Source: Zhitong Finance "Since 1950, the S&P 500 index has risen more than 10% 21 times as of the end of May. In about 90% of these cases, the S&P 500 index rose for the rest of the year. There were only two instances of declines for the rest of the year, in 1987 (-13%) and 1986 (-0.1%)." With the rebound of the stock market, the old adage "Sell in May and Go Away" seems to have been a bad advice once again. Last month, the S&P 500 index rose 4.8%, the best May performance since 2009. The NASDAQ 100 index rose nearly 6.2%, and the NASDAQ Composite Index rose 6.9%. Goldman Sachs FICC & Equities Trading Division said: "History doesn't really support this saying. Don't sell, leave the market (go on vacation), and enjoy the good times." The rising trend is still to be continued? If history is any guide, it may indicate that the rise of the stock market is not over yet. Looking ahead to the rest of 2024, Scott Rubner, Managing Director of the Goldman Sachs Global Markets Division and tactical expert, pointed out the following historical background for investors. Rubner stated that the S&P 500 index has risen 10.7% year-to-date, and since 1950, the S&P 500 index has risen more than 10% 21 times as of the end of May. In about 90% of these cases, the S&P 500 index rose for the rest of the year. There were only two instances of declines for the rest of the year, in 1987 (-13%) and 1986 (-0.1%). "Since 1950, the median return of the last 7 months of each year (June 1 to December 31) is 5.4%. In the aforementioned 21 cases, the average performance of the last 7 months increased to 8.1%." Rubner added. Rubner also pointed out that the NASDAQ index has risen for 16 consecutive Julys, with an average return of about 4.64%.

The well-known Wall Street investment institution Rosenblatt recently released a heavy research report, whose core content is based on the potential prosperity of NVIDIA's software business based on CUDA, even if the AI chip overlord's stock price has risen more than 210% in the past year. However, the stock price of the chip giant will continue to rise in the next 12 months. It is expected that NVIDIA's stock price will be 50% higher than its current level.$NVIDIA (NVDA.US)$According to the official NVIDIA website, using NVIDIA GPUs for CUDA general accelerated computing programming and some basic tools is a free way, but if it involves CUDA enterprise-level large-scale applications and support (such as NVIDIA AI Enterprise), or renting NVIDIA computing power on cloud platforms (such as Amazon AWS, Google Cloud, Microsoft Azure) to develop AI systems with subscription-based CUDA microservices, additional fees may be required.

This is the view of Rosenblatt chip industry analyst Hans Mosesmann, who in this research report raised the institution's target stock price for NVIDIA from $140 per share to a stunning $200 per share within 12 months, ranking it as the highest target price for NVIDIA on Wall Street.

Mosesmann reiterated his "buy" rating on NVIDIA in the research report, which also suggests that the total market value of the "Global Stock Market New King" NVIDIA, which recently first became the "world's most valuable listed company", may reach $5 trillion within 12 months. Currently, excluding the overnight gain in the U.S. stock market, NVIDIA's total market value is as high as $3.34 trillion, surpassing the two old-tech giants Apple and Microsoft, and is far ahead of cloud computing giants Google and Amazon.

In late May, NVIDIA, the AI chip leader praised by Goldman Sachs as the "most important stock on earth," released an unprecedented performance that shocked global investors, dispelling concerns about spending declines in AI-related enterprises. NVIDIA has once again strengthened tech-stock investors' "AI beliefs" all by itself, driving the continued rise of U.S. tech stocks in recent days and also fueling NVIDIA's stock price to start a new round of crazy gains, repeatedly setting new highs to shock investors.

Nvidia's total Q1 revenue in 2024 increased by 262% to US $26 billion, with total revenue reaching a historic high, and the YoY growth rate of total revenue exceeding 200% for three consecutive quarters. Under the impetus of strong demand for H100/H200 GPUs, Nvidia's Q1 data center revenue reached a historic high of $22.6 billion, up 427% YoY.

