Micron faces antitrust lawsuit and director investigation

2 min read     Updated on 07 Jul 2026, 12:38 AM
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AI Summary

Micron Technology, Samsung Electronics, and SK Hynix face a federal class-action lawsuit alleging they conspired to restrict DRAM supply and inflate prices. The complaint, filed June 25 in California, claims violations of the Sherman Act and notes a 700% price surge over four years. Concurrently, Scott+Scott Attorneys at Law LLP is investigating Micron's officers and directors for potential breaches of fiduciary duties related to the alleged price-fixing scheme.

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Micron Technology, Inc., Samsung Electronics Co., Ltd., and SK Hynix Inc. face a proposed federal class-action lawsuit alleging they conspired to restrict supply and inflate prices in the global DRAM market. The complaint, Garciaguirre et al. v. Samsung Electronics Co., Ltd. et al. (No. 3:26-cv-06345), was filed on June 25 in the U.S. District Court for the Northern District of California. The plaintiffs accuse the manufacturers of coordinating production cuts and pricing following the pandemic to artificially drive up memory prices and are seeking damages and injunctive relief under U.S. antitrust laws. Together, the three companies control roughly 90% of global DRAM production, a concentration that the lawsuit argues allows them to manipulate the market effectively. Separately, law firm Scott+Scott Attorneys at Law LLP launched an investigation into whether certain officers and directors of Micron breached their fiduciary duties related to these allegations.

Allegations and Market Impact

The lawsuit alleges violations of Section 1 of the Sherman Act, claiming that commodity DRAM prices have surged roughly 700% over the past four years. Plaintiffs argue that the three manufacturers used a synchronized pivot toward high-bandwidth memory (HBM) as a cover to quietly choke production of older DDR3 and DDR4 modules, thereby reducing mainstream supply and increasing prices. The squeeze has already impacted downstream costs; Apple Inc., not a defendant in the suit, has raised prices across its lineup, lifting its cheapest MacBook Pro by $400 to $1,999, citing memory and storage costs it could no longer absorb.

Legal Precedents and Industry Structure

Price-fixing claims in the memory market have historical precedent. In the early 2000s, the Department of Justice won a criminal DRAM case, with Samsung paying $300 million and Hynix $185 million in 2005, while Micron cooperated and avoided penalties. However, a more relevant precedent failed in 2018 when a near-identical class action was dismissed by Judge Jeffrey S. White in 2020. On March 7, 2022, the Ninth Circuit affirmed the dismissal, ruling the cutbacks were "more consistent with conscious parallelism" than collusion. The industry structure remains highly concentrated, with Samsung leading the market, followed by SK Hynix and Micron.

Investigation into Directors and Officers

Scott+Scott Attorneys at Law LLP is investigating whether Micron’s officers and directors failed to manage the company in an acceptable manner, resulting in damages to Micron and its shareholders. The firm is examining Micron’s participation in the alleged computer memory price-fixing scheme. Shareholders of Micron common stock are being encouraged to join the investigation to determine their rights regarding potential breaches of fiduciary duties.

Investor Outlook and Next Steps

For investors, the lawsuit strikes at the industry's pricing power, a key bullish argument for memory stocks. A motion to dismiss is expected in the coming months. If the complaint is dismissed, similar to the 2018 case, the impact on memory stocks is likely to be minimal. However, if plaintiffs survive dismissal and obtain discovery into internal company communications, the litigation could pose a longer-term risk. Micron, as the only primary U.S.-listed company among the defendants, is the stock most exposed to investor reaction, having rallied over 300% year-to-date prior to the filing.

How will the court distinguish this case from the 2020 dismissal to overcome the 'conscious parallelism' defense?

What impact will the shift toward High-Bandwidth Memory (HBM) production have on the long-term supply and pricing of legacy DDR modules?

Could potential discovery of internal communications reveal explicit collusion that alters the legal trajectory for the defendants?

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Chip selloff is a bear trap amid $1.5 trillion AI buildout

2 min read     Updated on 07 Jul 2026, 12:24 AM
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Radhika SScanX News Team
AI Summary

Bank of America analyst Vivek Arya views the recent semiconductor selloff as a bear trap, forecasting global AI spending to reach $1.5 trillion by 2027. The firm identifies seven stocks, including Micron Technology as a top pick, poised to benefit from AI capital expenditures. Arya argues that memory is becoming a strategic AI enabler, dismissing fears that open-source AI models will hurt chip demand.

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The recent decline in semiconductor stocks represents a bear trap rather than a structural shift, according to Bank of America analyst Vivek Arya. The PHLX Semiconductor Index, tracked by the iShares Semiconductor ETF (NASDAQ: SOXX), fell 11% since the start of the third quarter following an 88% surge in the second quarter. This pullback occurred during the sector's historically weakest seasonal window, but the underlying driver of artificial intelligence infrastructure spending continues to accelerate.

Global cloud and AI infrastructure spending is on track to approach $1.5 trillion by 2027, marking a 40% to 50% increase year over year. Arya expects leadership to shift back toward companies directly tied to AI capital expenditures as visibility into 2027 spending improves during the second half of the year. Hyperscalers remain focused on maximizing AI utilization rather than cutting infrastructure spending, which should sustain demand for chips powering AI data centers.

Top AI Capital Expenditure Plays

Bank of America has identified seven companies positioned to win the AI buildout. These firms are leveraged to the ongoing capital spending cycle by hyperscalers and cloud providers.

Company Ticker Exchange
Advanced Micro Devices Inc. AMD NASDAQ
Applied Materials Inc. AMAT NASDAQ
Lam Research Corp. LRCX NASDAQ
Micron Technology Inc. MU NASDAQ
MACOM Technology Solutions Holdings Inc. MTSI NASDAQ
Credo Technology Group Holding Ltd. CRDO NASDAQ
Marvell Technology Inc. MRVL NASDAQ

Micron Technology: Top Pick

Micron Technology stands out as Bank of America's top pick, described by Arya as one of the market's biggest AI mispricings. Memory now accounts for roughly 35% to 40% of AI cloud capital spending, more than double historical levels. Despite this, memory stocks trade at modest valuation multiples due to investor concerns about traditional boom-and-bust pricing cycles.

Arya argues that memory is transitioning "from a cyclical commodity to a strategic AI enabler." Long-term supply agreements between memory suppliers and hyperscale customers are fundamentally changing industry economics by making pricing more durable and revenue streams more predictable. This shift could allow memory companies to command higher valuation multiples. The firm reiterated its Buy rating on Micron and maintained a $1,550 price target, implying roughly 59% upside from current levels.

Open-Source AI Impact

Concerns that increasingly capable Chinese open-weight AI models could reduce semiconductor demand are unfounded, according to the report. While lower-cost AI models may pressure software economics, Bank of America believes they will expand AI adoption by making inference cheaper and accelerating deployment. The report notes that broader AI usage will require more compute, memory, networking, and power infrastructure over time, posing a risk to model economics rather than semiconductor demand.

What specific catalysts in the second half of the year will likely provide the necessary visibility into 2027 spending to trigger a sector rotation?

How will the valuation multiples of other top picks like AMD and Marvell compare to Micron if the broader market accepts the shift from cyclical commodity to strategic AI enabler?

What are the potential supply chain bottlenecks that could emerge as hyperscalers accelerate infrastructure spending toward the projected $1.5 trillion mark?

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