OPEN-SOURCE SCRIPT
[MAD MBS] L3 Float Operations & ML-Normalizers

First of all:
This indicator is not a standalone tool; it relies on other script series for its inputs.
This script is an indicator designed for multi-path float operations with integrated machine learning normalizers.
It supports up to four distinct paths, each customizable with multiple sources, factors, and operations.
Users can perform various mathematical operations on price data, including addition, subtraction, multiplication, division, and percentage changes, as well as more advanced tasks like double and triple moving averages or power operations.
The script also integrates several normalization methods (e.g., Min-Max, Z-Score, Robust) to standardize data—an important step for machine learning models.
Each path supports multiple smoothing techniques (e.g., EMA, SMA, and specialized Ehlers smoothers) to further refine the output.
Designed to handle multiple data inputs simultaneously, this tool is especially useful for traders looking to analyze and normalize data from different price sources.
The combination of advanced mathematical operations, normalization techniques, and smoothing enhances data management, aiding in more effective trading decisions.
Here you can see a single path, out of the four possible:

Details to the screenshot:
First Series
Second Series
Option to override the second series with a custom constant (or when normalizing, use the length instead)
The first selection box sets the mathematical operation or activates the normalizer.
The second selection box sets the normalization method.
The third selection box sets the final smoothing technique, followed by parameters for smoothing length.
These settings are repeated identically for Paths 2–4.
At the bottom of the setup, there's a general offset option (add the 'close' price for overlay purposes).
Additionally, there's an option to display a line at zero for centered results.
This indicator is not a standalone tool; it relies on other script series for its inputs.
This script is an indicator designed for multi-path float operations with integrated machine learning normalizers.
It supports up to four distinct paths, each customizable with multiple sources, factors, and operations.
Users can perform various mathematical operations on price data, including addition, subtraction, multiplication, division, and percentage changes, as well as more advanced tasks like double and triple moving averages or power operations.
The script also integrates several normalization methods (e.g., Min-Max, Z-Score, Robust) to standardize data—an important step for machine learning models.
Each path supports multiple smoothing techniques (e.g., EMA, SMA, and specialized Ehlers smoothers) to further refine the output.
Designed to handle multiple data inputs simultaneously, this tool is especially useful for traders looking to analyze and normalize data from different price sources.
The combination of advanced mathematical operations, normalization techniques, and smoothing enhances data management, aiding in more effective trading decisions.
Here you can see a single path, out of the four possible:
Details to the screenshot:
First Series
Second Series
Option to override the second series with a custom constant (or when normalizing, use the length instead)
The first selection box sets the mathematical operation or activates the normalizer.
The second selection box sets the normalization method.
The third selection box sets the final smoothing technique, followed by parameters for smoothing length.
These settings are repeated identically for Paths 2–4.
At the bottom of the setup, there's a general offset option (add the 'close' price for overlay purposes).
Additionally, there's an option to display a line at zero for centered results.
開源腳本
秉持TradingView一貫精神,這個腳本的創作者將其設為開源,以便交易者檢視並驗證其功能。向作者致敬!您可以免費使用此腳本,但請注意,重新發佈代碼需遵守我們的社群規範。
免責聲明
這些資訊和出版物並非旨在提供,也不構成TradingView提供或認可的任何形式的財務、投資、交易或其他類型的建議或推薦。請閱讀使用條款以了解更多資訊。
開源腳本
秉持TradingView一貫精神,這個腳本的創作者將其設為開源,以便交易者檢視並驗證其功能。向作者致敬!您可以免費使用此腳本,但請注意,重新發佈代碼需遵守我們的社群規範。
免責聲明
這些資訊和出版物並非旨在提供,也不構成TradingView提供或認可的任何形式的財務、投資、交易或其他類型的建議或推薦。請閱讀使用條款以了解更多資訊。