In Mosesmann's view, NVIDIA's market value deserves the $5 trillion mark. "We've seen NVIDIA's Hopper, Blackwell and Rubin series AI GPU architectures drive 'value market' share in one of Silicon Valley's most successful silicon chip and platform product cycles," Mosesmann stressed.

The software business based on CUDA may be NVIDIA's new revenue engine.

Looking ahead, analyst Mosesmann said NVIDIA's truly powerful source of profit comes not only from its AI GPU products focused on AI hardware infrastructure, but also from NVIDIA software business, which is led by the popular CUDA software-hardware co-development platform of NVIDIA. That is, "CUDA+AI GPU" together form NVIDIA's extremely powerful moat. At present, millions of software developers worldwide cannot do without NVIDIA's CUDA platform, which is indispensable for building and updating large language models and other AI applications on artificial intelligence training/inference systems, such as ChatGPT. "The real story is the completeness of the software across all hardware systems. We expect, on a portfolio basis, NVIDIA's software business will grow significantly over the next 10 years, and because of the sustainability of software business, NVIDIA's valuation is likely to rise sharply," he said.

If NVIDIA can achieve a considerable recurring revenue scale from its software business layout based on CUDA platform, it will make the revenue scale of this chip giant more predictable and significantly reduce the risk of revenue decline for the company. Analyst Mosesmann emphasized in the research report that NVIDIA's software business, which is based on the CUDA platform, may help push the company's profit scale to $5 per share in 2026 after the split adjustment.

NVIDIA has always relied on the sales of hardware products to drive accelerated revenue growth, and hardware product sales usually have obvious cyclical properties. Non-stable "booms and busts" periods are common for hardware products such as chips, even though NVIDIA's high-performance GPU cannot avoid cyclical properties. Currently, NVIDIA's hardware business is undoubtedly in an unprecedented "boom" period.

Nvidia has always relied on the sales of hardware products to drive accelerated revenue growth, and hardware product sales usually have obvious cyclical properties. The unstable period of "prosperity and depression" is very common for hardware products such as chips, even high-performance GPUs cannot avoid cyclical properties. At present, Nvidia's hardware business is undoubtedly in an unprecedented "prosperity period."

Nvidia has been deeply rooted in the global high-performance computing field for many years, especially its CUDA computing platform, which is recommended by software and hardware for high-performance computing applications such as AI training/inference. The CUDA computing platform is an exclusive parallel computing acceleration platform and programming assistant software developed by Nvidia, which allows software developers and software engineers to use Nvidia GPUs to accelerate parallel general-purpose computing (only supports Nvidia GPUs and cannot be compatible with mainstream GPUs such as AMD and Intel).

CUDA can be said to be the platform on which generation-based AI applications such as ChatGPT depend heavily. Its importance is on the same level as the hardware system and is crucial for the development and deployment of large-scale AI models. With extremely high technical maturity, absolute performance optimization advantages, and extensive ecosystem support, CUDA has become the most commonly used and widely popularized collaborative platform in AI research and commercial deployment.

In addition to the huge GPU hardware revenue brought by CUDA firmly bound to AI GPUs, and the revenue generated by CUDA enterprise-level large-scale applications, the software business derived from CUDA as the core is also the engine for NVIDIA's enormous revenue realization. For example, based on the powerful platform and high penetration rate of CUDA, NVIDIA has continuously increased its layout in the software business field through its powerful AI GPU performance.

NVIDIA's recent layout in the software business field is truly impressive, relying on the incredibly powerful and highly penetrated CUDA platform and powerful AI GPU. For example, based on the powerful platform and high penetration rate of CUDA, NVIDIA has continuously increased its layout in the software business field through its powerful AI GPU performance.

