kanchi-dividend-sop

Automating dividend stock screening involves evaluating yield, growth, safety, and valuation using financial data APIs and Python libraries like pandas and numpy for data processing. This Skill applies the Kanchi methodology to execute that specific analysis.

The Kanchi methodology is a structured approach to dividend investing that evaluates stocks based on dividend yield, growth, safety, and valuation metrics. This Skill automates that methodology for investment research and portfolio management workflows.

Yes, you can use yfinance and financialmodelingprep to fetch financial data for dividend portfolio monitoring. This Skill requires these specific dependencies alongside pandas and numpy to analyze performance and monitor key events.

To screen dividend-paying stocks with a specific yield floor, you apply filtering parameters to financial data retrieved via APIs. This Skill allows you to set parameters like a 3% yield floor and a medium safety bias for screening.

Yes, this Skill handles dividend valuation analysis and monitors selected stocks to provide alerts for key events and changes. It processes the data using Python libraries to track performance within your portfolio management workflow.