The selloff came despite Marvell reporting solid results and raising its revenue outlook for fiscal 2027 and 2028. Investors had been looking for stronger signs of growth after the company’s stock nearly tripled this year amid the artificial intelligence spending boom, Reuters reported.
Marvell’s shares fell to about $221.60 in early trading, putting the company on track to lose more than $17 billion in market value if the decline holds.
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Much of the focus has centered on Marvell’s agreement with Google to develop custom AI chips. The deal could generate as much as $120 billion in revenue through fiscal 2033, but investors are now seeking greater clarity on when that revenue will begin making a meaningful contribution.
CEO Matt Murphy said some Google-related revenue is already reflected in Marvell’s custom-chip revenue targets through fiscal 2028, while the deal is expected to have a much larger impact beginning in fiscal 2029.
Analysts at Morgan Stanley said investor expectations had been particularly high because of the Google agreement and noted that much of its potential upside was already incorporated into Marvell’s previous guidance.
Marvell expects revenue to grow by about 45% in fiscal 2027 and reach roughly $18 billion in fiscal 2028, helped by stronger demand from data centers.
Despite Friday’s decline, analysts remain optimistic about the company’s longer-term prospects. At least eight brokerages raised their price targets following the results, with a median target of $275, according to LSEG data.
Analysts have pointed to the Google agreement, potential business with Microsoft and growing demand for AI connectivity products as possible sources of significant future growth.
However, Marvell’s valuation leaves little room for disappointment. The company trades at a 12-month forward price-to-earnings ratio of about 58, compared with roughly 32 for rival Broadcom, according to LSEG.
The sharp market reaction highlights the challenge facing AI-linked chip companies: with investor expectations already elevated, strong results may no longer be enough unless companies can demonstrate when major AI contracts will translate into substantial earnings.
