ML - Momentum Index (Pivots)

Building upon the innovative foundations laid by Zeiierman's Machine Learning Momentum Index (MLMI), this variation introduces a series of refinements and new features aimed at bolstering the model's predictive accuracy and responsiveness. Licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0), my adaptation seeks to enhance the original by offering a more nuanced approach to momentum-based trading.

Key Features:

• Pivot-Based Analysis: Shifting focus from trend crosses to pivot points, this version employs pivot bars to offer a distinct perspective on market momentum, aiding in the identification of critical reversal points.
  
• Extended Parameter Set: By integrating additional parameters for making predictions, the model gains improved adaptability, allowing for finer tuning to match market conditions.
  
• Dataset Size Limitation: To ensure efficiency and mitigate the risk of calculation timeouts, a cap on the dataset size has been implemented, balancing between comprehensive historical analysis and computational agility.
  
• Enhanced Price Source Flexibility: Users can select between closing prices or (suggested) OHLC4 as the basis for calculations, tailoring the indicator to different analysis preferences and strategies.
  

This adaptation not only inherits the robust framework of the original MLMI but also introduces innovations to enhance its utility in diverse trading scenarios. Whether you're looking to refine your short-term trading tactics or seeking stable indicators for long-term strategies, the ML - Momentum Index (Pivots) offers a versatile tool to navigate the complexities of the market.

For a deeper understanding of the modifications and to leverage the full potential of this indicator, users are encouraged to explore the tooltips and documentation provided within the script.

The Momentum Indicator calculations have been transitioned to the MLMomentumIndex library, simplifying the process of integration. Users can now seamlessly incorporate the momentumIndexPivots function into their scripts to conduct detailed momentum analysis with ease.

發布通知:

• Updated compiler annotations in the library for better documentation.
  
• Upgraded indicator to align with the new library version for improved clarity and functionality.