Nvidia stock rose nearly 7% in after-hours trading Wednesday. The reason? It beat expectations and raised guidance. After rising 229% so far in 2023, is it too late for investors to profit from buying Nvidia stock?
I see two reasons its stock could hit $1,000:
- Nvidia targets a large, fast-growing industry
- Nvidia’s competitive advantages suggest it will continue to be the market leader
Nvidia’s Great Q2 Financial Report
Nvidia designs semiconductors for gaming, data centers, and automotive vehicles industries — while outsourcing their manufacturing.
Revenue soared in its fiscal 2024 second quarter. which ended in July. Nvidia stock is soaring on its forecast for explosive Q3 revenue growth driven by demand for AI chips.
- Q2 Revenue: up 88% to $13.51 billion — about $3.3 billion ahead of the consensus forecast of $11.22 billion, according to Refinitiv.
- Q2 adjusted earnings per share: $2.70 — 61 cents more than expected. Earnings: $2.09 per share, according to Refinitiv.
- Q3 revenue forecast: $16 billion — $3.4 billion above estimates, according to CNBC.
Most of its revenue growth came from selling chips to data centers. Here is the revenue breakout by division:
- Data center revenue: $10.3 billion — $2.27 billion more than forecast
- Gaming revenue: $2.49 billion — $110 million above estimates.
Nvidia’s Large Addressable Market
The company has ample room to grow given a total addressable market Nvidia estimated in February 2023 at $1 trillion. The opportunity breaks down by industry as follows:
- Automotive: $300 billion
- Chips and Systems: $300 billion
- Nvidia AI Enterprise Software: $150 billion
- Nvidia AI Omniverse Software: $150 billion
- Gaming: $100 billion
Investors are most excited about Nvidia’s AI business which the company reports within the data center line item. Data center revenue increased 41% in 2022 — surpassing gaming revenue where Nvidia began competing in 1993, according to CNBC.
Nvidia’s Market Dominance And Competitive Advantages
Nvidia dominates the AI chip market — with 80% or more market share, according to CNBC — and has been building competitive advantages for 15 years to sustain its leadership position.
Nvidia’s Differentiation Strategy
If a company wants to lead its industry, it must choose one of two strategies:
- Differentiation — where the company delivers more value to customers than competing products and charges a price premium; and
- Low Cost Producer — where a competitor sets its price well-below the industry average and reaps scale economies enabling it to reduce its costs below its price.
Nvidia is a differentiator. After all, customers are willing to pay a significant price premium and to wait for over a year to obtain its chips. According to the New York Times
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Nvidia chips are expensive; however, the company argues they enable companies to save time training their Large Language Models — which more than offsets the the price premium.
The price for each Nvidia H100 ranges from $15,000 to more than $40,000. AWS Vice President David Brown said Amazon’s AI chips are a bargain compared to Nvidia’s. Nvidia CEO Jensen Huang disagrees. “If you can reduce the time of training to half on a $5 billion data center, the savings is more than the cost of all of the chips. We are the lowest-cost solution in the world,” the Times noted.
Nvidia’s Competitive Advantages
Nvidia’s competitive advantages flow from its ability to adapt to new opportunities faster than rivals and a page it took from Apple
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Naveen Rao is an entrepreneur who sold his startup that built GPU chips for gaming and AI to Intel. Rao saw Nvidia adapting GPUs for AI far more rapidly than did Intel. He left Intel and started a software company, MosaicML where he compared Nvidia chips to rivals’. Rao told the Times, “Everybody builds on Nvidia first. If you come out with a new piece of hardware, you’re racing to catch up.”
Nvidia’s competitive advantages make it difficult for rivals to gain market share. The Times reported these competitive advantages include:
- Lanching CUDA. In 2006, Nvidia announced CUDA — software for programming GPUs for other fields such as physics or chemical simulation. In 2012, researchers used the chips to identify a cat with precision
- Hiring an AI team. Nvidia hired a team to train LLMs — gaining early insights into what AI practitioners wanted. Using that market intelligence, Nvidia built libraries — to perform tasks common to AI development — thus saving developers time.
- Building faster chips every few years and expanding to complete computers. Nvidia consistently delivered faster chips every few years. In 2017, it began tailoring GPUs to handle specific AI calculations, sold chips or circuit boards for other companies, and provided complete computers aimed at faster AI processing.
- Launching H100 chips. In September 2022, Nvidia announced production of H100 chips to enhance transformer operations — which are essential for training ChatGPT and other Generative AI chatbots.
- Forming partnerships with big tech companies and investing in startups. Nvidia collaborates with large technology companies such as ServiceNow
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These competitive advantages are difficult for rivals to copy. Moor Insights semiconductor analyst Patrick Moorhead told CNBC, “Nvidia has a double moat right now in that they they have the highest performance training hardware. Then on the input side of the software, in AI, there are libraries and CUDA.”
Nvidia’s competitive advantages suggest significant growth potential. CoreWeave, a cloud provider that sells access to Nvidia GPUs, generated $30 million in 2022 revenue and has contracted for $2 billion in business in 2024, the Times reported, representing a 716% compound annual growth rate.
Where Does Nvidia Stock Go From Here?
Heavy options trading ahead of Nvidia’s announcement suggested many are afraid to miss out on the upside. Matthew Tym, head of equity derivatives trading at Cantor Fitzgerald, said “This name in particular is full of FOMO, and people do not want to miss out on it,”the Journal reported.
Analysts expect Nvidia stock to rise. FacSet noted the 50 investment analysts covering the stock set an average price target around $537, or 18% above Tuesday’s close of $456.68. The most optimistic analyst is Warren Lau at Aletheia Capital with a price target of $1,000.
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