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Building an EquiVolume Indicator in MQL5

Building an EquiVolume Indicator in MQL5

This article shows how to build an EquiVolume indicator in MQL5. It transforms traditional candles into volume‑weighted boxes whose width depends on relative trading activity within a lookback period. We will implement a step-by-step process that identifies maximum volume, normalizes all other volumes against it, and converts them into proportional visual widths for each candle. The result can be used to analyze market strength, highlight high-participation zones, and improve price action interpretation for both manual trading and algorithmic strategy development.
Building an EquiVolume Indicator in MQL5
Building an EquiVolume Indicator in MQL5
  • 2026.05.31
  • www.mql5.com
We implement an EquiVolume indicator in MQL5 that converts standard candlesticks into volume-weighted boxes. The workflow includes selecting volume type, detecting the maximum volume within a lookback range, normalizing all values against it, and mapping them into proportional box widths. The result is a chart-based structure that visualizes trading activity intensity alongside price movement in MetaTrader 5.
 

Encoding Candlestick Patterns (Part 3): Frequency Analysis for Single Candlestick Type Structure

Encoding Candlestick Patterns (Part 3): Frequency Analysis for Single Candlestick Type Structure

Frequency analysis is widely used in many disciplines, including linguistics, genetics, and data science, to identify dominant structures within large datasets. Applying the same principle to encoded candlestick data allows us to determine which market structures occur most frequently, which are relatively rare, and whether certain combinations exhibit recurring behavior that may warrant further investigation.

Encoding Candlestick Patterns (Part 3): Frequency Analysis for Single Candlestick Type Structure
Encoding Candlestick Patterns (Part 3): Frequency Analysis for Single Candlestick Type Structure
  • 2026.06.24
  • www.mql5.com
This article introduces a frequency-analysis framework for encoded candlestick patterns in MQL5. By transforming candlesticks into alphabetic symbols, historical price action can be analyzed as a statistical sequence rather than a visual chart. Using GBPUSD and Gold across multiple timeframes, the study examines the occurrence frequency of individual candlestick types, identifies dominant market structures, and reveals the symmetry between bullish and bearish price movements. The results establish a quantitative foundation for pattern discovery and prepare the way for analyzing multi-candlestick sequences and their predictive potential in algorithmic trading systems.