Taylor Series Approximations for Trigonometry: 1. The indicator starts by calculating sine and cosine values of the close price using Taylor Series approximations. These approximations use polynomial terms to estimate the values of these trigonometric functions. Mathematical Component Formation: 2. The calculated sine and cosine values are then multiplied...
Library "Feature_Scaling" FS: This library helps you scale your data to certain ranges or standarize, normalize, unit scale or min-max scale your data in your prefered way. Mostly used for normalization purposes. minmaxscale(source, min, max, length) minmaxscale: Min-max normalization scales your data to set minimum and maximum range Parameters: ...
Feature scaler | Pine Utilities series, ready to be used in "study-on-study" fashion | Includes min-max, normalization, standardization and unit length scaling. One and only source: en.wikipedia.org Endpoint inputs allow to set an interval of interest for min-max scaler. Can be (and should be) applied to other studies, or to the chart itself. In this example,...
This is one of my powerful strategy which I might probably have ever came up. After a lot of backtesting over multiple timeframes and testing different values of the indicator on those multiple timeframes I finally came to a point where this indicator reaches its ultimate goal " Higher Reward Than Risk ". The final result is fantastic as you all can see it's...
This is a scaled version of LazyBear's Squeeze Momentum Indicator. Also added are fibo-based periods for BB and KC.
This is a scaled version of a Forecast Oscillator, which may be used as a standalone indicator or as a filter. Scaling allows to reduce data to a standard interval, say, 0..1 or -1..1. Oftentimes, it also makes data more contrastive.
This is an PS4 update to the Logistic Difference Indicator. It uses logistic function (sigmoid), which stabilizes the variance of data. The logistic function resembles the inverse Fisher transform. This version has a repaint/non-repaint switch and a scaling feature.