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Episode Description
Stock screeners can feel intimidating, but they’re really just a fast way to generate starting points—not “buy” signals. In this episode, Stephen and Andrew build a simple screener in Fiscal.ai (growth, ROIC, balance sheet strength, valuation, and anti-dilution rules), then run it live and walk through what shows up.
You’ll hear how they quickly pressure-test businesses like Yelp, LendingTree, Brinker (Chili’s), Yeti, Zoetis, and CarGurus—using basic questions around moats, management quality, cyclicality, and what the financials are actually saying. The big takeaway: keep an open mind, be willing to be wrong, and use the screener to spark curiosity—then do the real research.
What You Will Learn
How to build a “good enough” stock screener without overcomplicating it
Why a screener is a starting point, not an investing answer
The key metrics Andrew screens for (growth, ROIC, leverage, valuation, dilution signals)
How to do a fast first-pass business check
How to think about “cheap” stocks correctly
Timestamps
00:00 What this “live screener” episode is (no prep, show the process)
00:49 How Andrew built the screener and what it’s screening for
00:56 Fiscal.ai and the screener rules (growth, SBC <10%, negative financing cash flow, valuation, leverage, ROIC)
02:36 Run the screener: 43 names + how they’ll pick what to review
02:45 Yelp (YELP): quick overview + “Yelp Assistant” + 90% gross margins
03:46 Yelp moat question: “are people still using Yelp?” + Google/Maps competition
08:18 LendingTree (TREE): not a lender—lead gen marketplace + why research matters
11:20 LendingTree: what happened post-2019 (legal disputes, losses, data breach)
18:06 Brinker (EAT): Chili’s surprise growth + “cheap” means valuation, not share price
22:23 Brinker: same-store sales as the key KPI + why 25% comps is shocking
Resources Mentioned
The Value Spotlight Newsletter: https://einvestingforbeginners.com/value-spotlight-newsletter/
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Remember, invest with a margin of safety—emphasis on the safety. Have a great week, and we’ll talk to you next time.
Timestamps are generated by artificial intelligence, and are not 100% accurate depending on the platform used for listening.
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