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%.

Global large ai datacenter ethernet switch chip, as well as the core supply force in the ai hardware sector custom ai chip - $Broadcom (AVGO.US)$ has become the core market focus of the ai investment wave since 2023, with investment enthusiasm only second to the ai chip leader $NVIDIA (NVDA.US)$ However, in recent times, stock prices have underperformed against XLK and$PHLX Semiconductor Index (.SOX.US)$, Broadcom's stock price has fallen over 15% from its historic peak on October 9. Could there be a trap in this?

Since October 2024, one of the biggest winners in the global AI boom, Broadcom, has recently underperformed compared to ETFs tracking popular tech stocks in the US market— $The Technology Select Sector SPDR® Fund (XLK.US)$ and the benchmark for US chip stocks— $PHLX Semiconductor Index (.SOX.US)$ 。

Wall Street analysts have concluded that the logic behind this is mainly due to investors reallocating funds from popular semiconductor stocks focused on AI hardware infrastructure to relatively undervalued semiconductor stocks that have not been excessively hyped by the market, and also benefiting from the unprecedented AI frenzy in SaaS software stocks, especially those software stocks that have already achieved actual profits, such as$Applovin (APP.US)$and$Snowflake (SNOW.US)$、$ServiceNow (NOW.US)$and many more.

In terms of PEG valuation, Broadcom's forward adjusted PEG ratio of 1.69 appears relatively attractive compared to the median of 1.89 for the entire U.S. technology sector. Additionally, although the hyperscale datacenters are expected to incur massive capital expenditures on AI hardware, including AI GPUs and customized AI chips, the market still seems to be pricing in NVIDIA's dominance of over 90%, without fully accounting for Broadcom as a leader in customized AI chips that could challenge NVIDIA's supremacy, and which may expand its AI chip market share at a growth rate of up to 50% in the future.

Broadcom - The strongest player in the customized AI chip field, strongly bullish on Wall Street to $200.

After Broadcom released its earnings report in September, some Wall Street investment institutions urged investors not to heed the market's concerns about its forward guidance, as Broadcom is not like NVIDIA and other companies.$Taiwan Semiconductor (TSM.US)$In this way, most business exposures are closely related to ai. Broadcom's third quarter results, announced in early September for the period ending August 4, showed that demand for ai-related chips is booming, while non-ai areas such as analog chips and industrial sectors are still in their "darkest moment." Without the contribution of ai, the company's performance would be quite bleak.

Despite this, Broadcom's performance slightly keeps pace with$S&P 500 Index (.SPX.US)$(SPX)(SPY) and Wall Street's average target price for Broadcom is as high as $200, indicating a potential upside of up to 23% over the next 12 months. With strong demand from major global datacenters for Broadcom's Ethernet switch chip, and due to its absolute technological leadership in inter-chip communication and high-speed data transfer between chips, Broadcom has become the most important player in the customized ai chip field in recent years. For instance, the AI acceleration chip TPU developed by Google for its own servers, Broadcom is a core participant, collaborating with the Google team in the research and development of the TPU AI acceleration chip and the ai training/inference acceleration library.

Broadcom's Ethernet switch chips are mainly used in datacenter and server cluster equipment, responsible for efficiently and quickly processing and transmitting data streams. Broadcom chips are essential for building ai hardware infrastructure, as they ensure the high-speed transmission of data between GPU processors, storage systems, and networks, which is extremely important for generative ai like ChatGPT, especially for applications that require handling large amounts of data input and real-time processing capabilities, such as Dall-E text-to-image generation and Sora text-to-video large models. More importantly, Broadcom has now become the most important player in the ASIC customization chip field in the ai sector, as not only has Google chosen to collaborate with Broadcom on the design and development of customized ai chips,$Microsoft (MSFT.US)$but it is expected that giants like Meta and more datacenter service operators will collaborate with Broadcom in the long term to create high-performance ASICs.

