Kalman Volume Filter [ChartPrime]

The "Kalman Volume Filter", aims to provide insights into market volume dynamics by filtering out noise and identifying potential overbought or oversold conditions. Let's break down its components and functionality:

Settings:

• Users can adjust various parameters to customize the indicator according to their preferences:
  
• Volume Length: Defines the length of the volume period used in calculations.
  
• Stabilization Coefficient (k): Determines the level of noise reduction in the signals.
  
• Signal Line Length: Sets the length of the signal line used for identifying trends.
  
• Overbought & Oversold Zone Level: Specifies the threshold levels for identifying overbought and oversold conditions.
  
• Source: Allows users to select the price source for volume calculations.
  

Volume Zone Oscillator (VZO):

• Calculates a volume-based oscillator indicating the direction and intensity of volume movements.
  
• Utilizes a volume direction measurement over a specified period to compute the oscillator value.
  
• Normalizes the oscillator value to improve comparability across different securities or timeframes.
  

// VOLUME ZONE OSCILLATOR
VZO(get_src, length) =>
    Volume_Direction    = get_src > get_src[2] ? volume : -volume
    VZO_volume          = ta.hma(Volume_Direction, length)
    Total_volume        = ta.hma(volume, length)
    VZO  = VZO_volume / (Total_volume)
    VZO := (VZO - 0) / ta.stdev(VZO, 200)
    VZO

Kalman Filter:

• Applies a Kalman filter to smooth out the VZO values and reduce noise.
  
• Utilizes a stabilization coefficient (k) to control the degree of smoothing.
  
• Generates a filtered output representing the underlying volume trend.
  

// KALMAN FILTER
series float M_n     = 0.0                           //   - the resulting value of the current calculation
series float A_n     = VZO                       //   - the initial value of the current measurement
series float M_n_1   = nz(M_n[1])            //   - the resulting value of the previous calculation
float k              = input.float(0.06)  //  - stabilization coefficient

// Kalman Filter Formula
kalm(k)=>
    k * A_n + (1 - k) * M_n_1

Volume Visualization:

• Displays the volume histogram, with color intensity indicating the strength of volume movements.
  
• Adjusts bar colors based on volume bursts to highlight significant changes in volume.
  

Overbought and Oversold Zones:
Marks overbought and oversold levels on the chart to assist in identifying potential reversal points.


Plotting:

• Plots the Kalman Volume Filter line and a signal line for visual analysis.
  
• Utilizes different colors and fills to distinguish between rising and falling trends.
  
• Highlights specific events such as local buy or sell signals, as well as overbought or oversold conditions.
  

This indicator provides traders with a comprehensive view of volume dynamics, trend direction, and potential market turning points, aiding in informed decision-making during trading activities.