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.
In this article, we show how to send authenticated requests to the Binance API using MQL5 to retrieve your account balance for all assets. Learn how to use your API key, server time, and signature to securely access account data, and how to save the response to a file for future use.
From ChatGPT to Gemini and many model AI tools for text, image, and video generation. Transformers have rocked the AI-world. But, are they applicable in the financial (trading) space? Let's find out.
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.
This article presents a session-based analytical framework that combines time-defined market sessions with the Candle Pressure Index (CPI) to classify acceptance and rejection behavior at session boundaries using closed-candle data and clearly defined rules.
Hybrid graph sequence models (GSM++) combine the advantages of different architectures to provide high-fidelity data analysis and optimized computational costs. These models adapt effectively to dynamic market data, improving the presentation and processing of financial information.
This article introduces the basic concepts behind HMAC-SHA256 and API signatures in MQL5, explaining how messages and secret keys are combined to securely authenticate requests. It lays the foundation for signing API calls without exposing sensitive data.
In this article, we enhance the correlation matrix dashboard in MQL5 with interactive features like panel dragging, minimizing/maximizing, hover effects on buttons and timeframes, and mouse event handling for improved user experience. We add sorting of symbols by average correlation strength in ascending/descending modes, toggle between correlation and p-value views, and incorporate light/dark theme switching with dynamic color updates.
In this article, we will continue to connect the new strategy to the created auto optimization system. Let's look at what changes need to be made to the optimization project creation EA, as well as the second and third stage EAs.
In this article we introduce Python-MetaTrader5-like ways of handling trading operations such as opening, closing, and modifying orders in the simulator. To ensure the simulation behaves like MetaTrader 5, a strict validation layer for trade requests is implemented, taking into account symbol trading parameters and typical brokerage restrictions.
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.
In this article, we build a correlation matrix dashboard in MQL5 to compute asset relationships using Pearson, Spearman, and Kendall methods over a set timeframe and bars. The system offers standard mode with color thresholds and p-value stars, plus heatmap mode with gradient visuals for correlation strengths. It includes an interactive UI with timeframe selectors, mode toggles, and a dynamic legend for efficient analysis of symbol interdependencies.
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.
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.
This article demonstrates how to automate Larry Williams’ volatility breakout strategy in MQL5 using a practical, step-by-step approach. You will learn how to calculate daily range expansions, derive buy and sell levels, manage risk with range-based stops and reward-based targets, and structure a professional Expert Advisor for MetaTrader 5. Designed for traders and developers looking to transform Larry Williams’ market concepts into a fully testable and deployable automated trading system.
In this article, you will learn how to create an interactive control panel in MetaTrader 5. We cover the basics of adding input fields, action buttons, and labels to display text. Using a project-based approach, you will see how to set up a panel where users can type messages and eventually display server responses from an API.
In this article, we will explore the innovative Chimera framework: a two-dimensional state-space model that uses neural networks to analyze multivariate time series. This method offers high accuracy with low computational cost, outperforming traditional approaches and Transformer architectures.
Master the automation of Larry Williams’ short-term swing patterns using MQL5. In this guide, we develop a fully configurable Expert Advisor (EA) that leverages non-random market structures. We’ll cover how to integrate robust risk management and flexible exit logic, providing a solid foundation for systematic strategy development and backtesting.
This article demonstrates how to integrate the Google Generative AI API with MetaTrader 5 using MQL5. You will learn how to structure API requests, handle server responses, extract AI-generated content, manage rate limits, and save the results to a text file for easy access.
In this article, we enhance the AI-powered trading system in MQL5 with user interface improvements, including loading animations for request preparation and thinking phases, as well as timing metrics displayed in responses for better feedback. We add response management tools like regenerate buttons to re-query the AI and export options to save the last response to a file, streamlining interaction.
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.
In this article, we will attempt to predict the market with a decent model for time series forecasting named DeepAR. A model that is a combination of deep neural networks and autoregressive properties found in models like ARIMA and Vector Autoregressive (VAR).
In high-probability support and resistance zones, valid entry confirmation signals are always present once the zone has been correctly identified. In this discussion, we build an intelligent MQL5 program that automatically detects entry conditions within these zones. We leverage well-known candlestick patterns alongside native confirmation indicators to validate trade decisions. Click to read further.
Learn how to automate Larry Williams market structure concepts in MQL5 by building a complete Expert Advisor that reads swing points, generates trade signals, manages risk, and applies a dynamic trailing stop strategy.
Market rules are continuously evolving, and many once-reliable principles gradually lose their effectiveness. What worked in the past no longer works consistently over time. Today’s discussion focuses on probability ranges and how they can be used to navigate market irregularities. We will leverage MQL5 to develop an algorithm capable of trading effectively even in the choppiest market conditions. Join this discussion to find out more.
