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Risk Management (Part 4): Completing the Key Class Methods
Risk Management (Part 4): Completing the Key Class Methods
This is Part 4 of our series on risk management in MQL5, where we continue exploring advanced methods for protecting and optimizing trading strategies. Having laid important foundations in earlier articles, we will now focus on completing all remaining methods postponed in Part 3, including functions for checking whether specific profit or loss levels have been reached. In addition, we will introduce new key events that enable more accurate and flexible risk management.
Market Simulation (Part 12): Sockets (VI)
Market Simulation (Part 12): Sockets (VI)
In this article, we will look at how to solve certain problems and issues that arise when using Python code within other programs. More specifically, we will demonstrate a common issue encountered when using Excel in conjunction with MetaTrader 5, although we will be using Python to facilitate this interaction. However, this implementation has a minor drawback. It does not occur in all cases, but only in certain specific situations. When it does happen, it is necessary to understand the cause. In today’s article, we will begin explaining how to resolve this issue.
Market Simulation (Part 13): Sockets (VII)
Market Simulation (Part 13): Sockets (VII)
When we develop something in xlwings or any other package that allows reading and writing directly to Excel, we must note that all programs, functions, or procedures execute and then complete their task. They do not remain in a loop, no matter how hard we try to do things differently.
Creating Custom Indicators in MQL5 (Part 7): Hybrid Time Price Opportunity (TPO) Market Profiles for Session Analysis
Creating Custom Indicators in MQL5 (Part 7): Hybrid Time Price Opportunity (TPO) Market Profiles for Session Analysis
In this article, we develop a custom indicator in MQL5 for hybrid Time Price Opportunity (TPO) market profiles, supporting multiple session timeframes such as intraday, daily, weekly, monthly, and fixed periods with timezone adjustments. The indicator quantizes prices into a grid, tracks session data including highs, lows, opens, and closes, and calculates key elements like the point of control and value area based on TPO counts. It renders profiles visually on the chart with customizable colors for TPO letters, single prints, value areas, POC, and close markers, enabling detailed session analysis
Introduction to MQL5 (Part 41): Beginner Guide to File Handling in MQL5 (III)
Introduction to MQL5 (Part 41): Beginner Guide to File Handling in MQL5 (III)
Learn how to read a CSV file in MQL5 and organize its trading data into dynamic arrays. This article shows step by step how to count file elements, store all data in a single array, and separate each column into dedicated arrays, laying the foundation for advanced analysis and trading performance visualization.
Market Simulation (Part 15): Sockets (IX)
Market Simulation (Part 15): Sockets (IX)
In this article, we will discuss one of the possible solutions to what we have been trying to demonstrate—namely, how to allow an Excel user to perform an action in MetaTrader 5 without sending orders or opening or closing positions. The idea is that the user employs Excel to conduct fundamental analysis of a particular symbol. And by using only Excel, they can instruct an expert advisor running in MetaTrader 5 to open or close a specific position.
Market Simulation: (Part 11): Sockets (V)
Market Simulation: (Part 11): Sockets (V)
We are beginning to implement the connection between Excel and MetaTrader 5, but first we need to understand some key points. This way, you won't have to rack your brains trying to figure out why something works or doesn't. And before you frown at the prospect of integrating Python and Excel, let's see how we can (to some extent) control MetaTrader 5 through Excel using xlwings. What we demonstrate here will primarily focus on educational objectives. However, don't think that we can only do what will be covered here.
From Basic to Intermediate: Struct (VI)
From Basic to Intermediate: Struct (VI)
In this article, we will explore how to approach the implementation of a common structural code base. The goal is to reduce the programming workload and leverage the full potential of the programming language itself—in this case, MQL5.
From Basic to Intermediate: Struct (IV)
From Basic to Intermediate: Struct (IV)
In this article, we will explore how to create so-called structural code, where the entire context and methods for manipulating variables and information are placed within a structure to create a suitable context for implementing any code. Therefore, we will examine the necessity of using a private section of the code to separate what is public from what is not, thereby adhering to the rule of encapsulation and preserving the context for which the data structure was created.
Market Simulation (Part 14): Sockets (VIII)
Market Simulation (Part 14): Sockets (VIII)
Many programmers might assume we should abandon using Excel and move directly to Python, using some packages that allow Python to generate an Excel file for later analysis of results. However, as mentioned in the previous article, although this solution is the simplest for many programmers, it will not be accepted by some users. And in this particular case, the user is always right. As programmers, we must find a way to make everything work.
Developing A Custom Account Performance Matrix Indicator
Developing A Custom Account Performance Matrix Indicator
This indicator acts as a discipline enforcer by tracking account equity, profit/loss, and drawdown in real-time while displaying a performance dashboard. It can help traders stay consistent, avoid overtrading, and comply with prop-firm challenge rules.
