BN · rank #12 · 2026-07-24
VRT
NYSE · $116.78B (USD)
The exact numbers the algorithm saw.
| Composite score Z-score blend of the factors below; drives the rank. | 0.29 |
|---|---|
| Forward revenue growth Consensus forward revenue growth. | +28.6% |
| Forward net margin Consensus forward net margin. | +15.3% |
| Net margin TTM Trailing twelve month net margin. | +14.4% |
| Margin expansion Forward minus trailing net margin (percentage points). | +0.9% |
| Forward PEG Forward P/E to growth. Below 1 is cheap for the growth. | 1.51 |
| Debt / FCF Net debt relative to free cash flow. Lower is safer. | 1.41× |
| Analyst upside Spread between the consensus 12m target and the current price. | +23.9% |
| Last EPS surprise Most recent reported EPS versus consensus. | +16% |
| Market cap (USD) | $116.78B |
The AI research card
Independent qualitative review of each pick before the order is placed. On the rare day the research service is unavailable, the paper book trades on the quant ranking alone and no card appears here.
Summary
Vertiv designs and manufactures integrated power distribution and thermal management systems that are embedded in hyperscale and colocation data centers as critical, hard-to-displace infrastructure.
Rationale
With 30% revenue growth, 430 bps of margin expansion, a 15%+ EPS beat, raised full-year guidance, and net leverage of just 0.2x, VRT is demonstrably solving the AI data center power-and-cooling bottleneck at scale with accelerating financial proof points that validate the quant signal.
Material risks
- 1Hyperscale customers (Microsoft, Google, Amazon) increasingly developing proprietary power and cooling architectures in-house is a credible disqualifier for the bottleneck-solver thesis, as it could structurally shrink Vertiv's addressable role in next-generation builds.
- 2A rapid industry shift toward alternative liquid or immersion cooling technologies where competitors hold stronger IP could commoditize Vertiv's thermal management portfolio and compress the margin expansion the thesis depends on.
AI verdict council
Each pick is reviewed independently by 3 models before any order. 1 of 3 voted to proceed.