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Thursday, October 29, 2026

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Another Haircut with Avy the Barber

SoFi’s stock case hinges on interest rates, tangible book value and private-credit loan sales after its $1.5 billion equity offering.

SOFI $22B
WHAT ARE WE DOING? “Contrarians At The Gate” 3 clicks

From X

@StableBread

Fajasy on X

At ~$6.8M net of cash, Nubeva Technologies $NBVAF (TSXV: $NBVA) trades below every one of the five small ransomware-security deals I found with a disclosed price. That’s a CAD$13.0M market cap at CAD$0.185/share (70,173,783 × CAD$0.185), or $9.3M at 1.40 USD/CAD, with the $2.49M of cash and $12,262 of debt netted out. The $6.8M buys two granted patents, two pending applications, the unfinished AI decryptor builder, and a deployment agreement with what Nubeva calls a top-10 global bank, on $500,586 of FY2026 revenue. Here’s what larger security firms paid for five small companies that detect, stop, or recover from ransomware, per the buyers’ filings: → Smokescreen (June 2021): Zscaler $ZS paid ~$11.7M in cash for a startup that plants decoys to catch attackers. → TrapX Security (January 2022): Commvault $CVLT paid $18.65M in cash for an Israeli decoy-technology company. → Minerva Labs (March 2023): Rapid7 $RPD paid $34.6M for a 14-person Israeli startup selling anti-evasion and ransomware-prevention software. → Appranix (April 2024): Commvault paid $26.27M in cash and stock for a Boston startup that cuts the time to rebuild cloud applications after an attack. → Airgap Networks (April 2024): Zscaler paid $124.4M for an “early-stage” network-security company whose product it called a “ransomware kill switch.” For context, Commvault bought TrapX and Appranix as product lines already bringing in ~$3.2M and ~$2.4M a year. Rapid7 and Zscaler bought Minerva Labs and Airgap mainly for their technology. A buyer would be paying for Nubeva’s technology too, meaning four AI patents (assuming the last two come through), the key-capture agent, and a top-10 bank as a reference account (if the license customer renewed), not just ~$500K of revenue. Still, Nubeva’s revenue is a fifth or less of what TrapX and Appranix brought in, and 82% of its revenue comes from two customers, one of which may not have renewed. So I’d put a sale at the low end of these deals, $12-19M (Smokescreen to TrapX), or CAD$0.23-0.37/share, 1.3-2.0x from here. The ~$26M median (2.8x) is the more bullish upside case. If nothing works, two more years of burn leave $0.93-1.29M of cash, and adding the two granted patents and what’s left of the business gets shareholders $1.33-2.01M, or CAD$0.03-0.04/share, a 78-86% loss from CAD$0.185. In other words, CAD$0.185 sits ~45% of the way between the CAD$0.03-0.04 floor and a TrapX-size sale (CAD$0.37/share). If those are the only two outcomes, the market is pricing a sale as close to a coin flip.
@convequity 1 click

Convequity on X

We prefer $UMC to $GFS, and we are increasing our UMC position. Both companies are foundries that make chips on mature processes, well behind the leading edge. We hold GlobalFoundries as a recovery investment. United Microelectronics offers two things on top of a recovery: a manufacturing partnership with production targeted for 2027, and a longer-term way to make its existing processes more competitive. 1. The nearer-term driver is the 12nm process UMC is developing with $INTC. 12nm is a mature process generation, not a leading-edge one. Production is targeted for 2027 at Intel's factories in Arizona. UMC contributes its foundry experience and its experience working with chip designers. Intel contributes the manufacturing capacity. UMC gains a way to offer customers chips made in the United States without building an American factory itself. UMC could also earn income from intellectual property and revenue sharing, but the commercial terms are not yet clear, so we do not yet count on royalty income. The attraction today is the chance to win customers and expand the business through the partnership. 2. The longer-term driver is logic folding. In a conventional chip, the circuits sit on one layer and signals cross it along long horizontal wires. Folding arranges the circuits across two or more layers connected vertically, so many long horizontal wires become short vertical ones. Signals travel a shorter distance, which takes less time and less energy. The chip gets faster and more energy-efficient without smaller transistors. For UMC, folding could make chips built on its established processes more capable and easier to sell, which extends the value of its factories without matching the most advanced processes at $TSM. We described the mechanism in our Huawei series on the Kirin 9050. 3. We think a mature process is the more manageable place to start folding. Whoever folds chips has to solve bonding, heat removal and reliable high-volume production. UMC would solve those on a transistor process it already understands. Applying folding to TSMC's newest processes would combine two difficult manufacturing changes at once: a new generation of smaller, more complex transistors, and active circuits connected across several layers. A problem with either one can reduce the share of usable chips, raise costs or delay customer launches. This is a difference in the risks being combined. TSMC already offers advanced stacking technologies and has the expertise. 4. The commercial incentives differ as well. For UMC, folding extends the useful life of processes it already owns and lets it compete for business that would otherwise need a newer process. For TSMC, folding on older processes competes with the returns it expects from its leading-edge investments and could disrupt customer roadmaps built around those investments. So UMC has the stronger reason to become an advocate for folding on older processes. This is our prospective thesis about where folding is most likely to be adopted. UMC has not announced a logic-folding program. We have two reservations. UMC's shares have already recovered from their low, so the entry point is less attractive than it was. Logic folding could take years to contribute to revenue. The Intel partnership is our reason to add now. The chance to make UMC's existing processes more competitive is why we hold a larger position in UMC than in GlobalFoundries.
@convequity 1 click

