Friction Heatmap & Vacuum Zones [ZOM]
Markets do not move through price evenly.
Some areas act like very dense with heavy resistance, while others like low-friction vacuum zones where price can accelerate rapidly.
This indicator models those regions using time-weighted volume interaction density to estimate market friction and visualize traversable paths.
Features:
• Time-decay weighted friction calculations
• Volume-adjusted heatmap
• Vacuum zone detection
• Friction-adjusted risk/reward engine
• ATR-based targeting
• Dynamic path efficiency dashboard
• Multiple heatmap visualization modes
It is simple:
High-friction zones may slow or reject price.
Low-friction zones may allow price to move quickly.
The script attempts to visualize those areas using historical interaction density and volume distribution. TradingView does not provide true order book or full market depth data to Pine scripts. So, because of this, the friction modeling is estimated using historical price interaction and volume distribution rather than direct liquidity data. Therefore, this tool should be viewed as a contextual framework rather than a predictive system!
Some areas act like very dense with heavy resistance, while others like low-friction vacuum zones where price can accelerate rapidly.
This indicator models those regions using time-weighted volume interaction density to estimate market friction and visualize traversable paths.
Features:
• Time-decay weighted friction calculations
• Volume-adjusted heatmap
• Vacuum zone detection
• Friction-adjusted risk/reward engine
• ATR-based targeting
• Dynamic path efficiency dashboard
• Multiple heatmap visualization modes
It is simple:
High-friction zones may slow or reject price.
Low-friction zones may allow price to move quickly.
The script attempts to visualize those areas using historical interaction density and volume distribution. TradingView does not provide true order book or full market depth data to Pine scripts. So, because of this, the friction modeling is estimated using historical price interaction and volume distribution rather than direct liquidity data. Therefore, this tool should be viewed as a contextual framework rather than a predictive system!
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