White Noise

17 Ogo 2023

The "White Noise" indicator is designed to visualize the dispersion of price movements around a moving average, providing insights into market noise and potential trend changes. It highlights periods of increased volatility or noise compared to the underlying trend.

Code Explanation:
Inputs:

mlen: Input for the length of the noise calculation.
hlen: Input for the length of the Hull moving average.
col_up: Input for the color of the up movement.
col_dn: Input for the color of the down movement.

Calculations:

ma: Calculate the simple moving average of the high, low, and close prices (hlc3) over the specified mlen period.
dist: Calculate the percentage distance between the hlc3 and the moving average ma, then scale it by 850. This quantifies the deviation from the moving average as a value.
sm: Smooth the calculated dist values using a weighted moving average (WMA) twice, with different weights, and subtract one from the other. This provides a smoothed representation of the dispersion.
Coloring:

col_wn: Determine the color of the bars based on whether dist is positive or negative and whether it's greater or less than the smoothed sm value. This creates color-coded columns indicating upward or downward movements with varying opacity.
col_switch: Define the color for the current trend state. It switches color when the smoothed sm crosses above or below its previous value, indicating potential trend changes.
col_switch2: Define the color for the horizontal line that separates the two trend states. It switches color based on the same crossover and crossunder conditions as col_switch.

Plots:

plot(dist): Plot the dispersion values as columns with color defined by col_wn.
plot(sm): Plot the smoothed dispersion line with a white color and thicker linewidth.
plot(sm[1]): Plot the previous smoothed dispersion value with a lighter white color to create a visual distinction.
Usage:

This indicator can help traders identify periods of increased market noise, visualize potential trend reversals, and assess the strength of price movements around the moving average. The colored columns and smoothed line offer insights into the ebb and flow of market sentiment, aiding in decision-making.


ps. This can be used as a long-term TPI component if you dabble in Modern Portfolio Theory (MPT)

Recommended for timeframes on the 1D or above:

20 Sep 2023

Nota Keluaran

Updated to work on more timeframes, more sources and added normalization.

Normalization is great if you want to find more details regarding another system:

Above is a case where you use the EMA (Which is a smooth average of the direction (trend))

Below is the case for RSI:

Notice that it is normalized when using mean reversion systems! In the case when using mean reversion systems as a source, The White Noise Indicator becomes a mean reverting system!