This project conducts a comprehensive financial analysis of Johnson & Johnson (J&J) using Python. The analysis encompasses income statements, balance sheets, and cash flows sourced from Yahoo Finance. Various financial ratios, the Capital Asset Pricing Model (CAPM), and Monte Carlo simulation are employed to evaluate the financial data. Additionally, advanced techniques including Simple Moving Average (SMA), Exponential Moving Average (EMA), and FB Prophet are utilized to forecast future stock prices of Johnson & Johnson based on the most recent two years' data.
The financial data used for this analysis is sourced from Yahoo Finance. It includes historical data for Johnson & Johnson's income statements, balance sheets, and cash flows.
The first step involves collecting financial data for Johnson & Johnson from Yahoo Finance. Python libraries such as Pandas and yfinance are used to fetch and store the data for analysis.
A variety of financial ratios are calculated to assess J&J's financial health and performance. These ratios include liquidity ratios, profitability ratios, and solvency ratios.
The Capital Asset Pricing Model (CAPM) is applied to estimate J&J's expected rate of return. This helps in evaluating the company's stock performance against the market.
Monte Carlo simulation is employed to assess the potential future stock price movements of J&J. This stochastic technique considers multiple scenarios to provide a range of possible outcomes.
Advanced time series analysis techniques such as Simple Moving Average (SMA), Exponential Moving Average (EMA), and the FB Prophet model are utilized to forecast J&J's future stock prices. This forecasting provides insights into potential trends and helps in making informed investment decisions.
The analysis of Johnson & Johnson's financial data reveals key insights into the company's financial performance, risk, and potential future stock price movements. These findings are essential for investors and financial analysts to make informed decisions regarding their investments in J&J.
- Special thanks to Yahoo Finance for providing the financial data for this analysis.