BN · rank #5 · 2026-07-21
LRCX
NASDAQ · $383.63B (USD)
The exact numbers the algorithm saw.
| Composite score Z-score blend of the factors below; drives the rank. | 0.78 |
|---|---|
| Forward revenue growth Consensus forward revenue growth. | +32.9% |
| Forward net margin Consensus forward net margin. | +33.1% |
| Net margin TTM Trailing twelve month net margin. | +30.9% |
| 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. | 1.81 |
| Debt / FCF Net debt relative to free cash flow. Lower is safer. | 0.58× |
| Analyst upside Spread between the consensus 12m target and the current price. | +20.0% |
| Last EPS surprise Most recent reported EPS versus consensus. | +8% |
| Market cap (USD) | $383.63B |
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 a leading wafer fabrication equipment supplier specializing in etch and deposition tools that are critical bottlenecks for producing advanced DRAM, NAND, and logic chips powering AI workloads.
Rationale
Record Q3 FY2026 revenue of $5.84B, Q4 guidance of up to $7.0B, 33% forward net margins, and explicit management commentary on AI-driven memory demand directly reinforce the bottleneck-solver thesis — Lam is structurally embedded in the AI chip supply chain, not merely riding sentiment rotation.
Material risks
- 1Escalating U.S. export controls on semiconductor equipment to China could materially curtail shipments to a significant revenue contributor, creating a sudden demand air pocket that would disconfirm the multi-quarter revenue visibility underpinning the thesis.
- 2A technology path shift — such as AI architectures reducing reliance on NAND or pivoting to novel memory substrates requiring fewer Lam-intensive etch steps — could erode its sole-source bottleneck position even as aggregate chip demand stays robust.
AI verdict council
Each pick is reviewed independently by 3 models before any order. 2 of 3 voted to proceed.