Potential Drop in Nvidia's Share Price to Reach $65
Potential Drop in Nvidia's Share Price to Reach $65
Could Nvidia shares decrease around 50% to roughly $65 in the impending future, given they're currently priced at around $130? We believe this scenario is plausible. Nvidia has experienced significant growth, driven primarily by the escalating demand for its graphics processing units, which have become the go-to silicon for executing artificial intelligence applications. However, there are potential threats on the horizon. These include a potential decrease in AI-related training demands, escalating competition, and lower valuation multiples assigned by investors due to decelerating growth and less appealing monetary policies. We delve deeper into Nvidia's key hazards and explain how the shares could decrease by over 50% from their current value by examining three aspects, namely the company's revenue growth, profit margins, and price-to-earnings ratio. For a contrasting perspective, check out our assessment on Nvidia Shares: Potential Gain to $300. Indeed, we believe that this wide range of potential gains and losses demonstrates that Nvidia is an inherently volatile stock. While AI has been a popular topic, quantum computing could be the next major breakthrough. See our analysis on What's Driving D-Wave Quantum Shares? and also Palantir Shares: Buy, Sell, or Hold?
Reasons for Possible Revenue Decline
Nvidia's revenues have grown at an unprecedented pace. In the previous 12 months, Nvidia's revenues surged by almost three times, thanks to companies intensifying their use of accelerated computing with GPUs to conduct more artificial intelligence tasks. However, growth is beginning to slow down. In the most recent quarter, Nvidia's sales increased by approximately 122%. It's possible that growth may continue to slow, potentially even resulting in declining sales compared to current levels in the medium term. Here's why:
Waning demand for model training
Companies have invested massive resources in building AI models over the past two years or so. Now, training these extensive models is more of a one-time affair that requires substantial computing power, and Nvidia has greatly profited from this, as its GPUs are renowned for being the fastest and most efficient for these tasks. However, the AI landscape may be transitioning. Incremental performance improvements are anticipated to diminish as models expand in size, considering various parameters. Additionally, the availability of high-quality data for training models could become a bottleneck, as much of the internet's high-quality data has already been processed through large language models. Given these factors, the heavy front-loading phase of AI training may be coming to an end. Furthermore, as shareholders seek better returns, we may witness a cooling off in capital spending on GPU chips, impacting companies like Nvidia. Separately, if you're seeking upside potential with a smoother ride, consider the *Quality Portfolio, which has outperformed the S&P and has recorded returns exceeding 91% since its inception.
Nvidia’s GPUs may be overkill for inference
The main focus of AI will be on inference, where trained models are applied in practical applications. This phase is less computationally demanding, making room for alternative AI processors that are less powerful. To be clear, Nvidia may continue to be the market leader in inferencing, but there is an opportunity for rivals such as AMD and possibly even Intel to gain market share with chips like AMD's MI300 chips or Intel's Gaudi AI accelerators. Nvidia's high-end chips, like the H100, may be considered overkill for simpler inference tasks, considering their high power consumption and initial cost.
Enhanced supply-demand balance
There are indications that the substantial supply-demand imbalance observed during the initial phase of the generative AI wave is starting to normalize. For instance, Microsoft, one of Nvidia's largest GPU customers, recently stated that it was no longer constrained in terms of GPU supply. The fact that Nvidia's largest customer has sufficient chips to support its AI endeavors suggests that the intense "fear of missing out" phase for GPU demand might be a thing of the past. Moreover, if demand stabilizes at the same time that supply catches up, Nvidia may face pricing pressures or slower sales growth, particularly if prominent customers reassess their inventory requirements.
Currently, Nvidia’s revenues are projected to more than double in FY'25 (2025) to approximately $129 billion, based on market consensus. However, if its growth rates decline substantially from this point, to around 10% over the subsequent two years, revenue could decrease from roughly $61 billion in FY'24 to about $165 billion in FY'27.
Potential Margin Challenges
Nvidia's margins (net income, or profits after all expenses and taxes, calculated as a percentage of revenues) have been showing a positive trend - they rose from around 25% in FY'19 to approximately 49% in FY'24, as the company experienced better economies of scale and a more favorable product mix leaning towards complex data center products. Our dashboard delves deeper into the various factors responsible for *Nvidia’s net income change.*
Competitive pressure is intensifying in the semiconductor market, with companies like AMD investing heavily to boost their presence. AMD asserts that its new Instinct MI300X chip surpasses Nvidia's current offerings in multiple aspects, while Intel is also aiming to carve out a niche with affordable AI chips. Furthermore, major tech players such as Google, who are significant Nvidia clients, are increasing their commitment to AI and machine learning technology. This competitive landscape is likely to challenge Nvidia's revenue expansion rates and historically high profit margins.
Recently, Amazon unveiled plans to establish an AI supercomputer, known as an ultracluster, utilizing its own Trainium chipsets. Amazon is not only investing in its own AI solutions but also promoting them to other businesses, such as Apple, which reportedly utilizes Amazon's AI chips for certain functions, like searching. This could potentially impact Nvidia's market position and profitability.
Debating whether to sell Nvidia shares and invest in Intel stock is a valid consideration given Nvidia's inconsistent returns over the past 4 years. Annual fluctuations in Nvidia stock have been more pronounced than those of the S&P 500, with returns of 125% in 2021, -50% in 2022, and 239% in 2023. In this context, the Trefis 'High Quality Portfolio,' comprising of 30 stocks, has delivered less volatility and consistently outperformed the S&P 500.
Given the current economic uncertainties and expected changes in the AI landscape, what could unfavorable consequences be for Nvidia's stock? If revenue growth increases by approximately 1.2x (20%) between fiscal years 2025 and 2027, and margins diminish from the current 50% to around 35% (a 30% reduction from the present levels, equating to 0.7x), net income could potentially decrease by around 15% by 2027. Consequently, a decrease in earnings might alter the investor's perspective towards Nvidia as a growth stock, leading to a descent in P/E ratios.
As interest rates evolve, high multiple tech stocks, such as Nvidia, may feel the impact. The Federal Reserve's latest meeting indicated a slower pace of rate cuts, reducing the anticipated number of quarter-point reductions in 2025 from an average of four in September to two at present. This shift may suggest the end of the era of extremely low interest rates during the Covid-19 pandemic. If the P/E ratio for Nvidia dips from its current multiple of around 44x to approximately 25x, this could result in a decline in Nvidia stock to about $65 per share.
Regarding the timing of this adverse return scenario, it may not significantly impact the outcome, whether it takes 2 or 3 years. If the competitive threat unfolds and Nvidia's GPU business encounters challenges, we might expect a substantial correction in Nvidia stock.
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The potential decrease in AI-related model training demands and the shift towards less computationally demanding inference tasks could negatively impact Nvidia's revenue growth. Additionally, Nvidia's high-end GPUs, like the H100, may be considered overkill for simpler inference tasks, providing an opportunity for rivals to gain market share.
Nvidia's current valuation multiples could decrease due to less appealing monetary policies and decelerating growth, which could lead to a significant decrease in its stock price. For instance, if the P/E ratio for Nvidia dips from its current multiple of around 44x to approximately 25x, Nvidia stock could decline to about $65 per share.