QuantitativeStockAnalysis

Overview

QuantitativeStockAnalysis is a Flask-based web application that provides statistical analysis and visualizations for stock data. Users can input a stock ticker to view detailed statistics, perform hypothesis tests, and generate predictive models based on historical stock data.

Screenshot

Features

• Fetches historical stock data for the past 5 years.
• Calculates daily log returns and key statistical metrics (mean, variance, skewness, kurtosis, etc.).
• Performs hypothesis tests, including kurtosis tests and t-tests.
• Generates visualizations such as closing price trends, log return distributions, and regression plots.
• Predicts future stock prices using regression analysis.

How to Run

1. Set Up the Environment

• Upgrade pip and install dependencies:

python -m pip install --upgrade pip
pip install -r requirements.txt

2. Run the Application

• Navigate to the app directory:

cd stockAnalysis_app

• Start the Flask server:

python app.py

3. Access the Application

• Open your browser and navigate to http://127.0.0.1:5000 to use the application.

Notes

• The dependencies are listed in requirements.txt.
• If you encounter execution policy errors when activating the virtual environment, run the following command in an elevated PowerShell session:

Set-ExecutionPolicy -Scope CurrentUser -ExecutionPolicy RemoteSigned

File Structure

QuantitativeStockAnalysis/
├── main.py
├── README.md
├── requirements.txt
├── stockAnalysis_app/
│   ├── app.py
│   ├── stock_analysis.py
│   ├── static/
│   │   ├── style.css
│   ├── templates/
│   │   ├── base.html
│   │   ├── index.html

Future Improvements

• Add more advanced statistical models.
• Enhance the UI with additional visualizations and interactivity.
• Integrate real-time stock data updates.

Sources & Acknowledgments

• Special thanks to Matt Macarty for providing the foundational concepts for the analyses used in this project. Very insightful video, 10/10 would reccomend.