aesthetics, supporting real-time updates and interactions for engaging trading insights.

In this discussion we will Automate Swing Extremes and the Pullback Indicator, which transforms raw lower-timeframe (LTF) price action into a structured map of market intent, precisely identifying swing highs, swing lows, and corrective phases in real time. By programmatically tracking microstructure shifts, it anticipates potential reversals before they fully unfold—turning noise into actionable insight.

We build a calendar‑driven news filter entirely in MQL5, avoiding web requests and external DLLs. Part 1 covers loading and caching events, mapping them to symbols by currency, filtering by impact level, defining pre/post windows, and blocking new trades during active news, with optional pre‑news position closure. The result is a configurable, prop‑firm‑friendly control that reduces false pauses and protects entries during volatility.

This article turns Market Memory Zones from a chart-only concept into a complete MQL5 Expert Advisor. It automates Displacement, Structure Transition (CHoCH), and Liquidity Sweep zones using ATR- and candle-structure filters, applies lower-timeframe confirmation, and enforces risk-based position sizing with dynamic SL and structure-based TP. You will get the code architecture for detection, entries, trade management, and visualization, plus a brief backtest review.

We present a slanted trendline breakout tool that relies on three‑swing validation to generate objective, price‑action signals. The system automates swing detection, trendline construction, and breakout confirmation using crossing logic to reduce noise and standardize execution. The article explains the strategy rules, shows the MQL5 implementation, and reviews testing results; the tool is intended for analysis and signal confirmation, not automated trading.

This is an article about a specialized trend-following EA that aims to clearly elaborate how to utilize trading setups after liquidity raids. This article will explore in detail an EA that is specifically designed for traders who are keen on optimizing and utilizing liquidity raids and purges as entry criteria for their trades and trading decisions. It will also explore how to correctly differentiate between liquidity raids and market structure shifts and how to validate and utilize each of them when they occur, thus trying to mitigate losses that occur from traders confusing the two.

In this article, we explore vector-based methods for drawing rounded rectangles and triangles in MQL5 using canvas, with supersampling for anti-aliased rendering. We implement scanline filling, geometric precomputations for arcs and tangents, and border drawing to create smooth, customizable shapes. This approach lays the groundwork for modern UI elements in future trading tools, supporting inputs for sizes, radii, borders, and opacities.

We add supersampling‑driven anti‑aliasing and high‑resolution rendering to the MQL5 canvas dashboard, then downsample to the target size. The article implements rounded rectangle fills and borders, rounded triangle arrows, and a custom scrollbar with theming for the stats and text panels. These tools help you build smoother, more legible UI components in MetaTrader 5.

This article introduces file handling in MQL5 using a practical, project-based workflow. You will use FileSelectDialog to choose or create a CSV file, open it with FileOpen, and write structured account headers such as account name, balance, login, date range, and last update. The result is a clear foundation for a reusable trading journal and safe file operations in MetaTrader 5.

In this article, we explore the File Operations classes of the MQL5 Standard Library to build a robust reporting module that automatically generates Excel-ready CSV files. Along the way, we clearly distinguish between manually executed trades and algorithmically executed orders, laying the groundwork for reliable, auditable trade reporting.

This article presents a MetaTrader 5–compatible backtesting workflow that scales across symbols and timeframes. We use HistoryManager to parallelize data collection, synchronize bars and ticks from all timeframes, and run symbol‑isolated OnTick handlers in threads. You will learn how modelling modes affect speed/accuracy, when to rely on terminal data, how to reduce I/O with event‑driven updates, and how to assemble a complete multicurrency trading robot.

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.

We implement Larry Williams’ Smash Day reversal patterns in MQL5 by building a rule-based Expert Advisor with dynamic risk management, breakout confirmation logic, and one trade at a time execution. Readers can backtest, reproduce, and study parameter effects using the MetaTrader 5 Strategy Tester and the provided source.

Create a practical bridge between MetaTrader 5 and Binance: fetch 30‑minute klines with WebRequest, extract OHLC/time values from JSON, and confirm a bullish engulfing pattern using only completed candles. Then assemble the query string, compute the HMAC‑SHA256 signature, add X‑MBX‑APIKEY, and submit authenticated orders. You get a clear, end‑to‑end EA workflow from data acquisition to order execution.

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.

In this part, we will focus on designing an intelligent execution layer that continuously monitors and evaluates real-time spread conditions across multiple symbols. The EA dynamically adapts its symbol selection by enabling or disabling trading based on spread efficiency rather than fixed rules. This approach allows high-frequency multi-pair systems to prioritize cost-effective symbols.

We continue exploring hybrid graph sequence models (GSM++), which integrate the advantages of different architectures, providing high analysis accuracy and efficient distribution of computing resources. These models effectively identify hidden patterns, reducing the impact of market noise and improving forecasting quality.

Wave analysis is one of the methods used in technical analysis. This article focuses on two less conventional wave patterns: triangular and sawtooth waves. These formations underpin a number of technical indicators designed for market price analysis.