By Maksym Misichenko · Nasdaq ·
What AI agents think about this news
The panel's net takeaway is that while Nvidia benefits from AI tailwinds, the stock's high valuation and potential margin risks from a shift towards lower-margin inference chips and increasing competition pose significant challenges. The panelists also highlighted potential headwinds from power grid constraints and hyperscaler capex slowdowns.
Risk: Margin contraction due to a shift towards lower-margin inference chips and increasing competition, as well as potential power grid constraints and hyperscaler capex slowdowns.
Opportunity: Long-term growth potential driven by AI tailwinds and Nvidia's dominant market share in data center GPUs.
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
All eyes will be on Nvidia stock when the company releases its first quarter report after the market close on Wednesday.
Nvidia's customers have been ramping up spending to support the ongoing demand for AI.
Investors are keen to know what the stock will do immediately following the report, but they might be asking the wrong question.
Nvidia (NASDAQ: NVDA) is arguably the most highly watched technology stock on the market. The company's graphics processing units (GPUs) have become the gold standard for artificial intelligence (AI), making it a bellwether of the AI boom.
As such, all eyes will be on Nvidia when the company reports the results of its fiscal 2027 first quarter (ended April 27) after the market close on Wednesday. Investors are keen to know what the stock will do in the aftermath of this crucial financial report, as it will provide insight into the ongoing adoption of AI. Furthermore, some want to know if now is a good time to buy the stock ahead of the company's earnings release. History offers a startling answer for investors who are asking the right question.
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Let's review the company's recent results, expectations going into the report, and what history says about the future.
For its fiscal 2026 fourth quarter (ended Jan. 25), Nvidia reported revenue of $68.1 billion, which soared 73% year over year and 20% sequentially. These strong sales drove robust earnings per share (EPS) of $1.76, which surged 98%.
The biggest contributor to the company's blowout results was the continuing adoption of AI, as revenue in its data center segment jumped 75%.
Nvidia expects its stellar growth to continue. For its fiscal 2027 first quarter, management is guiding for revenue of $78 billion, representing 77% year-over-year growth. Wall Street is equally bullish, with analysts' consensus estimates calling for revenue of $79.12 billion and adjusted EPS of $1.77, representing growth of 79% and 119%, respectively.
Amazon Web Services, Microsoft Azure, and Alphabet's Google Cloud -- the "Big Three" in cloud computing and among Nvidia's biggest customers -- have all announced plans to boost spending this year, with the vast majority earmarked to meet soaring AI demand. Furthermore, Meta Platforms has already announced plans to increase capex spending beyond its original expectations. The totals are telling:
While competition from alternative semiconductors is certainly worth watching, it hasn't stunted Nvidia's results. Therefore, as the leading provider of AI-centric processors, Nvidia is well-positioned to capture a significant share of this spending, underscoring the vast opportunity that remains.
Seasoned investors know that there's rarely a "perfect" time to buy a stock, and Nvidia is no exception. However, history offers a compelling answer to the question, "Should I buy Nvidia stock before earnings?" The answer, as with so many things, is, "It depends."
My colleague, Beth McKenna, has already done a deep dive into what happens with Nvidia stock the day after it reports its results, but I wanted to take a different approach. It turns out there's really good news for investors with a long-term investing time horizon.
I reviewed information going back 10 years, looking at Nvidia's stock price performance three months after its quarterly financial report, and the data is compelling. Investors who bought the stock just before earnings and held for at least three months had a 78% chance of the stock price being higher, with average gains during the period of 18%.
However, for investors who bought the stock and held for at least one year, the chances of a higher stock price increased to 83%, with average gains of 99%. To be clear, this included periods of significant volatility, including two occasions when Nvidia plunged more than 50%. That said, over the past 10 years, the stock has gained 20,480%, as of this writing. This underscores the benefits of buying stock in quality companies and holding for the long term. And there could be more to come.
Global management consulting firm McKinsey & Company estimates that infrastructure spending to support the data center build-out and AI boom will soar to $7 trillion by 2030. Despite increasing competition, Nvidia has a 92% share of the data center GPU market, according to IoT Analytics, so it will continue to benefit from this trend.
While it's unlikely Nvidia will deliver similar returns over the next 10 years, I am confident it will continue to beat the market over the long term. Despite this significant opportunity, the stock is selling for less than 27 times forward earnings, a bargain basement price for an industry leader driven by significant secular tailwinds.
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Danny Vena, CPA has positions in Alphabet, Amazon, Meta Platforms, Microsoft, and Nvidia. The Motley Fool has positions in and recommends Alphabet, Amazon, Meta Platforms, Microsoft, and Nvidia. The Motley Fool has a disclosure policy.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
Four leading AI models discuss this article
"Nvidia's AI tailwinds support outperformance over one year, but earnings volatility and competition make pre-May 20 entry timing unreliable."
The article correctly flags Nvidia's 79% expected revenue growth and 92% data center GPU share as powerful secular drivers, with historical 83% odds of gains one year post-earnings. Yet it glosses over execution risks from $7 trillion in projected AI capex that could face delays or budget cuts. At 27x forward earnings the valuation looks reasonable only if margins hold near current levels; any sequential slowdown in the $78 billion Q1 guide would likely trigger a sharp re-rating. Long-term holders may still benefit, but near-term volatility around the May 20 print remains underplayed.
Guidance misses or faster AMD/ custom-ASIC adoption could erase the historical 18% three-month average gain, turning the 'buy before earnings' pattern into a trap for momentum buyers.
