BN · rank #8 · 2026-09-09
AMAT
NASDAQ · $375.20B (USD)
The exact numbers the algorithm saw.
| Composite score Z-score blend of the factors below; drives the rank. | 0.64 |
|---|---|
| Forward revenue growth Consensus forward revenue growth. | +34.5% |
| Forward net margin Consensus forward net margin. | +32.2% |
| Net margin TTM Trailing twelve month net margin. | +30.0% |
| Margin expansion Forward minus trailing net margin (percentage points). | +2.2% |
| Forward PEG Forward P/E to growth. Below 1 is cheap for the growth. | 0.90 |
| Debt / FCF Net debt relative to free cash flow. Lower is safer. | 1.31× |
| Analyst upside Spread between the consensus 12m target and the current price. | +35.6% |
| Last EPS surprise Most recent reported EPS versus consensus. | +4% |
| Market cap (USD) | $375.20B |
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
Applied Materials is a leading semiconductor wafer fabrication equipment supplier with broad process coverage across deposition, etch, and inspection for logic, memory, and advanced packaging customers globally.
Rationale
Three consecutive record revenue quarters in fiscal 2026, a 0.90x forward PEG, 34.5% forward revenue growth, and new DRAM-focused systems directly targeting AI memory scaling bottlenecks all reinforce the bottleneck-solver thesis with tangible revenue visibility rather than sentiment alone.
Material risks
- 1Export controls on China already carved out a ~$600M revenue hole and any further tightening—particularly targeting advanced logic or packaging equipment—could materially shrink the addressable market without an offsetting demand source at comparable margins.
- 2AMAT lacks sole-source status; Lam Research and Tokyo Electron compete across overlapping process steps, meaning customers under cost pressure or geopolitical scrutiny can credibly diversify away from AMAT tools, eroding the bottleneck premium over time.
AI verdict council
Each pick is reviewed independently by 3 models before any order. 3 of 3 voted to proceed.