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Nadaraya-Watson Regression Liquidity Sweeps
Free TradingView Indicator by AlgoAlpha — Smart Money & Liquidity
This script combines Nadaraya-Watson regression, momentum analysis, and liquidity level tracking into a single workflow. It measures the slope of a smoothed price regression curve, converts that slope into a normalized oscillator, and uses momentum shifts to identify areas where liquidity may be resting.
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2026-05-29published
What is Nadaraya-Watson Regression Liquidity Sweeps?
This script combines Nadaraya-Watson regression, momentum analysis, and liquidity level tracking into a single workflow. It measures the slope of a smoothed price regression curve, converts that slope into a normalized oscillator, and uses momentum shifts to identify areas where liquidity may be resting.
The oscillator is built from the rate of change of the Nadaraya-Watson estimate rather than price itself. This allows momentum transitions to be measured relative to the underlying regression trend. When momentum weakens after an extended move, the script records swing-based liquidity levels that can later be swept by price.
A volatility-adjusted Nadaraya-Watson band is also displayed on the chart. This provides context for trend direction, momentum strength, and potential rebound conditions around the regression value.
Nadaraya-Watson Regression Liquidity Sweeps Features
Normalized Nadaraya-Watson Oscillator
Measures momentum using the slope of a smoothed regression curve.
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Liquidity Sweep Detection
Creates liquidity levels when bullish or bearish momentum begins to weaken.
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Volatility-Adjusted Regression Band
Displays a dynamic overlay around the Nadaraya-Watson estimate using smoothed ATR values.
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Momentum Weakening Signals
Marks locations where oscillator momentum begins to lose strength against the current directional bias.
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Rebound Signals
Highlights situations where price reclaims or loses the regression value while momentum remains aligned with trend direction.
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How Nadaraya-Watson Regression Liquidity Sweeps Works
• Nadaraya-Watson Regression — A kernel-based smoothing method that estimates an underlying price curve by weighting nearby historical data more heavily than distant data.
• Normalized Regression Slope — The change in the Nadaraya-Watson estimate divided by its recent standard deviation, allowing momentum strength to be compared across different market conditions.
• Liquidity Sweep Level — A horizontal level created from a swing high or swing low when momentum begins to weaken, representing an area that may later attract price.
• Oscillator Signal Line — An EMA of the normalized oscillator used to identify momentum crossovers and momentum phase changes.
• Rebound Condition — A signal generated when price moves back through the Nadaraya-Watson value while oscillator direction remains aligned with the prevailing momentum bias.
How to Use Nadaraya-Watson Regression Liquidity Sweeps
• Monitor the oscillator relative to its signal line to identify momentum shifts and changes in directional bias.
• Watch for newly created liquidity levels after momentum weakening events, as these levels may become future sweep targets.
• Use sweeps of upper or lower liquidity levels to identify areas where price has taken resting liquidity.
• Look for bullish rebound signals when price reclaims the regression value while bullish momentum remains active.
• Look for bearish rebound signals when price loses the regression value while bearish momentum remains active.
• Combine oscillator direction, liquidity levels, and regression band structure to build context around trend continuation or reversal scenarios.
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