MQL5 Trading Tools (Part 19): Building an Interactive Tools Palette for Chart Drawing
MQL5 Trading Tools (Part 19): Building an Interactive Tools Palette for Chart Drawing
In this article, we build an interactive tools palette in MQL5 for chart drawing, with draggable, resizable panels and theme switching. We add buttons for tools like crosshair, trendlines, lines, rectangles, Fibonacci, text, and arrows, handling mouse events for activation and instructions. This system improves trading analysis through a customizable UI, supporting real-time interactions on charts
Using the MQL5 Economic Calendar for News Filtering (Part 1): Implementing Pre- and Post-News Windows in MQL5
Using the MQL5 Economic Calendar for News Filtering (Part 1): Implementing Pre- and Post-News Windows in MQL5
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.
Creating Custom Indicators in MQL5 (Part 8): Adding Volume Integration for Deeper Market Profile Analysis
Creating Custom Indicators in MQL5 (Part 8): Adding Volume Integration for Deeper Market Profile Analysis
In this article, we enhance the hybrid Time Price Opportunity (TPO) market profile indicator in MQL5 by integrating volume data to calculate volume-based point of control, value areas, and volume-weighted average price with customizable highlighting options. The system introduces advanced features like initial balance detection, key level extension lines, split profiles, and alternative TPO characters such as squares or circles for improved visual analysis across multiple timeframes.
From Novice to Expert: Automating Intraday Strategies
From Novice to Expert: Automating Intraday Strategies
We translate the EMA‑50 retest idea into a behavior‑driven Expert Advisor for intraday trading. The study formalizes trend bias, EMA interaction (pierce and close), reaction confirmation, and optional filters, then implements them in MQL5 with modular functions and resource‑safe handles. Visual testing in the Strategy Tester verifies signal correctness. The result is a clear template for coding discretionary bounces.
MetaTrader 5 Machine Learning Blueprint (Part 6): Engineering a Production-Grade Caching System
MetaTrader 5 Machine Learning Blueprint (Part 6): Engineering a Production-Grade Caching System
Tired of watching progress bars instead of testing trading strategies? Traditional caching fails financial ML, leaving you with lost computations and frustrating restarts. We've engineered a sophisticated caching architecture that understands the unique challenges of financial data—temporal dependencies, complex data structures, and the constant threat of look-ahead bias. Our three-layer system delivers dramatic speed improvements while automatically invalidating stale results and preventing costly data leaks. Stop waiting for computations and start iterating at the pace the markets demand.
MQL5 Trading Tools (Part 20): Canvas Graphing with Statistical Correlation and Regression Analysis
MQL5 Trading Tools (Part 20): Canvas Graphing with Statistical Correlation and Regression Analysis
In this article, we create a canvas-based graphing tool in MQL5 for statistical correlation and linear regression analysis between two symbols, with draggable and resizable features. We incorporate ALGLIB for regression calculations, dynamic tick labels, data points, and a stats panel displaying slope, intercept, correlation, and R-squared. This interactive visualization aids in pair trading insights, supporting customizable themes, borders, and real-time updates on new bars
From Novice to Expert: Extending a Liquidity Strategy with Trend Filters
From Novice to Expert: Extending a Liquidity Strategy with Trend Filters
The article extends a liquidity-based strategy with a simple trend constraint: trade liquidity zones only in the direction of the EMA(50). It explains filtering rules, presents a reusable TrendFilter.mqh class and EA integration in MQL5, and compares baseline versus filtered tests. Readers gain a clear directional bias, reduced overtrading in countertrend phases, and ready-to-use source files.
Larry Williams Market Secrets (Part 12): Context Based Trading of Smash Day Reversals
Larry Williams Market Secrets (Part 12): Context Based Trading of Smash Day Reversals
This article shows how to automate Larry Williams Smash Day reversal patterns in MQL5 within a structured context. We implement an Expert Advisor that validates setups over a limited window, aligns entries with Supertrend-based trend direction and day-of-week filters, and supports entry on level cross or bar close. The code enforces one position at a time and risk-based or fixed sizing. Step-by-step development, backtesting procedure, and reproducible settings are provided.
Overcoming Accessibility Problems in MQL5 Trading Tools (Part I): How to Add Contextual Voice Alerts in MQL5 Indicators
Overcoming Accessibility Problems in MQL5 Trading Tools (Part I): How to Add Contextual Voice Alerts in MQL5 Indicators
This article explores an accessibility-focused enhancement that goes beyond default terminal alerts by leveraging MQL5 resource management to deliver contextual voice feedback. Instead of generic tones, the indicator communicates what has occurred and why, allowing traders to understand market events without relying solely on visual observation. This approach is especially valuable for visually impaired traders, but it also benefits busy or multitasking users who prefer hands-free interaction.
Introduction to MQL5 (Part 42): Beginner Guide to File Handling in MQL5 (IV)
Introduction to MQL5 (Part 42): Beginner Guide to File Handling in MQL5 (IV)
This article shows how to build an MQL5 indicator that reads a CSV trading history, extracts Profit($) values and total trades, and computes a cumulative balance progression. We plot the curve in a separate indicator window, auto-scale the Y-axis, and draw horizontal and vertical axes for alignment. The indicator updates on a timer and redraws only when new trades appear. Optional labels display per-trade profit and loss to help assess performance and drawdowns directly on the chart.
