Key Components : 📍 Natural Logarithm Function : The script starts by employing a custom Taylor Series approximation for natural logarithms. This function serves to calculate entropy with higher accuracy than conventional methods, laying the foundation for further calculations. 📍 Entropy Calculation : The core of this indicator is its entropy function. It employs...
Adaptive Two-Pole Super Smoother Entropy (Math) MACD is an Ehlers Two-Pole Super Smoother that is transformed into an MACD oscillator using entropy mathematics. Signals are generated using Discontinued Signal Lines. What is Ehlers; Two-Pole Super Smoother? From "Cycle Analytics for Traders Advanced Technical Trading Concepts" by John F. Ehlers A...
This script performs the basic Shannon entropy on the closing value of the stock. Additionally, it performs the trailing first and second derivatives of the Shannon Entropy, giving you more information about its movement. You can change the "Source" to be whatever value you like.
Library "Probability" erf(value) Complementary error function Parameters: value : float, value to test. Returns: float ierf_mcgiles(value) Computes the inverse error function using the Mc Giles method, sacrifices accuracy for speed. Parameters: value : float, -1.0 >= _value >= 1.0 range, value to test. Returns: float ierf_double(value) ...
function to retrieve Gini Impurity / Gini Index. reference: - victorzhou.com - en.wikipedia.org
functions for shannon's entropy reference: - en.wiktionary.org - machinelearningmastery.com
This indicator is the Bernoulli Process or Wikipedia - Binary Entropy Function . Within Information Theory, Entropy is the measure of available information, here we use a binary variable 0 or 1 (P) and (1-P) (Bernoulli Function/Distribution), and combined with the Shannon Entropy measurement. As you can see below, it produces some wonderful charts and signals,...
Version 2, Shannon Entropy This update includes both a deadband (Plotting Optional) and PercentRank Indicating. Here is a unique way of looking at your price & volume information. Utilize the calculated value of "Shannon Entropy". This is a measure of "surprise" in the data, the larger the move or deviation from the most probable value, the higher the new...
Here is a unique way of looking at your price & volume information. Utilize the calculated value of "Shannon Entropy". This is a measure of "surprise" in the data, the larger the move or deviation from the most probable value, the higher the new information gain. What I think is so interesting about this value, is the smoothness that it displays the information...