Model the underlying business
Explore customer adoption, retention, pricing, segment revenue, profitability, and cash generation before translating assumptions into valuation scenarios.
Why do some companies defy easy valuation? StockPhys explores how adoption, feedback, business fundamentals and discounted cash flow fit together. We are building the research framework—without claiming to know tomorrow’s share price.
Public research preview · No price targets, subscriptions, or forecasts published yet.
Stylized curves only—not PLTR data, a fitted model, or a forecast. Different adoption assumptions can imply different future business fundamentals.
A stock-price target is a conclusion. The more useful questions are how the company might evolve, why, and how much confidence the evidence supports.
Explore customer adoption, retention, pricing, segment revenue, profitability, and cash generation before translating assumptions into valuation scenarios.
Use alternative scenarios and explicit uncertainty to distinguish plausible paths from precise-looking but fragile point estimates.
Historical examples will be evaluated using data available at the time, with forecasted fundamentals compared against subsequently reported results.
A spreadsheet can discount future cash flows. The harder problem is deciding which future business trajectory belongs in that spreadsheet.
Consider Palantir (NYSE: PLTR). Its government and commercial businesses have different buying dynamics, while adoption of AI-enabled software, expansion within customers and operating leverage can reshape future economics. None of those paths is guaranteed.
Two analysts can use perfectly valid discounted cash flow methods and still arrive at very different values—because the assumptions about adoption, pricing, margins and durability differ.
See the ideas behind our approach →Illustrative research questions only. No PLTR estimate, recommendation or forecast is presented. Company filings ↗
Ideas from complex systems—nonlinear growth, feedback, time delays and uncertainty—can help us ask better questions about businesses. DCF remains part of the toolkit, but it is only as useful as the business assumptions behind it.
Read what we are exploringThe model is not the evidence.
We want to understand how a company may evolve before discussing valuation. When we publish future research, the test will be whether its assumptions and model outputs stand up against real company results—not whether an estimated fair value happens to equal the market price.
For now, we are sharing questions, ideas and methods—not security-specific forecasts, subscriptions or model results.