Financial Analysis of Short Selling Impact on Volkswagen During the 2008-2009 Financial Crisis

Table of Contents

1. Introduction
2. Project Structure
3. Setup Instructions
4. Data Sources
5. Running the Scripts
   • Download Data
   • Analyze Data
   • Sentiment Analysis
6. Analysis and Results
7. Dependencies
8. Contributing
9. License

---

Introduction

This project aims to analyze the impact of short selling on Volkswagen stock and the broader market during the 2008-2009 financial crisis. The analysis includes:

• Correlation analysis between Volkswagen stock prices and Failures to Deliver (FTD) volumes.
• Regression analysis to explore the relationship between FTD volumes and stock prices.
• Sentiment analysis of news articles related to Volkswagen during the period of interest.

---

Project Structure

financial_analysis/
├── data/
├─├──FTDs/
├─├──├─cnsp_sec_fails_200{701..812}.txt/
│ ├── volkswagen_stock_prices.csv
│ ├── ftd_data.csv
│ ├── sp500_index.csv
│ └── news_articles.json
├── scripts/
│ ├── download_data.py
│ ├── analyze_data.py
│ └── sentiment_analysis.py
├── requirements.txt
└── README.md

• data/: Directory to store all datasets.
• scripts/: Directory containing Python scripts for data download, analysis, and sentiment analysis.
• requirements.txt: File listing all Python dependencies.
• README.md: Detailed project documentation.

---

Setup Instructions

Follow these steps to set up the project on your local machine:

1. Clone the repository:

   git clone https://github.com/yourusername/financial_analysis.git
   cd financial_analysis
   

2. Install the required packages:

   pip install -r requirements.txt
   

Data Sources

The data used in this project includes:

• Volkswagen Stock Prices: Historical stock prices for Volkswagen.
• Failures to Deliver (FTD) Data: FTD data for Volkswagen.
• S&P 500 Index Data: Historical S&P 500 index data.
• News Articles: News articles related to Volkswagen.

Running the Scripts

1. Download and Parse Data This script downloads the required datasets and saves them into the data/ directory.

   python scripts/download_data.py

paste the data of 2007-2008 files from SEC FTD in the data folder (use curl) these two scripts will parse the data accordingly.

python scripts/parseftd.py
python scripts/convert_text_csv.py

2. Analyze Data This script loads and analyzes the data, performing correlation and regression analysis.

   python scripts/analyze_data.py

3. Sentiment Analysis This script performs sentiment analysis on the news articles related to Volkswagen.

   python scripts/sentiment_analysis.py
   

Analysis and Results

The analysis includes the following components:

1. Correlation Analysis: Identifies correlations between Volkswagen stock prices and FTD volumes.
2. Regression Analysis: Explores the relationship between FTD volumes and stock prices.
3. Sentiment Analysis: Analyzes the sentiment of news articles related to Volkswagen during the period of interest. Example Outputs: Correlation Analysis The correlation matrix showing the relationship between Volkswagen stock prices and FTD volumes.

Regression Analysis A summary of the regression analysis exploring the relationship between FTD volumes and Volkswagen stock prices.

Sentiment Analysis A plot showing the sentiment of news articles over time.

Dependencies

The project relies on the following Python libraries:

• yfinance
• requests
• pandas
• matplotlib
• seaborn
• statsmodels
• textblob

These dependencies are listed in the requirements.txt file and can be installed using pip install -r requirements.txt.

Contributing

Contributions are welcome! Please create a pull request or submit an issue if you have any suggestions or find any bugs.