Stock Market Analysis

This project presents a comprehensive analysis of stock performance across various sectors and indices, visualizes trends around significant events, and detects anomalies in stock volatility, specifically focus on the periods of COVID-19 and the Russia-Ukraine War. The deliverables are the final report and a streamlit dashboard (see below). Completed during the UIC Fall '24 course CS 418 under Prof. Sathya Ravi.

Table of Contents

• Introduction
• Features
• Dashboard
• Data
• Contributors

Introduction

The Stock Market Analysis Dashboard is designed to provide insights into the performance of different sectors, including Defense, Tech, Healthcare, Energy, and major Indices. It allows users to visualize normalized stock prices, analyze correlations, and detect anomalies in stock volatility using machine learning techniques.

Features

• Sector Performance Visualization: Compare normalized stock prices within a selected sector over a specified time period.
• Correlation Heatmap: Display the correlation matrix of stocks within a sector to understand interdependencies.
• Volatility Analysis and Anomaly Detection: Analyze stock volatility and detect anomalies using the Isolation Forest algorithm.

Dashboard

View the Deployed dashboard Here

Data

The project utilizes stock data fetched using the yfinance library. Users can specify the date range and sector of interest in the dashboard. The data is normalized to facilitate comparison across different stocks.

Contributors

1. Prajwal Vishwanath - ParzivalDV
2. Apoorva Vutukur - avutuUIC
3. Devarshi Dhola - DevarshiDhola07
4. Sanjana Uppalike - suppa17
5. Shriraksha B Srinivas - sbyra
6. Varun P Srivathsa - varunpuic