financial-data-collector

You can collect US public company financial data into structured JSON by running a collector that pulls market data, income statements, and cash flows from free sources, validating data quality and handling missing values with explicit source markers for reliable downstream modeling.

Yes, you can use yfinance to gather WACC inputs and analyst estimates for DCF models by collecting market data, balance sheets, and historical financials across multiple years, outputting a standardized schema with cross-field consistency checks for accurate valuation analysis.

The best way to handle missing financial data and NaN values when collecting income statements is to flag missing years explicitly, enforce sign conventions for CapEx, and apply cross-field consistency checks to ensure reliable inputs for downstream financial modeling.

Yes, this financial data collector enforces data provenance for balance sheet and cash flow validation by adding explicit source markers to collected fields, handling NaNs for supplementation, and performing cross-field consistency checks to guarantee reliable financial data inputs.

Yes, you can pull historical financials and market data for multiple tickers to build comparables analysis by collecting standardized JSON outputs across companies, enabling downstream financial skills to perform comps analysis and earnings reviews efficiently.

Limitations of using free sources for US public company financial data collection include potential missing years requiring NaN flagging, reliance on data validation to handle source inconsistencies, and the need for explicit source markers to track provenance for reliable modeling inputs.