{"repo":"Amey-Thakur/OPTIMIZING-STOCK-TRADING-STRATEGY-WITH-K-MEANS-CLUSTERING","free":true,"listed":false,"github":"https://github.com/Amey-Thakur/OPTIMIZING-STOCK-TRADING-STRATEGY-WITH-K-MEANS-CLUSTERING","clone":"git clone https://github.com/Amey-Thakur/OPTIMIZING-STOCK-TRADING-STRATEGY-WITH-K-MEANS-CLUSTERING.git","description":"Big Data Analytics [BDA] Mini Project","language":"Jupyter Notebook","stars":15,"topics":["ameythakur","amey","engineering","computer-engineering","big-data-analytics","big-data","megasatish","algorithmic-trading","big-data-analytics-techniques","financial-data-science"],"license":"MIT","category":"trading","readme_excerpt":"# Optimizing Stock Trading Strategy with K-Means Clustering An analytical project utilizing unsupervised machine learning to cluster stocks based on their volatility and returns, identifying latent market patterns and optimizing diversified trading strategies. Source Code &nbsp;·&nbsp; Technical Specification &nbsp;·&nbsp; Video Demo &nbsp;·&nbsp; Live Demo --- Authors &nbsp;·&nbsp; Overview &nbsp;·&nbsp; Features &nbsp;·&nbsp; Structure &nbsp;·&nbsp; Quick Start &nbsp;·&nbsp; Usage Guidelines &nbsp;·&nbsp; License &nbsp;·&nbsp; About &nbsp;·&nbsp; Acknowledgments --- ## Authors Terna Engineering College Computer Engineering Batch of 2022 Amey Thakur Hasan Rizvi Mega Satish :---: :---: :---: [!IMPORTANT] ### 🤝🏻 Special Acknowledgement Special thanks to Hasan Rizvi and Mega Satish for their meaningful contributions, guidance, and support that helped shape this work. --- Overview This project investigates the application of K-Means Clustering on financial market data. By categorizing stocks into distinct clusters based on their historical price movements, the system provides a data-driven approach to understanding market dynamics and constructing balanced investment portfolios. Developed as a mini-project for the Big Data Analytics & Computational Lab - I curriculum, this implementation showcases the full data science pipeline: from data acquisition via Yahoo Finance to feature engineering (volatility/returns) and unsupervised model validation. Resources # Resource Descriptio","default_branch":null,"files":null,"tree":[],"storefront":"/r/Amey-Thakur","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Amey-Thakur/OPTIMIZING-STOCK-TRADING-STRATEGY-WITH-K-MEANS-CLUSTERING/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}