Volatility-Normalized Multi-Scale Trend Channels and Breakout States
Summary
This indicator builds trend channels from OHLC data using a volatility-normalized coordinate system. It estimates volatility with the Yang-Zhang method, groups price history into blocks, and represents each block by the geometric midpoint of its high and low. The longest monotonic sequence of block values supplies a direction and normalized angle; a threshold distinguishes trends from ranges. Channel boundaries are fitted from price extremes within that segment.
The process runs across six scales, with one primary scale driving a state machine for channel breakouts, retests, failed breaks, and gap crossings. A dashboard displays scale-by-scale direction, agreement, channel levels, and breakout context. The indicator offers live-bar and closed-bar calculation modes: live values can change during a bar, while closed-bar calculations anchor structural logic to the prior bar. It describes a method and visual tool, not a trading system with tested returns. Its thresholds, scale choices, and fitted channels remain design choices requiring independent evaluation.
Key ideas
- Yang-Zhang volatility normalizes log-price slopes so trend angles can be compared across instruments and volatility regimes.
- Block geometric means reduce price history to central values before monotonic trend segments are identified.
- Channel boundaries are fitted from price extremes within the detected segment.
- Six independently calculated scales provide trend-direction agreement, while the primary scale tracks breakout and retest states.
- Closed-bar mode bases structural calculations on the previous bar; live-bar mode can repaint as prices change.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.