Bank of America resets Nvidia price target after earnings
Nvidia (NVDA) reported its Q4 earnings on Feb. 25 after the bell. Despite the earnings smasher, the stock is trading 5.6% lower at the time of writing, Thursday, Feb. 26, according to Yahoo Finance.
The stock’s crash after earnings, no matter how strong the report, has seemingly become the norm for Nvidia. So how can stock slide after reporting record quarterly revenue of $68.1 billion, up 20% sequentially, and up 73% year over year?
Nvidia CEO Jensen Huang explained this phenomenon at the all-hands meeting after the Q3 earnings. “If we delivered a bad quarter, it is evidence there’s an AI bubble. If we delivered a great quarter, we are fueling the AI bubble,” he said, as reported by Business Insider.
It is important to note that Huang doesn’t believe AI is a bubble.
Revenue of $78.0 billion, plus or minus 2%.
GAAP gross margin of 74.9%, plus or minus 50 basis points
GAAP operating expenses of approximately $7.7 billion Source: Nvidia
The company stated that it is not assuming any Data Center compute revenue from China in its outlook.
“While small amounts of H200 products for China-based customers were approved by the U.S. government, we have yet to generate any revenue, and we do not know whether any imports will be allowed into China,” said CFO Colette Kress during the earnings call.
The statement about no China Data Center sales and what the CFO said might seem like a possible reason for disappointment, but only if you have very unrealistic expectations.
Bank of America raised its Nvidia non-GAAP EPS estimate for 2027 to $8.11.Shutterstock ·Shutterstock
Following the report’s release, Bank of America analyst Vivek Arya and his team updated their view on Nvidia stock.
The team said Nvidia “more than delivered, with topline growth accelerating to 77% YoY” in Q1 guidance.
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Analysts raised their fiscal year 2027/2028/2029 non-GAAP EPS estimates by 5%/10%/13% to $8.11/$10.72/$13.18, respectively, and noted that they now include stock compensation expenses and embed a higher tax rate.
In a research note shared with me, Arya reiterated a buy rating for Nvidia stock and raised the target price to $300 from $275, based on 28 multiple of his estimate for price to earnings ratio excluding cash for calendar year 2027, which is within Nvidia’s historical forward year price to earnings range of 25 to 56.
Weakness in consumer driven gaming market
Competition with major public firms
Larger-than-expected impact from restrictions on compute shipments to China
Lumpy and unpredictable sales in new enterprise, data center, and autos markets
Potential for decelerating capital returns
Enhanced government scrutiny of Nvidia’s dominant market position in AI chips
The report shows how the industry is approaching achieving a return on investment (ROI) in core applications such as medical imaging and drug discovery. It also demonstrates that the industry is embracing open-source software and AI models to address specific use cases.
70% of respondents said their organizations are actively using AI, up from 63% in 2024.
82% said open source software and models are moderately to extremely important to their organizations’ AI strategy.
85% of executives said AI is helping increase revenue, and 80% said it’s helping reduce costs.
“Scaling generative AI in healthcare starts with focusing on real clinical and operational problems, rather than the technology itself,” said Annabelle Painter, clinical AI strategy lead at Visiba U.K.
“The organizations seeing impact are those that embed AI into existing workflows instead of layering AI on top as a separate tool.”
Sixty-one percent of respondents from medical technology said they’re using AI for medical imaging, such as radiologists using it to work more quickly and efficiently, while 57% from pharmaceutical and biotechnology said drug discovery is being driven by AI.
As a result of AI’s positive impact, 85% of respondents said their AI budgets would increase this year, with another 12% saying budgets would stay the same. 82% of survey respondents stated that open source is moderately to extremely important to their AI strategy.
“Open models will shape the intellectual field,” said John Nosta, president of NostaLab, a health care think tank.
“They are essential for exploration and for keeping the field honest. But in clinical environments where safety, liability, and accountability are non-negotiable, proprietary systems will remain necessary for validation, integration, and trust. The key insight here is that discovery will be open, and deployment will demand stewardship.”
