Anchored Value Distribution Oscillator (Zeiierman)█ Overview
Anchored Value Distribution Oscillator (Zeiierman) is a structure-driven oscillator that models price as a dynamic value distribution, then measures where price is positioned within that structure to reveal balance, imbalance, and shifting market conditions.
Instead of relying purely on price momentum, the indicator builds a rolling, volume-weighted distribution of price over time. From this structure, it extracts key reference levels such as the value center, high/low distribution bands, and peak activity zones. These are then used to normalize the price into a bounded oscillator.
Alongside the distribution, the script constructs an adaptive trailing anchor that reacts to structural shifts and volatility. The oscillator combines both the structural distribution and the adaptive anchor into a single positioning score, producing a contextual view of trend, extension, and balance.
The result is an oscillator that reflects not just direction, but where price sits within its evolving value landscape.
█ How It Works
⚪ Distribution Engine (Value Model)
The core of the indicator is a rolling value distribution built from price and volume.
Each bar contributes to a log-scaled price histogram, where:
price ranges are segmented into rows
volume is distributed across those rows
candle bodies and wicks are weighted differently
older data gradually decays over time
This produces a continuously updating view of:
Point of Control (vp)
Value High / Value Low (vh / vl)
Outer extremes (xh / xl)
Distribution center (cen)
Unlike a static volume profile, this model evolves with the market and adapts to both recent and historical activity.
⚪ Adaptive Anchor (Trend Engine)
On top of the distribution, the script builds an adaptive trend anchor (anc).
The anchor is derived from a structural base:
blended from the distribution center and peak activity
offset using volatility (ATR)
constrained to trail price in the active direction
The anchor flips direction when the price crosses it, and then trails using a volatility-adjusted distance.
This creates a structure-aware trend model that behaves similarly to a trailing stop, but is grounded in value distribution rather than raw price movement.
⚪ Normalized Positioning Model
The oscillator converts price into a normalized position within the distribution.
Two independent scores are calculated:
Position relative to the adaptive anchor (scAnc)
Position relative to the value distribution (scVp)
Each score maps price into a bounded range:
-50 → extreme downside
-25 - 20 → fair value
+50 → extreme upside
These scores are then combined into a single output using a weighted blend.
A confidence factor reduces the distribution score's contribution when it disagrees with the anchor, ensuring cleaner signals in conflicting conditions.
⚪ Smoothed Oscillator Output
The final oscillator (outAvg) is a smoothed combination of:
trend-aware positioning (anchor)
structure-aware positioning (distribution)
█ How to Use
⚪ Read Position Relative to Value
Use the oscillator to understand where the price sits within its value distribution:
Above 25 → price is positioned above fair value
Below -25 → price is positioned below fair value
Near extremes (±50) → price is extended relative to structure
This helps distinguish between:
continuation conditions
mean reversion zones
balanced market states
⚪ Follow the Adaptive Trend Anchor
The trailing anchor provides a clear trend reference:
Price above anchor → bullish regime
Price below anchor → bearish regime
Anchor flips → potential regime shift
█ Settings
Lookback – Controls how much historical data is used to build the value distribution. Higher values produce smoother structure, while lower values increase responsiveness.
Canvas Pad – Expands the distribution range to include more extreme price levels. Increasing this captures broader moves but reduces precision.
Rebuild Drift – Determines how much the distribution can drift before being recalculated. Lower values rebuild more frequently, higher values allow more continuity.
Signal Length – Controls the smoothing of the signal line. Higher values reduce noise but increase lag.
Profile Center Bias – Blends between the value distribution center and the point of control to define the structural base. Higher values anchor the trail to the broader distribution center, while lower values make it follow peak activity more closely.
Trail Acceleration – Controls how quickly the trailing stop tightens as the price accelerates. Higher values make the trail react more aggressively to impulsive moves, reducing lag during strong trends.
Max Trail Acceleration – Limits how much the acceleration can compress the trailing distance. Higher values allow the stop to tighten more during rapid expansion, while lower values keep behavior closer to the original, smoother trail.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
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