Market Trend Classification Model

[alo7lika]

#1283

Description

This update introduces the Market Trend Classification Model, which analyzes historical stock price data to classify distinct market conditions. The model utilizes key features such as adjusted close prices, daily returns, moving averages, and volatility to provide insights into market dynamics. By employing K-means clustering, the model categorizes periods into market regimes: Bull, Bear, and Neutral. The motivation behind this development is to equip traders and investors with a robust tool for informed decision-making based on identified market trends.

Dependencies:

• pandas
• numpy
• scikit-learn
• matplotlib
• seaborn

Fixes # (issue)

Type of change

• Added a new machine learning framework, library, or software.
• Documentation update

Checklist:

• My code follows the style guidelines of this project
• I have performed a self-review of my own code
• I have commented on my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• My changes generate no new warnings

[github-actions]

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