AI SuperTrend Clustering Oscillator Download for MT5 – Free

The design of AI SuperTrend Clustering Oscillator is based on the following combination: SuperTrend logic and statistical K-Means clustering method.
The tool analyzes the difference between the current price and multiple calculated SuperTrend values, dividing the data into three main groups: Bullish, Bearish and Consensus clusters.
The results of this process are displayed as colored bands within the oscillator for quick identification of market conditions.

AI SuperTrend cluster oscillator specification sheet

The following table shows the specifications of the AI ​​SuperTrend Clustering Oscillator:

AI SuperTrend cluster oscillator overview

In the lower half of the diagram, the AI ​​SuperTrend Clustering Oscillator generates three different outputs, as shown below:

• Consensus Output: The central gray line represents the consensus of the indicator and the main market direction;
• Bullish Output: The oscillation line moves upward above the midline, forming a blue area;
• Bearish Output: The oscillator line moves below the midline, expanding the red area.

Bullish Trend

According to the 1-hour chart of Silver/USD (XAG/USD), when the oscillator crosses above the midline, a blue zone forms, indicating the start of a strong bullish trend.
As this situation remains stable, the candlesticks accelerate and the upward movement pattern is confirmed on the main chart.

Bearish Trend

Based on the Bitcoin (BTC) 30-minute chart cryptocurrency , when the oscillator line moves below the midline and forms a wide red zone below, it signals the beginning of a strong bearish trend.
Following this signal, candles closed lower continuously and selling pressure intensified in the market structure.

AI SuperTrend clustering oscillator settings

The customizable parameters of AI SuperTrend Clustering Oscillator are as follows:

• 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

AI SuperTrend Clustering Oscillator is built on the following combination: SuperTrend methodology and K-Means clustering algorithm to more accurately depict market trends through multi-dimensional price data analysis.
Using the Average True Range (ATR) to measure volatility, it dynamically rescales bullish and bearish areas accordingly.
As a result, this oscillator provides greater accuracy in identifying rapid trend reversals, short-term corrections, and potential price reversal areas compared to traditional SuperTrend versions.