On the eve of financial reports, Micron's "super bulls" reiterate their target price of $2,000
The Block
50m ago
Ai Focus
D.A. Davidson analyst Jill Luria reiterated her $2,000 target price ahead of Micron Technology's earnings report, stating that AI is driving strong demand for memory, and there is a supply shortage of HBM and advanced DRAM, with the storage industry cycle still in a super cycle.
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Among the Wall Street analysts who are bullish on memory chip company Micron Technology (stock code: MU), Jill Luria of D.A. Davidson is arguably the most aggressive, and she can be called Micron's "super bull".

This storage vendor is set to release its financial report on Wednesday. On Monday, Luria reiterated a target price of $2,000, which is close to the highest level seen on Wall Street, implying a potential increase of about 100% from the current stock price. According to Yahoo Finance data, analysts have an average target price of $1,520 for Micron.

Consistent with Luria's previous research reports on Micron, this investment logic is highly coherent.

Luria stated, "Memory is a key component for running the AI large model, and that will not change. The larger the memory, the better the model performance; the larger the memory, the faster the inference speed; the larger the memory, the longer the context window. All participants in the market have repeatedly indicated that their own memory supply falls far short of demand. Demand continues to soar, while any new supply is not expected to be available for at least another year. The current market valuation multiples were determined at the end of the pricing and storage cycle, but the demand for AI computing power continues to rise. Recently, the Muse launched by Meta ( META ) has been a great success, and this innovative feature at the interaction level has opened up new application scenarios for consumers. Just a few weeks ago, we were concerned that the storage demand brought about by Meta would weaken, but now that possibility seems very low."

Luria added, "This current storage industry cycle is a true super cycle. There is a mismatch in expectations in the market: investors predict that the storage cycle has come to an end, yet they are optimistic about the continued growth of CPU before 2030. We believe that the AI macro-cycle is a complete cycle that encompasses GPU, CPU, and storage as a trinity. Therefore, the price-earnings ratios of AMD ( AMD ) and Intel ( INTC ) remain at 40-60 times, while Micron's price-earnings ratio is only 7 times."

AI The high-bandwidth memory used by servers, HBM along with advanced technologies, DRAM are in persistent short supply, and the supply and demand in the storage chip market have significantly tightened.

Companies such as NVIDIA ( NVDA ), Microsoft ( MSFT ), Amazon ( AMZN ), and Meta ( META ) are making every effort to build the infrastructure for AI. For most of 2026, the high-end AI storage production capacities of companies like Hynix, Samsung Electronics, and Micron were basically sold out.

Especially the HBM3E and HBM4 products from Micron are in high demand; they are essential hardware components when paired with NVIDIA's AMD AI acceleration chips.

After several years of decline in the industry, the situation of a shortage of storage chips has significantly enhanced the bargaining power of storage manufacturers. Industry experts predict that the tight supply of memory will continue until 2027, creating a favorable environment for leading storage manufacturers such as Micron and SanDisk ( SNDK ).

Jaye Kwon, an analyst at JPMorgan Chase, stated: "The increase in unit price, coupled with an increase in shipments, is driving the continuous expansion of the potential storage market size; the supply-demand gap will continue over the next two years. Investors have underestimated the trend of memory demand spreading from GPU to CPU. Although this logic is well-known within the industry, the actual impact on supply and demand has been overlooked by the market, and this is also an important source for upward revisions in future demand forecasts."

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