PROTECTED SOURCE SCRIPT
Heisenberg Uncertainty Moving Average (HUMA)
Overview
This script introduces and approximation of the Heisenberg Uncertainty Moving Average (HUMA), inspired by the principles of quantum physics, particularly the Heisenberg Uncertainty Principle. The indicator dynamically adjusts its moving average length based on price and momentum uncertainty, ensuring adaptability to market conditions. It also features dynamic coloring to indicate the slope of the moving average.
Step-by-Step Explanation
Calculate Uncertainty in Price (Δx):
The price uncertainty is measured over a specified lookback period (length).
This is done by finding the difference between the highest high and lowest low over the period
Momentum uncertainty is defined using the Rate of Change (ROC) of the closing price over the same lookback period (length).
This indicates how much the price has changed over that period, providing a measure of momentum uncertainty.
Introduce Planck’s Constant (h):
Planck’s constant (h) is scaled down for financial use to set a theoretical minimum threshold for the product of uncertainties.
The threshold is defined as h / (4 * π) to simulate a limit that aligns with the Heisenberg Uncertainty Principle in physics.
Calculate the Uncertainty Product (Δx ⋅ Δp):
The product of price uncertainty (Δx) and the absolute value of momentum uncertainty (Δp) is calculated.
To ensure the product respects the minimum threshold set by quantum principles, the value is capped using math.max(uncertainty_product, threshold).
Normalize the Uncertainty Product to Determine the Moving Average Window Size:
The uncertainty product is used to adjust the length of the moving average dynamically.
The formula inversely adjusts the moving average length based on uncertainty: higher uncertainty results in a shorter (more responsive) window and lower uncertainty results in a longer (smoother) window.
Calculate the Heisenberg Uncertainty Moving Average (HUMA):
The slope is determined by finding the difference between the current HUMA value and the value from the previous period, smoothed with a Double Exponential Moving Average (DEMA).
This helps identify the direction of the trend: positive slope indicates an uptrend, and negative slope indicates a downtrend.
Dynamic Coloring Based on the Slope:
This script introduces and approximation of the Heisenberg Uncertainty Moving Average (HUMA), inspired by the principles of quantum physics, particularly the Heisenberg Uncertainty Principle. The indicator dynamically adjusts its moving average length based on price and momentum uncertainty, ensuring adaptability to market conditions. It also features dynamic coloring to indicate the slope of the moving average.
Step-by-Step Explanation
Calculate Uncertainty in Price (Δx):
The price uncertainty is measured over a specified lookback period (length).
This is done by finding the difference between the highest high and lowest low over the period
Momentum uncertainty is defined using the Rate of Change (ROC) of the closing price over the same lookback period (length).
This indicates how much the price has changed over that period, providing a measure of momentum uncertainty.
Introduce Planck’s Constant (h):
Planck’s constant (h) is scaled down for financial use to set a theoretical minimum threshold for the product of uncertainties.
The threshold is defined as h / (4 * π) to simulate a limit that aligns with the Heisenberg Uncertainty Principle in physics.
Calculate the Uncertainty Product (Δx ⋅ Δp):
The product of price uncertainty (Δx) and the absolute value of momentum uncertainty (Δp) is calculated.
To ensure the product respects the minimum threshold set by quantum principles, the value is capped using math.max(uncertainty_product, threshold).
Normalize the Uncertainty Product to Determine the Moving Average Window Size:
The uncertainty product is used to adjust the length of the moving average dynamically.
The formula inversely adjusts the moving average length based on uncertainty: higher uncertainty results in a shorter (more responsive) window and lower uncertainty results in a longer (smoother) window.
Calculate the Heisenberg Uncertainty Moving Average (HUMA):
The slope is determined by finding the difference between the current HUMA value and the value from the previous period, smoothed with a Double Exponential Moving Average (DEMA).
This helps identify the direction of the trend: positive slope indicates an uptrend, and negative slope indicates a downtrend.
Dynamic Coloring Based on the Slope:
Geschütztes Skript
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