Welcome to the Financial Analytics with Python repository! This repository houses two distinct projects that focus on analyzing financial data and investment strategies using Python. Each project is stored in its own directory and is designed to offer insights into different aspects of financial planning and analysis.
Description: This project analyzes a financial portfolio consisting of FAANG stocks—Facebook (META), Amazon (AMZN), Apple (AAPL), Netflix (NFLX), and Alphabet (GOOG). Using Python and data sourced from Yahoo Finance, the project calculates key financial metrics including cumulative returns, daily returns, and portfolio volatility.
Key Features:
- Portfolio Simple Returns Calculation
- Daily Returns Analysis
- Volatility Assessment
- Data Extraction with Pandas Data Reader
- Customizable Timeframe Analysis
Objective: To provide a comprehensive understanding of how a stock portfolio behaves over time, offering insights into its profitability and risk.
Description: This project simulates an investment strategy to assess if investing 50% of an individual's income over a 10-year period will provide sufficient financial support upon retirement. The analysis includes yearly income, expenses, investments, and returns to validate the sustainability of this investment strategy.
Key Features:
- Income and Expense Modeling
- Investment Calculation with Fixed Parameters
- Financial Projections for 20 Years
- Scenario Analysis with Adjustable Parameters
Objective: To evaluate the effectiveness of investing 50% of income to ensure financial stability by retirement and to provide insights into how different financial parameters impact investment outcomes.
To explore the projects, follow these links to access the respective directories:
Feel free to fork the repository and submit pull requests with improvements or additional features. For any issues or questions, please open an issue on the GitHub repository.
Special thanks to the open-source community and financial data providers for their invaluable resources and tools.
Thank you for visiting the Financial Analytics with Python repository. We hope you find these projects useful and informative!