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Larry Williams Market Secrets (Part 11): Detecting Smash Day Reversals with a Custom Indicator
Larry Williams Market Secrets (Part 11): Detecting Smash Day Reversals with a Custom Indicator
We convert Larry Williams’ Smash Day reversal rules into a practical MQL5 indicator that flags confirmed setups with arrows. Step by step, the text shows buffer binding, plot properties, historical mapping, and real‑time updates inside OnCalculate. Adjustable lookback parameters and clean chart rendering help you detect valid reversals quickly while keeping final trade decisions discretionary and context‑driven.
Price Action Analysis Toolkit Development (Part 21): Market Structure Flip Detector Tool
Price Action Analysis Toolkit Development (Part 21): Market Structure Flip Detector Tool
The Market Structure Flip Detector Expert Advisor (EA) acts as your vigilant partner, constantly observing shifts in market sentiment. By utilizing Average True Range (ATR)-based thresholds, it effectively detects structure flips and labels each Higher Low and Lower High with clear indicators. Thanks to MQL5’s swift execution and flexible API, this tool offers real-time analysis that adjusts the display for optimal readability and provides a live dashboard to monitor flip counts and timings. Furthermore, customizable sound and push notifications guarantee that you stay informed of critical signals, allowing you to see how straightforward inputs and helper routines can transform price movements into actionable strategies.
Automating Market Memory Zones Indicator: Where Price is Likely to Return
Automating Market Memory Zones Indicator: Where Price is Likely to Return
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.
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
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.
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.
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 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.
Package-based approach with KnitPkg for MQL5 development
Package-based approach with KnitPkg for MQL5 development
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.
Engineering Trading Discipline into Code (Part 3): Enforcing Symbol-Level Trading Boundaries with a Whitelist System in MQL5
Engineering Trading Discipline into Code (Part 3): Enforcing Symbol-Level Trading Boundaries with a Whitelist System in MQL5
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.
Creating Custom Indicators in MQL5 (Part 9): Order Flow Footprint Chart with Price Level Volume Tracking
Creating Custom Indicators in MQL5 (Part 9): Order Flow Footprint Chart with Price Level Volume Tracking
This article builds an order-flow footprint indicator in MQL5 that aggregates tick-by-tick volume into quantized price levels and supports Bid vs Ask and Delta display modes. A canvas overlay renders color-scaled volume text aligned with the candles and updates on every tick. You will learn sorting of price levels, max-value normalization for color mapping, and responsive redraws on zoom, scroll, and resize to read volume distribution and aggressor dominance inside each bar.
Creating Custom Indicators in MQL5 (Part 10): Enhancing the Footprint Chart with Per-Bar Volume Sentiment Information Box
Creating Custom Indicators in MQL5 (Part 10): Enhancing the Footprint Chart with Per-Bar Volume Sentiment Information Box
The article enhances an MQL5 footprint indicator with a compact box above each candle that summarizes net delta, total volume, and buy/sell percentages. We implement supersampled anti‑aliased rendering, rounded corners via arc and quadrilateral rasterization, and per‑pixel alpha compositing. Supporting utilities include ARGB conversion, scanline fills, and box‑filter downsampling. The box delivers fast sentiment reads that stay legible across zoom levels.
From Novice to Expert: Adaptive Risk Management for Liquidity Strategies
From Novice to Expert: Adaptive Risk Management for Liquidity Strategies
In this article, we explore practical and robust risk management techniques specifically tailored for liquidity-based trading. You will learn how to protect positions during retests, handle false breakouts with confidence, and identify signs of potential level manipulation. By the end, you will have built an adaptive Expert Advisor capable of managing zone flips and executing strategic pending orders with integrated risk control.
Trend Criteria. Conclusion
Trend Criteria. Conclusion
In this article, we will consider the specifics of applying some trend criteria in practice. We will also try to develop several new criteria. The focus will be on the efficiency of applying these criteria to market data analysis and trading.
Creating Custom Indicators in MQL5 (Part 11): Enhancing the Footprint Chart with Market Structure and Order Flow Layers
Creating Custom Indicators in MQL5 (Part 11): Enhancing the Footprint Chart with Market Structure and Order Flow Layers
This article extends the MQL5 footprint chart with market-structure and order-flow layers: volume-profile bars, point of control, value-area highlighting, stacked imbalance detection, absorption zones, and single-print/unfinished markers. We expand bar data structures, add functions for POC/value area, imbalance, and absorption, and build a fixed-order rendering pipeline. You will get ready-to-use inputs, metadata, and drawing utilities to integrate and customize these layers in your indicator.
Building a Volume Bubble Indicator in MQL5 Using Standard Deviation
Building a Volume Bubble Indicator in MQL5 Using Standard Deviation
The article demonstrates how to build a Volume Bubble Indicator in MQL5 that visualizes market activity using statistical normalization. It covers how to work with tick and real volume, compute the mean and standard deviation over a rolling window, and normalize volume values to identify relative strength. You will implement chart objects to display bubbles with dynamic size and color, providing a clear representation of volume intensity directly on the chart.