AI SuperTrend Clustering Oscillator Download for MT4 – Free

AI SuperTrend Clustering Oscillator is based on K-Means clustering algorithm and SuperTrend logic.
The indicator calculates the deviation between price and multiple SuperTrend changes, grouping the data into three statistical clusters: Bullish, Bearish, and Consensus.
The output of each cluster is shown as a colored area within the oscillator.

AI SuperTrend cluster oscillator specification sheet

The specifications of AI SuperTrend Clustering Oscillator are as follows.

AI SuperTrend cluster oscillator overview

In the lower half of the chart, the AI ​​SuperTrend Clustering Oscillator produces three types of output that help identify current trends, movement strength, and potential price reversals:

• Consensus Output: The central gray line defines the overall market direction;
• Bullish Output: The oscillating line passes upward above the midline, forming a blue area and point;
• Bearish Output: The line below the center line oscillates with the appearance of red areas and dots.

Bullish Trend

According to the USD/CHF 1-hour chart, once the oscillator crosses above the midline, a blue zone forms, indicating the beginning of a stable bullish trend.
As this situation stabilizes, the candlesticks gain momentum and bullish movement structures appear on the main chart.

Bearish Trend

According to the Dogecoin (DOGE) 30-minute chart of the cryptocurrency , the movement of the oscillator line below the midline and the expansion of the red area at the bottom indicate the formation of a bearish trend.
After this shift, the candles closed lower continuously and selling pressure increased in the price structure.

AI SuperTrend clustering oscillator settings

The settings panel of AI SuperTrend Clustering Oscillator contains the following parameters:

• ATR Length: The number of periods used to calculate the average true fluctuation range;
• Minimum coefficient range: The minimum coefficient value used to calculate the super trend line.
• Maximum coefficient range: The maximum coefficient value used to determine the super trend range.
• Step: Incremental step size between the minimum and maximum factors.
• Smooth: The degree of smoothness applied to the indicator output to reduce signal noise.
• Maximum number of iteration steps: the maximum number of iterations of the clustering algorithm to find cluster centers.
• Historical bars calculation: The number of historical candlesticks used in the indicator calculation.
• Bullish Trend Color: Specify the color used to display bullish areas.
• Bearish Trend Color: Specify the color used to display bearish areas.

Conclusion

The AI ​​SuperTrend Clustering Oscillator combines SuperTrend's logic with the K-Means clustering algorithm to reveal the true structure of trends through multi-dimensional price action analysis.
By using Average True Range (ATR) data, it measures market volatility and dynamically adjusts bullish and bearish zones accordingly.
Therefore, unlike the classic SuperTrend version, this indicator can quickly detect trend reversals , correction phases and potential price reversal areas.