Extracting Fibonacci, Channel, and Pitchfork Data from MQL5 Chart Objects
Summary
This article explains how an MQL5 detector can collect structured data from complex chart objects for use in rule-based trading systems. It covers Fibonacci retracements, fans, arcs, and time zones, along with equidistant channels and Andrews pitchforks. The descriptions outline the anchor points and geometric relationships used to calculate levels, boundaries, slopes, and median lines; an extended data structure is intended to make those values available to an Expert Advisor.
The trading discussion treats retracement levels and channel or pitchfork lines as possible support, resistance, entry, or alert references, and gives example rules such as acting near a retracement or channel boundary. The article also describes periodic object detection and suggests responding to chart events for updates. These are implementation and technical-analysis concepts, not evidence of predictive value: the document provides no controlled performance test for Fibonacci or pitchfork hypotheses, and chart scaling affects the geometry of arcs. The cited behavioral claims should be independently evaluated.
Key ideas
- Fibonacci retracements use two price anchors to calculate ratio-based levels along a prior move.
- Fans, arcs, and time zones extend Fibonacci analysis into angled, curved, and temporal projections.
- An equidistant channel uses two points for its trendline and a third point to set parallel channel width.
- An Andrews pitchfork uses three pivots to define a median line and parallel boundaries.
- Structured extraction makes chart-object levels and geometry available to automated rules, but does not establish their predictive value.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.