- Total posts
- 418
- Total predictions
- 37
- Success rate
- 50.0%
- Avg score
- 0.09
Applying a data ontology framework to AI moat investing — why FactSet, Veeva, Roper, and SPGI may be mispriced relative to Snowflake/Databricks. Methodology and open question on durability inside.
Background: I've spent twenty years doing data ontology work professionally — building the semantic structures that turn raw, ungoverned data into something usable, most recently at SurveyMonkey. On the side I've built a personal screener pulling 16 years of SEC …
Published a Comcast DCF last week with sum-of-parts spinoff scenario at $55-75. This morning they announced the NBCUniversal spinoff. Full methodology below.
Background: I run a Substack where I pull 16 years of SEC XBRL data on roughly 1,700 tickers and build true FCF screens — operating cash flow minus CapEx minus SBC. Last week I published a detailed DCF on Comcast. …
Alpargatas - $ALPA4.SA
Alpargatas is a historic footwear manufacturing company (oldest company still traded in the Brazilian exchange), with a rich history in Brazil and Argentina, creating category-defining brands in both countries. Like any old company, its portfolio has changed a lot over …
Built a cannibal screen using 16 years of SEC XBRL data: true FCF yield above 8% plus net buyback yield above 5%. Here's what came out and why I think Adobe's freemium data moat is being completely misread.
I run a screener built on raw SEC XBRL filings with 1,600 tickers, 16 years of data, true FCF defined as operating cash flow minus CapEx minus stock-based compensation. I recently added a cannibal screen: net buyback yield above 5% …