Investment bank HSBC and KeyBanc Capital Markets have issued bullish reports on Nvidia (NVDA), leading to a surge in the company’s stock price. HSBC reiterated its buy rating and increased its price target to $780, while KeyBanc raised its price target to $620. The stock jumped 6.4% to $460.70 following the reports.
Wedbush Securities analyst Daniel Ives highlighted the importance of Nvidia CEO Jensen Huang’s commentary on Wednesday’s earnings call. Ives referred to Huang as the “Godfather of AI” and stated that investors are eager to hear his insights on the demand for AI semiconductors, software, and services. Wedbush rates NVDA stock as outperform with a price target of $490.
KeyBanc analyst John Vinh believes that Nvidia will deliver better-than-expected fiscal second-quarter results, despite facing production constraints. Vinh noted that Nvidia gained additional production capacity at chip foundry Taiwan Semiconductor Manufacturing (TSM) due to the delay of rival AMD’s AI processor. Additional capacity was also found at semiconductor packaging and testing services provider Amkor Technology.
Analysts predict Nvidia will earn $2.08 per share on sales of $11.19 billion in the July quarter, indicating significant year-over-year growth. Rosenblatt Securities’ Hans Mosesmann expects demand for Nvidia’s AI chips to exceed supply by at least 50% in the coming quarters.
However, Jordan Klein, managing director at Mizuho Securities, cautioned investors to temper their expectations for Nvidia’s near-term outlook due to capacity constraints in the data center products segment.
Nvidia stock is included on IBD’s Leaderboard and Tech Leaders lists and ranks third out of 36 stocks in IBD’s fabless semiconductor industry group. The stock has an impressive IBD Composite Rating of 96 out of 99.
Sources:
- Investor’s Business Daily
Definitions:
- Fabless Chipmaker: A company that designs and markets semiconductor chips but does not maintain its own manufacturing facilities.
- AI Semiconductors: Semiconductors specifically designed for artificial intelligence applications, capable of performing complex calculations and data processing.
- Capacity Constraints: Limitations on a company’s ability to meet demand due to restricted production capacity.
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