The aforementioned NVIDIA NIM microservice was officially launched during the March GTC. It is a cloud-native microservice focused on optimization, aimed at shortening the time to market for generative AI applications based on large AI models and simplifying the deployment workload for these AI applications on the cloud, data center, and GPU-accelerated workstations. Enterprises can deploy AI applications on NVIDIA AI GPU cloud inference computing power and CUDA platforms to seek to establish an exclusive NVIDIA GPU system AI application software development ecosystem.

NIM is easy to get started with. In the NVIDIA API directory, enterprise developers can access a variety of large AI models that can be used to quickly build and deploy their own company's AI applications on the NIM platform. Therefore, we can simply understand that 'NVIDIA NIM' and Microsoft Azure OpenAI Service provide AI developer service ecosystems with similar functions and application scenarios, which are aimed at simplifying the deployment and inference workload of AI applications based on large AI models.

NIM fully utilizes the accelerated computing capabilities provided by the CUDA platform to ensure optimal performance of AI models when running on NVIDIA GPUs. This integration makes NIM part of NVIDIA's software and hardware ecosystem and promotes the construction of NVIDIA's exclusive GPU-based AI application software development ecosystem.

In 2023, the company's overall sales volume of 18,000 kiloliters, +28.10% year-on-year, significant growth. Product structure, 10-30 billion yuan products operating income of 401/1288/60 million yuan respectively.

From a long-term perspective, the rise of 'the most important stock on earth' may be far from over.

Last month, Beth Kindig, a technology industry analyst from the well-known investment institution I/O Fund, also bullish on Nvidia's software business revenue prospects based on CUDA. "The CUDA software platform is a collaborative platform that AI developers must use. So, the real reason for the iOS ecological barrier is that people are locked into the iPhone because developers are developing applications for the iPhone. The same thing is happening to Nvidia. That is, the CUDA platform is what artificial intelligence engineers learn to program GPU, which helps to lock them in. Coupled with high-performance GPU combinations, now I call it an insurmountable moat." Kindig said in the report.

"CUDA software platform is a collaborative platform that AI developers must use. So, the real reason for the iOS ecological barrier is that people are locked into the iPhone because developers are developing applications for the iPhone. The same thing is happening to Nvidia. That is, the CUDA platform is what artificial intelligence engineers learn to program GPU, which helps to lock them in. Coupled with high-performance GPU combinations, now I call it an insurmountable moat." Kindig said in the report.

It is worth noting that the long-term market outlook given by I/O Fund analyst Kindig for Nvidia is even more aggressive. The analyst released a research report last month, stating that it is expected that by 2030, Nvidia's stock price will soar by more than 200% compared to the current level, and the market value is expected to reach 10 trillion US dollars (currently Nvidia's market value is about 3.34 trillion US dollars). The main logic is the extremely powerful moat brought by Nvidia's CUDA+AI GPU ecosystem, and the next generation of Nvidia AI GPUs based on the Blackwell architecture is expected to bring huge revenue contributions.

Analyst Jin Di predicts that by the end of Nvidia's fiscal year 2026, revenue from the Blackwell architecture AI GPU will significantly exceed that of its predecessor H100 architecture, with Blackwell architecture expected to drive Nvidia's datacenter revenue to as high as $200 billion.

Kindig also predicts in the report that by 2027, the total potential market size of the global AI data center market will reach 400 billion US dollars, and by 2030 it will reach 1 trillion US dollars. It is expected that the data center AI chip market will be mainly occupied by Nvidia, not its largest competitor AMD or Intel. "Nvidia will occupy the largest share of the market," Kindig said. "This is largely due to CUDA ecology and Nvidia AI GPU's powerful performance. "

In the March news release of Nvidia's Blackwell architecture AI GPU, Tesla CEO Musk publicly stated that Nvidia's AI hardware is the best. Musk even compared the AI arms race between technology companies to a high-risk 'poker game', saying that companies need to invest billions of dollars in AI hardware every year to stay competitive.

Editor/tolk