Price Action Analysis Toolkit Development (Part 62): Building an Adaptive Parallel Channel Detection and Breakout System in MQL5
Price Action Analysis Toolkit Development (Part 62): Building an Adaptive Parallel Channel Detection and Breakout System in MQL5
This article presents an adaptive parallel channel detection and breakout system in MQL5. It explains how swing points are identified, channels are constructed and dynamically recalculated, and breakouts are confirmed and visualized with persistent signals. The framework integrates trendline geometry, ATR-based filtering, and retest validation to provide reliable, real-time price action analysis for professional charting and trading decisions.
Swing Extremes and Pullbacks in MQL5 (Part 1): Developing a Multi-Timeframe Indicator
Swing Extremes and Pullbacks in MQL5 (Part 1): Developing a Multi-Timeframe Indicator
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.
MQL5 Trading Tools (Part 21): Adding Cyberpunk Theme to Regression Graphs
MQL5 Trading Tools (Part 21): Adding Cyberpunk Theme to Regression Graphs
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.
Developing a Trading Strategy: The Butterfly Oscillator Method
Developing a Trading Strategy: The Butterfly Oscillator Method
In this article, we demonstrated how the fascinating mathematical concept of the Butterfly Curve can be transformed into a practical trading tool. We constructed the Butterfly Oscillator and built a foundational trading strategy around it. The strategy effectively combines the oscillator's unique cyclical signals with traditional trend confirmation from moving averages, creating a systematic approach for identifying potential market entries.
Markets Positioning Codex in MQL5 (Part 1): Bitwise Learning for Nvidia
Markets Positioning Codex in MQL5 (Part 1): Bitwise Learning for Nvidia
We commence a new article series that builds upon our earlier efforts laid out in the MQL5 Wizard series, by taking them further as we step up our approach to systematic trading and strategy testing. Within these new series, we’ll concentrate our focus on Expert Advisors that are coded to hold only a single type of position - primarily longs. Focusing on just one market trend can simplify analysis, lessen strategy complexity and expose some key insights, especially when dealing in assets beyond forex. Our series, therefore, will investigate if this is effective in equities and other non-forex assets, where long only systems usually correlate well with smart money or institution strategies.
Reimagining Classic Strategies (Part 17): Modelling Technical Indicators
Reimagining Classic Strategies (Part 17): Modelling Technical Indicators
In this discussion, we focus on how we can break the glass ceiling imposed by classical machine learning techniques in finance. It appears that the greatest limitation to the value we can extract from statistical models does not lie in the models themselves — neither in the data nor in the complexity of the algorithms — but rather in the methodology we use to apply them. In other words, the true bottleneck may be how we employ the model, not the model’s intrinsic capability.
The MQL5 Standard Library Explorer (Part 3): Expert Standard Deviation Channel
The MQL5 Standard Library Explorer (Part 3): Expert Standard Deviation Channel
In this discussion, we will develop an Expert Advisor using the CTrade and CChartObjectStdDevChannel classes, while applying several filters to enhance profitability. This stage puts our previous discussion into practical application. Additionally, I’ll introduce another simple approach to help you better understand the MQL5 Standard Library and its underlying codebase. Join the discussion to explore these concepts in action.
Overcoming Accessibility Challenges in MQL5 Trading Tools (Part II): Enabling EA Voice Using a Python Text-to-Speech Engine
Overcoming Accessibility Challenges in MQL5 Trading Tools (Part II): Enabling EA Voice Using a Python Text-to-Speech Engine
Let's discuss how we can make our Expert Advisors speech‑capable using text‑to‑speech technology, partnering Python and MQL5. After reading this article, you will walk away with a working example of an EA that speaks dynamic market information. You will master the application of TTS, the WebRequest function, and learn how Python libraries integrate with the MQL5 language to create a truly voice‑aware trading tool.
Price Action Analysis Toolkit Development (Part 63): Automating Rising and Falling Wedge Detection in MQL5
Price Action Analysis Toolkit Development (Part 63): Automating Rising and Falling Wedge Detection in MQL5
In this part of the Price Action Analysis Toolkit Development series, we develop an MQL5 indicator that automatically detects rising and falling wedge patterns in real time. The system confirms pivot structures, validates boundary convergence mathematically, prevents overlapping formations, and monitors breakout and failure conditions with precise visual feedback. Built using a clean object-oriented architecture, this implementation converts subjective wedge recognition into a structured, state-aware analytical component designed to strengthen disciplined price action analysis.
Larry Williams Market Secrets (Part 13): Automating Hidden Smash Day Reversal Patterns
Larry Williams Market Secrets (Part 13): Automating Hidden Smash Day Reversal Patterns
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.