MQL5 lacks built-in asymmetric cryptography, making secure data exchange over insecure channels like HTTP difficult. This article presents a pure MQL5 implementation of RSA using PKCS#1 v1.5 padding, enabling safe transmission of AES session keys and small data blocks without external libraries. This approach provides HTTPS-like security over standard HTTP and even more, it fills an important gap in secure communication for MQL5 applications.
For many traders, the gap between knowing a risk rule and following it consistently is where accounts go to die. Emotional overrides, revenge trading, and simple oversight can dismantle even the best strategy. Today, we will transform the MetaTrader 5 platform into an unwavering enforcer of your trading rules by developing a Risk Enforcement Expert Advisor. Join this discussion to find out more.
In this article, we enhance the AI-powered trading system's modularity by separating UI components into a dedicated include file. The system now automates trade execution based on AI-generated signals, parsing JSON responses for BUY/SELL/NONE with entry/SL/TP, visualizing patterns like engulfing or divergences on charts with arrows, lines, and labels, and optional auto-signal checks on new bars.
We continue our look at how the selection of indicators can be pipelined when facing a ‘none-typical’ MetaTrader asset. MetaTrader 5 is primarily used to trade forex, and that is good given the liquidity on offer, however the case for trading outside of this ‘comfort-zone’, is growing bolder with not just the overnight rise of platforms like Robinhood, but also the relentless pursuit of an edge for most traders. We consider the XLF ETF for this article and also cap our revamped pipeline with a simple MLP.
In this article, we will explore practical techniques for trading the Relative Strength Index (RSI) oscillator with market structure. Our focus will be on channel price action patterns, how they are typically traded, and how MQL5 can be leveraged to enhance this process. By the end, you will have a rule-based, automated channel-trading system designed to capture trend continuation opportunities with greater precision and consistency.
Learn how to use WebRequest and external API calls to retrieve recent candle data, convert each value into a usable type, and save the information neatly in a table format. This step lays the groundwork for building an indicator that visualizes the data in candle format.
In this article, we build a Liquidity Sweep on Break of Structure (BoS) system in MQL5 that detects swing highs/lows over a user-defined length, labels them as HH/HL/LH/LL to identify BOS (HH in uptrend or LL in downtrend), and spots liquidity sweeps when price wicks beyond the swing but closes back inside on a bullish/bearish candle.
This article explains the design of a prop-firm Expert Advisor for GOLD, featuring breakout filters, multi-timeframe analysis, robust risk management, and strict drawdown protection. The EA helps traders pass prop-firm challenges by avoiding rule breaches and stabilizing trade execution under volatile market conditions.
We continue our look at how MetaTrader can be used outside its forex trading ‘comfort-zone’ by looking at another tradable asset in the form of the FXI ETF. Unlike in the last article where we tried to do ‘too-much’ by delving into not just indicator selection, but also considering indicator pattern combinations, for this article we will swim slightly upstream by focusing more on indicator selection. Our end product for this is intended as a form of pipeline that can help recommend indicators for various assets, provided we have a reasonable amount of their price history.
This topic explores how to build an Adaptive Smart Money Architecture (ASMA)—an intelligent Expert Advisor that merges Smart Money Concepts (Order Blocks, Break of Structure, Fair Value Gaps) with real-time market sentiment to automatically choose the best trading strategy depending on current market conditions.
In this article, we will look at how to connect a new strategy to the auto optimization system we have created. Let's see what kind of EAs we need to create and whether it will be possible to do without changing the EA library files or minimize the necessary changes.
Learn how to build a complete Kagi-based trading Expert Advisor in MQL5, from signal construction to order execution, visual markers, and a three-stage trailing stop. Includes full code, testing results, and a downloadable set file.
In this article, we create an Inverse Fair Value Gap (IFVG) detection system in MQL5 that identifies bullish/bearish FVGs on recent bars with minimum gap size filtering, tracks their states as normal/mitigated/inverted based on price interactions (mitigation on far-side breaks, retracement on re-entry, inversion on close beyond far side from inside), and ignores overlaps while limiting tracked FVGs.
This article revisits the classic moving average crossover strategy and examines why it often fails in noisy, fast-moving markets. It presents five alternative filtering methods designed to strengthen signal quality and remove weak or unprofitable trades. The discussion highlights how statistical models can learn and correct the errors that human intuition and traditional rules miss. Readers leave with a clearer understanding of how to modernize an outdated strategy and of the pitfalls of relying solely on metrics like RMSE in financial modeling.
