kedarghule/Stock-Portfolio-Diversification-Using-Clustering-and-Volatility-Prediction

The project aims to profile stocks with similar weekly percentage returns using K-Means Clustering. The project calculates realized volatility for each stock and predicts realized volatility for each stock using classical volatility models and machine learning models and comparing their performance. This is a capstone project for CIVE 7100 Time Series and Geospatial Data Sciences.