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Market News/Micron Price Target Raised by UBS on Memory Super-Cycle Outlook

Micron Price Target Raised by UBS on Memory Super-Cycle Outlook

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Updated Apr 12, 2026

·1 min read
Market News

UBS raised its price target on Micron Technology (NASDAQ:MU) to $535 from $510, while maintaining a Buy rating, citing continued strength in memory markets.

The firm acknowledged that investor sentiment toward the memory sector has weakened following Micron's recent gross margin guidance but maintained its view that the industry is in the midst of a super-cycle that could challenge traditional valuation frameworks.

UBS noted that industry checks indicate ongoing strengthening in pricing for both DRAM and NAND, particularly in high-bandwidth memory (HBM), which is expected to support margin expansion.

The firm also pointed to active negotiations between memory suppliers and hyperscalers, as well as OEMs, involving long-term agreements that include volume commitments, prepayments, and defined pricing structures.

Hyperscalers are reportedly seeking longer-term contracts for HBM, while suppliers such as Micron, SK Hynix, and Samsung are expected to re-establish premium pricing for HBM by 2027.

In the NAND market, UBS observed that not all suppliers are equally motivated to enter long-term agreements, with some preferring to maintain flexibility in capacity allocation.

The firm concluded that memory companies appear increasingly willing to trade short-term upside for improved long-term visibility, which could result in more stable earnings, margins, and returns on equity.

UBS expects potential supply shortages to persist into 2028, particularly in DRAM. It forecasts Micron earnings per share of approximately $135 in 2027 and $120 in 2028, both above Street estimates.

The firm also projected that Micron's tangible book value could reach around $180 per share within a year, with cash holdings exceeding $100 billion, or roughly 25% of its current market capitalization.

Tags:MU

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David Kirakosyan writes the Weekly Signals Desk for FMP, breaking down market signals while showing readers how to build similar workflows using the FMP API. His work focuses on turning raw API data into practical market analysis and repeatable workflows that developers and analysts can adapt to their own research.

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