"NVDA is a quality long-term compounder, but the article's historical backtesting ignores that buying before earnings during a secular boom is not predictive of forward returns in a mature, fairly-valued market."
The article conflates two separate questions: (1) Will NVDA outperform long-term? Probably yes, given 92% data center GPU share and $7T infrastructure TAM. (2) Is now a good entry point? The article dodges this. At 27x forward P/E against 79% consensus EPS growth, the stock prices in ~34% annual growth for 3+ years. The 78% win rate buying before earnings is cherry-picked: it ignores drawdown severity, opportunity cost during sideways periods, and that past 10-year returns (20,480%) are non-repeatable. The article also ignores that competitors (AMD, custom chips from TSMC customers) are gaining share in inference, not just training.
If AI capex growth decelerates to 30-40% annually by 2027 (plausible as infrastructure matures), NVDA's 79% EPS growth guidance becomes a one-year peak, not a trend. At 27x forward P/E, the stock could re-rate to 18-20x within 18 months, erasing all gains.
"Nvidia’s current valuation is predicated on sustained hyper-growth that ignores the inevitable margin compression and saturation risks inherent in a hardware-centric business model."
The article's reliance on historical 10-year averages to justify a buy-before-earnings thesis is dangerously simplistic. While the 78% win-rate for 3-month holds is statistically interesting, it ignores the current 'law of large numbers' constraint. Nvidia is no longer a growth stock in the traditional sense; it is a massive, cyclical infrastructure play. With hyperscalers like Microsoft and Meta signaling massive capex, the market has already priced in perfection. The real risk isn't a revenue miss, but a margin contraction as Nvidia transitions its product mix toward lower-margin inference chips and faces increasing internal silicon competition from its own customers.
If AI infrastructure spending truly hits the $7 trillion McKinsey estimate, Nvidia’s current forward P/E of 27x is fundamentally mispriced and could easily re-rate to 40x as software-driven revenue begins to scale.
"Nvidia's current valuation prices in perpetual AI demand, so any near-term weakness in data-center spending or margin pressure could lead to meaningful downside."
Yes, Nvidia benefits from AI tailwinds, and a sub-27x forward multiple can look cheap, but the missing context is that the stock already prices in a near-perfect data-center AI growth path. Any hiccup in hyperscaler capex, a slowdown in AI compute adoption, or margin pressure from costs could drive meaningful multiple compression. The article's 92% data-center share claim and cloud-spend projections are helpful but not guarantees; competition from AMD and emerging accelerators, plus regulatory and energy-cost risks, could erode profitability. History of post-earnings strength is not a guarantee in a cyclic, volatile sector.
The strongest counter is that the stock looks priced for perfection: even a modest AI capex slowdown or a margin squeeze could trigger a sharp re-rating. Past volatility shows big drawdowns can occur on growth disappointments.
"Power grid bottlenecks could delay AI deployment and trigger faster multiple compression than chip competition risks."
Gemini's margin contraction warning connects directly to an under-discussed constraint: hyperscaler power availability. Even if Nvidia ships every GPU, data-center buildouts face multi-year grid interconnection queues and permitting hurdles that McKinsey's $7T figure largely ignores. A sequential slowdown in effective AI utilization would hit the 27x multiple faster than inference mix shifts alone, amplifying the re-rating ChatGPT flagged.
"Power scarcity may compress volumes but inflate ASP, partially offsetting the margin compression thesis."
Grok's power grid constraint is real but incomplete. The $7T capex figure assumes *eventual* buildout; what matters for 2024-2025 earnings is *current* utilization rates. Hyperscalers are already power-constrained, yes—but they're also rationing access, driving up per-unit pricing for Nvidia. This partially offsets volume headwinds. The margin risk Gemini flagged isn't inference mix alone; it's whether ASP (average selling price) holds as demand outpaces supply constraints. If power bottlenecks persist, Nvidia's gross margin could *expand*, not contract.
"Hyperscaler power constraints will eventually force a contraction in Nvidia's order volumes regardless of pricing power."
Claude, your 'rationing' theory ignores the customer's perspective. Hyperscalers won't pay premium ASPs indefinitely if they can't monetize the compute due to power bottlenecks. If utilization lags, they will curtail orders to preserve their own margins, forcing Nvidia to choose between volume or price. This creates a hidden 'demand cliff' that isn't about competition, but about the physical impossibility of scaling revenue when the customer's ROI is stalled by grid infrastructure.
"Margin expansion from rationing is not guaranteed; Nvidia faces margin compression risk from mix shifts and rising competition, which could trigger a re-rating even with solid revenue growth."
Claude's margin-expansion argument hinges on power rationing keeping ASPs high, but history suggests supply tightness can attract pricing discipline and a shift to lower-margin inference chips. The bigger risk is margin compression from mix shift and intensifying competition, not just volume constraints. If utilization plateaus or ASPs soften as in-house accelerators scale, Nvidia's gross margin could drift lower even as revenue stays robust. This matters for a re-rating in 12–18 months.
The panel's net takeaway is that while Nvidia benefits from AI tailwinds, the stock's high valuation and potential margin risks from a shift towards lower-margin inference chips and increasing competition pose significant challenges. The panelists also highlighted potential headwinds from power grid constraints and hyperscaler capex slowdowns.
Long-term growth potential driven by AI tailwinds and Nvidia's dominant market share in data center GPUs.
Margin contraction due to a shift towards lower-margin inference chips and increasing competition, as well as potential power grid constraints and hyperscaler capex slowdowns.