BN · rank #15 · 2026-07-21
NVMI
NASDAQ · $13.78B (USD)
The exact numbers the algorithm saw.
| Composite score Z-score blend of the factors below; drives the rank. | 0.26 |
|---|---|
| Forward revenue growth Consensus forward revenue growth. | +21.6% |
| Forward net margin Consensus forward net margin. | +29.7% |
| Net margin TTM Trailing twelve month net margin. | +29.2% |
| Margin expansion Forward minus trailing net margin (percentage points). | +0.5% |
| Forward PEG Forward P/E to growth. Below 1 is cheap for the growth. | 1.46 |
| Debt / FCF Net debt relative to free cash flow. Lower is safer. | 4.12× |
| Analyst upside Spread between the consensus 12m target and the current price. | +39.3% |
| Last EPS surprise Most recent reported EPS versus consensus. | +6% |
| Market cap (USD) | $13.78B |
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
Nova Ltd is a semiconductor process control and metrology company supplying optical, X-ray, and chemical measurement systems to advanced logic, memory, and packaging fabs globally.
Rationale
NVMI screens validly as a bottleneck-solver because rising 3D complexity in HBM/advanced packaging structurally increases metrology intensity, Nova holds specialized IP with long qualification cycles that create sticky repeat revenue, and record Q1 2026 adoption of Metrion and AncoScene confirms the thesis is active rather than speculative.
Material risks
- 1KLA or Onto Innovation could displace Nova at a key memory or logic customer through broader portfolio bundling, eroding the sole-source qualification advantage that underpins revenue visibility and the bottleneck-solver moat.
- 2A deceleration in AI/HBM capex from hyperscalers or DRAM manufacturers would disproportionately hit Nova given its concentrated exposure to advanced packaging and memory, which have been the primary growth drivers in recent quarters.
AI verdict council
Each pick is reviewed independently by 3 models before any order. 2 of 3 voted to proceed.