Bullpen.News From Edwin Dorsey
Get Daily Recap Feedback

Latest News

Market capAny size
All Over $50MOver $300MOver $2BOver $10B
All Under $1BUnder $10BUnder $100BUnder $500B
SectorsAll
Filter by sector
Thursday, October 15, 2026· 10302 stock ideas· 217 writers·
15,892 views· 7,443 clicks

Problems at Dream Finders Homes (DFH)

Dream Finders Homes’ controlling owner borrowed against DFH stock before the homebuilder agreed to finance an acquisition with costly preferred stock and debt.

DFH $808M
Hunterbrook

From X

@convequity

Convequity on X

We think hardware manufacturing and chip costs, more than launch, will decide how much $SPCX earns from orbital compute. Our SPCX model estimates how much orbital compute can be made and launched, what it costs and what it earns as it ages, then adds that revenue to our forecasts for SpaceX's launch, Starlink and Cursor businesses in our SPCX DCF. Each year, deployment equals the gigawatts of solar and AI computing hardware the supply chain can make for orbital data centers, capped by what Starship can carry. In our base case, launch is the tighter limit only in the first four years of the forecast, and manufacturing is the limit after that. Our base case puts chips and racks at about 80% of the cost to build each gigawatt and launch at about 11%. Solar arrays, satellite structure and laser communications make up the rest. Because chips make up most of the cost and launch only a small part, whether SpaceX uses merchant GPUs, custom chips or makes its own chips at Terrafab will matter more to returns than how cheap launch gets. Revenue per gigawatt depends on the business model, and we assume it is higher for selling AI services through an API than for renting out compute. Revenue falls as the hardware ages, and we assume each satellite is replaced after a 7-year life. The model's price-cut settings let us test price competition. We think Chinese companies could use their own launch and computing infrastructure to offer cheaper AI services internationally, pressuring the prices U.S. AI companies charge and what they can pay for capacity. The U.S. and China could also tie access to their AI services to defense and trade relationships. Countries with ties to both, including India and some Middle Eastern states, could keep access to U.S. and Chinese providers and negotiate lower prices.
@BrokenMoats

Broken Moats on X

Have to at least acknowledge rate reversal and move into low quality and retail/software today...... But oil/diesel/soft commodities/transportation all staying bid, find this more positioning over extended om rates then durable change (especially with the data and the still unresolved issues causing the inflation) AI sold off I think is what is driving both moves in rates (more out needs a home) and retail/rate sensitive/software were the funding shorts (see sectors and components today) ......but geez at these prices an easier trade I think is to fade software/retail then guess next stop on AI and funding.....the are correlated (for now) anyways. Go through the sectors and components and sort by % gain today almost stacked ranked from worst business (biggest intraday gain) to quality at the bottom.....tells you whats going on. Some might say low quality always leads on a reversal.....this is not a start this is after a stealth sharp move higher for $ARHS $ETSY $EBAY $KSS $SHAK $WMT $CBRL $APPN $DOCU $IT $FRSH $BSP etc.
@StableBread

Fajasy on X

If the AI model Nubeva Technologies $NBVAF (TSXV: $NBVA) is training to read malware works, it could also take over the one step in its ransomware recovery software that engineers still do by hand. Nubeva’s Ransomware Reversal software, or NuRR, copies the encryption keys during an attack, but someone still has to figure out how ransomware uses them before Nubeva can build a decryptor (a program that reverses the encryption). AI agents have run NuRR’s routine support (bug fixes, support tickets, and product maintenance) for some time, CEO Randy Chou said, but Nubeva’s engineers still handle each live ransomware case by hand. Nubeva’s first granted patent finds the encryption method by running the ransomware in a sandbox (an isolated test computer) and matching the result to a library of standard methods. But the sandbox method breaks down in two cases Chou described, since homemade encryption (encryption ransomware authors write themselves) won’t match any standard method, and malware that detects the sandbox does nothing. A model that reads the malware’s compiled code could get around both problems, since (1) homemade encryption still shows up in the code as steps a model can follow, and (2) the malware’s checks for a real computer only run when the malware runs, so reading the code never triggers the checks. With NuRR supplying the keys and the model working out the encryption method, Nubeva would have both inputs a decryptor needs without an engineer taking the ransomware apart by hand. Frontier models, the most advanced AI models from labs like OpenAI and Anthropic, can already work out what some binaries (compiled programs) do just by reading their code. Anthropic said in April 2026 that its Claude Mythos Preview model can take “a closed-source, stripped binary,” meaning one with its function and variable names removed, and reconstruct “(plausible) source code for what it does.” Obfuscation (scrambling code to hide its purpose) is harder for a model to get past, since compressed malware keeps its real code hidden until it runs. Chou blamed obfuscation for the ~70% of malware binaries frontier models can’t figure out, so Nubeva’s model still has to prove it can do better. Chou didn’t connect the model to NuRR in his October 5, 2026 interview, but working out the encryption method is the same step Nubeva’s FY2026 annual filings say its AI decryptor builder will automate. Therefore, if the model works on live ransomware, NuRR could take on more cases at once, easing the capacity problem that cost Nubeva its biggest customer in 2023 (risk advisory firm Kroll).

Investor Letters

All letters

Free Recaps of the best new stock ideas, delivered every morning.

Read past recaps

Constellation: Stars Aligning?

Constellation Brands trades near $127 at roughly 11x next-twelve-month EV/EBIT, with recent business results offsetting concerns over…

STZ $21B
TSOH Investment Research 15 clicks

TSMC Q3 FY12/26 Earnings Review

TSMC reported excellent Q3 results, guided Q4 revenue growth higher and saw its shares slip despite strong AI-driven earnings momentum.

TSM $2.3T
Cestrian Capital Research 4 clicks

My 2028 numbers

ASML’s €11.7 billion quarter benefited from €3.3 billion in installed-base sales and operating leverage, while the MATCH Act threatens…

ASML $660B
Best Anchor Stocks 22 clicks

Lennar, Part One: The Story

Lennar grew from a Miami builder into one of America’s two largest homebuilders, controlling land largely through options and land banks…

LEN $17B
Latticework by MOI Global 10 clicks

Lennar, Part Two: The Deep Dive

Lennar’s second audio program examines the homebuilder’s business for professional investors and housing analysts.

LEN $17B
Latticework by MOI Global 11 clicks

Have a source we’re missing? Send your pick

Recent recaps

Latest recap

Wednesday, October 14 70 stock ideas
  • October 2026 Random Ramblings Yet Another Value Podcast
  • Visa: Unpacking The 7 Powers And Forward Valuation Ahead Of Q4 Earnings Seeking Alpha
Read the recap

All recaps

Publications we follow

Every publication on this site, hand-picked.

129 publications

Newsletters 107

YouTube 4

Blogs 17

Seeking Alpha 49 of 227

Nominate a publication

X accounts we follow

Every account on this site, hand-picked.

88 accounts
Nominate an account

Investor letters we follow

189 firms

Sectors

Ordered by how often our editor reaches for them.

Anything we’re missing?

Send us a pick