OPEN-SOURCE SCRIPT

Support/Resistance v2 (ML) Kmean

By Arivadis
Updated
Kmean with Standard Deviation Channel


1. Description of Kmean
Kmean (or K-means) is a popular clustering algorithm used to divide data into K groups based on their similarity. In the context of financial markets, Kmean can be applied to find the average price values over a specific period, allowing the identification of major trends and levels of support and resistance.

2. Application in Trading
In trading, Kmean is used to smooth out the price series and determine long-term trends. This helps traders make more informed decisions by avoiding noise and short-term fluctuations. Kmean can serve as a baseline around which other analytical tools, such as channels and bands, are constructed.

3. Description of Standard Deviation (stdev)
Standard deviation (stdev) is a statistical measure that indicates how much the values of data deviate from their mean value. In finance, standard deviation is often used to assess price volatility. A high standard deviation indicates strong price fluctuations, while a low standard deviation indicates stable movements.

4. Combining Kmean and Standard Deviation to Predict Short-Term Price Behavior
Combining Kmean and standard deviation creates a powerful tool for analyzing market conditions. Kmean shows the average price trend, while the standard deviation channels demonstrate the boundaries within which the price can fluctuate. This combination helps traders to:

  • Identify support and resistance levels.
  • Predict potential price reversals.
  • Assess risks and set stop-losses and take-profits.




Should you have any questions about code, please reach me at Tradingview directly.

Hope you find this script helpful!
Release Notes
Kmean with Standard Deviation Channel


1. Description of Kmean
Kmean (or K-means) is a popular clustering algorithm used to divide data into K groups based on their similarity. In the context of financial markets, Kmean can be applied to find the average price values over a specific period, allowing the identification of major trends and levels of support and resistance.

2. Application in Trading
In trading, Kmean is used to smooth out the price series and determine long-term trends. This helps traders make more informed decisions by avoiding noise and short-term fluctuations. Kmean can serve as a baseline around which other analytical tools, such as channels and bands, are constructed.

3. Description of Standard Deviation (stdev)
Standard deviation (stdev) is a statistical measure that indicates how much the values of data deviate from their mean value. In finance, standard deviation is often used to assess price volatility. A high standard deviation indicates strong price fluctuations, while a low standard deviation indicates stable movements.

4. Combining Kmean and Standard Deviation to Predict Short-Term Price Behavior
Combining Kmean and standard deviation creates a powerful tool for analyzing market conditions. Kmean shows the average price trend, while the standard deviation channels demonstrate the boundaries within which the price can fluctuate. This combination helps traders to:

Identify support and resistance levels.
Predict potential price reversals.
Assess risks and set stop-losses and take-profits.



Should you have any questions about code, please reach me at Tradingview directly.

Hope you find this script helpful!
Release Notes
Additional description:

In this case, we are looking for strong clusters where the midpoint is near the upper or lower point of the cluster. The colors are represented by a gradient and become more transparent as the midpoint moves farther from the upper or lower point.

Using shifted standard deviation (STDEV), we can determine when the price may touch the value that lies between two clusters or the midpoint, enabling us to trade channels or reversal patterns.
AIBands and ChannelschanneltrendkmeansStandard Deviation (Volatility)supportresistaceTrend AnalysisVolatility

Open-source script

In true TradingView spirit, the author of this script has published it open-source, so traders can understand and verify it. Cheers to the author! You may use it for free, but reuse of this code in publication is governed by House rules. You can favorite it to use it on a chart.

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