Convequity on X

The $70bn revenue figure reported for OpenAI in late September was a gross-basis comparison number, not OpenAI's own. OpenAI's own run rate, the one it told investors, was approaching $50bn at the end of September. The number that now needs the same scrutiny is Anthropic's, before its IPO. The two labs count partner sales differently. When a customer pays $AMZN or $GOOGL for Claude, Anthropic records the full price as revenue and books the cloud's cut as a cost. OpenAI records only its own share of such sales. The $70bn was OpenAI's number grossed up to Anthropic's method so the two could be compared. Three things follow. 1. OpenAI's revenue did not fall. Its net run rate was approaching $50bn at the end of September. Yet the stocks that fell on Thursday were its suppliers: $ORCL, $CRWV and $NVDA. 2. Anthropic's $65bn run rate at the end of July is a gross figure. On OpenAI's basis it is smaller by whatever the cloud partners keep, and that share has not been disclosed. The claim that Anthropic has overtaken OpenAI rests on two numbers measured differently. 3. Which method applies is an accounting judgement about which company controls the sale to the customer, so Anthropic's prospectus for its planned November IPO may keep the gross figure, with the partners' share inside cost of revenue. That filing will show the cost line. OpenAI, still private, does not have to. In our view Thursday's selling hit the suppliers to the lab whose number did not change. The comparison investors should redo before November is Anthropic's $65bn against OpenAI's $50bn after the cloud partners' share is taken out of both.
@convequity 1 click

Convequity on X

Software multiples have fallen further since our January report. As of 7 Oct 2026, 238 companies in our all-software watchlist have EV/Sales (NTM) data on Koyfin. The median is 3.1x, down from 3.7x in January. The average is 5.4x, down from 6.2x. The 25th percentile is 1.8x, down from 1.9x. The 75th percentile is 5.5x, down from 6.1x. 191 of the 238 (80%) trade below our 6.7x private equity floor. 113 trade below 3x. The Bessemer Cloud Index shows the same pattern. Its median is 4.7x, down from 5.1x in January. 46 of its 68 companies (68%) trade below 6.7x. The cheapest are $CXM at 0.9x, $SPT at 1.1x, $MNDY at 1.7x and $WIX at 1.8x. In our watchlist, only 21 companies trade above 10x. The most expensive are $PLTR at 44.5x, $CRWD at 42.4x, $NET at 38.6x, $PANW at 24.2x, $DDOG at 19.5x and $SNOW at 16.3x. Growth still earns a higher multiple. The 44 names expected to grow revenue 20%+ a year over 3 years have a median of 5.2x. The 85 names expected to grow under 10% have a median of 2.6x. Even for the faster growers, the 5.2x median is below the floor. The market is paying up for very few names. We think that is right. Many software companies have slowing growth, high costs and no clear AI strategy. We would not buy the sector, or a cloud index, on valuation alone. In software, we focus on the few companies rebuilding their products around AI, and our SaaS Survival Scorecard tests key SaaS names against the pressure from AI agents.

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My Last GFL Update - Hopefully

GFL’s take-private structure hinges on BC Partners rolling 60% of its stake to preserve debt portability under the 40% permitted-holder…

GFL $16B
310 Value’s Newsletter 5 clicks

Are Neoclouds Dead?

Neoclouds face tighter debt financing as AI infrastructure capex outruns cash flow, leaving cash-burning GPU providers more exposed than…

NBIS $42B
Daniel Romero 9 clicks

Reddit: Deep Dive Analysis

Reddit generated $805 million in Q2 2026 revenue, 95% from ads, but slowing Google search referrals expose AI-driven traffic and…

RDDT $18B
Hated Moats 6 clicks

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