His data is free on the NYU page, but turning it into an actual valuation takes hours per stock.
StockValuation.io does it in minutes: - Pulls live financials via yFinance - Uses Damodaran's published datasets for cost of capital inputs - Runs deterministic DCF math (every assumption is visible) - Layers an LLM on top for bull/bear narratives and assumption overrides
The math never changes based on AI mood. The LLM only touches research and storytelling.
Self-host: https://github.com/stockvaluation-io/stockvaluation_io (one Docker command, MIT license)
Happy to discuss the methodology, assumption choices, or why I think Deterministic math + probabilistic narratives is the right architecture for this.