stock-analyzer

To generate a stock analysis report, you request analysis on a specific ticker like AAPL. The Skill retrieves market data using yfinance, performs fundamental and technical analysis, and outputs a comprehensive PDF document containing valuation metrics, technical indicators, and a DCF model.

DCF modeling, or discounted cash flow modeling, is a valuation method used to estimate the value of an investment based on its expected future cash flows. This Skill performs dynamic cash flow analysis to support equity research and determine intrinsic stock valuation.

Yes, you can use Python libraries like yfinance and matplotlib for technical analysis within this workflow. The Skill utilizes yfinance to retrieve historical market data and matplotlib to visualize price trends and technical indicators for chart analysis.

Yes, this equity research tool supports peer comparison. It generates comparative analysis tables that evaluate key financial metrics and valuation ratios against similar companies, aiding in relative valuation and portfolio analysis workflows.

The best way to automate investment research is by leveraging programmatic data retrieval and dynamic DCF modeling. By running scripts to automatically pull financial data, calculate ratios, and generate PDF reports, you streamline portfolio analysis and valuation workflows.

Yes, pandas and openpyxl are required dependencies for handling financial data structures and spreadsheet operations. The Skill uses pandas for data manipulation and relies on these libraries to process the underlying financial datasets used for reporting.