BN · rank #9 · 2026-10-26
LRCX
NASDAQ · $287.95B (USD)
The exact numbers the algorithm saw.
| Composite score Z-score blend of the factors below; drives the rank. | 0.43 |
|---|---|
| Forward revenue growth Consensus forward revenue growth. | +20.6% |
| Forward net margin Consensus forward net margin. | +33.8% |
| Net margin TTM Trailing twelve month net margin. | +32.3% |
| Margin expansion Forward minus trailing net margin (percentage points). | +1.5% |
| Forward PEG Forward P/E to growth. Below 1 is cheap for the growth. | 1.45 |
| Debt / FCF Net debt relative to free cash flow. Lower is safer. | 0.56× |
| Analyst upside Spread between the consensus 12m target and the current price. | +58.2% |
| Last EPS surprise Most recent reported EPS versus consensus. | +1% |
| Market cap (USD) | $287.95B |
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
Lam Research is the dominant supplier of deposition, etch, and clean wafer-fabrication equipment, with nearly every advanced chip built on its tools and a growing installed-base services business generating recurring revenue.
Rationale
The bottleneck-solver thesis is directly reinforced by management's explicit statement that demand exceeds tool availability, 8–10 new Tier 1 clean rooms are coming through 2027, and Lam's WFE share could expand from the low-30% to high-30% range — structural supply constraint, not sentiment rotation.
Material risks
- 1China concentration at 35% of revenue creates binary export-control risk; a single regulatory tightening could immediately remove Lam's largest geographic segment while simultaneously handing captive share to domestic Chinese competitors.
- 2Supply-chain and manufacturing-capacity constraints are currently preventing Lam from converting record customer demand into shipments, meaning near-term revenue and margin could disappoint even as the long-term thesis holds.
AI verdict council
Each pick is reviewed independently by 3 models before any order. 3 of 3 voted to proceed.