In addition to chip design, broadcom also provides critical inter-chip communication intellectual property for google, and is responsible for manufacturing, testing, and packaging new chips, thereby safeguarding google's expansion into new ai datacenters.

The strong demand for ethernet switch chips, as well as the ASIC customized ai chips closely related to ai, is clearly reflected in broadcom's strong revenue data for fiscal year 2023 and so far in fiscal year 2024, which has consistently exceeded expectations. In particular, customized ai chips have become an increasingly important source of revenue for broadcom. Market news indicates that tech giants microsoft and facebook's parent company meta will choose broadcom as a core partner for their self-developed ai chip technologies, as meta previously collaborated with broadcom to design its first and second generation ai training acceleration processors. It is expected that broadcom will accelerate the research and development of meta's next-generation ai chip MTIA 3 in the second half of 2024 and into 2025.

Therefore, although the stock price performance has been relatively weak recently, most analysts believe that investors do not need to hold a pessimistic view on broadcom's stock price and performance outlook. TIPRANKS compiled analyst ratings and target prices from wall street indicate that broadcom's average target price for the next 12 months could reach as high as $200, with a consensus rating of 'buy' and no 'sell' ratings. Among them, Cantor Fitzgerald recently raised broadcom's target price from $200 to $225, while mizuho significantly increased broadcom's target price from $190 to $220. In contrast, broadcom's stock price closed at $162.08 last Friday.

Customized ai chips — the strongest competitor to nvidia's ai gpu! The market expects stronger ai performance guidance.

Broadcom will announce its fourth quarter earnings on December 12th, eastern time. Given that the previous quarter's performance guidance was significantly disappointing, investors are expected to closely scrutinize the ai-related revenue outlook for this semiconductor leader. Broadcom's CEO Hock Tan expressed his optimism during the last conference call in September 2024, emphasizing the surge in demand for customized ai chips from leading hyperscale cloud computing companies (such as microsoft, $Amazon (AMZN.US)$AWS, and google) regarding capital expenditures for ai infrastructure.

The so-called datacenter ai gpus sold by nvidia are the core infrastructure hardware driving popular generative ai tools like ChatGPT, but broadcom also benefits comprehensively from the ai boom by providing related ai hardware components and associated software. The ethernet switch chips provided by broadcom and the ASIC customized chips developed in collaboration with chip giants like google are crucial for companies seeking to create generative ai applications similar to ChatGPT, as well as those pursuing cost efficiency and urgently needing to expand ai computing resources, particularly for tech giants like google and microsoft in building their ai datacenter computing power.

As observed during broadcom's recent third quarter earnings season, this momentum continues. Therefore, massive cloud computing giants are increasing their investment in ai chips to maintain a competitive advantage in the rapidly evolving ai race. Wall Street giant morgan stanley believes that capital expenditures on ai by these massive cloud computing companies could soar to 300 billion dollars by 2025. nvidia's recent earnings conference also highlighted the "crazy" demand fromlarge datacenter operators as they transition from the Hopper architecture to Blackwell architecture ai GPUs.

Therefore, can broadcom's latest guidance outperform the 12 billion dollars ai revenue expectation for the 2024 fiscal year given in September? Wall Street analysts believe there is ample reason to have confidence in broadcom's CEO Tan and his team. With large-scale ai clusters (>0.1 million ai GPUs) becoming the focus, ai hardware infrastructure such as ai GPUs and customized ai ASIC chips is increasingly becoming the "bet" in the ai supremacy race. Thus, we can see the hundreds of thousands of ai GPUs being constructed, and such an assessment is not misleading. However, leaders in the ai field and massive cloud computing giants are facing growing pressure to address challenges of ai computing power resources and expansion costs.

Recent reports from multiple media sources indicate that although technology companies focused on large language models are eager to improve their cutting-edge models, the scaling of ai performance is slowing down, causing companies to pay more attention to ai inference and cost effects. Customized ai chips that excel at data-intensive matrix computations and extensive high-load inference tasks, which are more aligned with large models and cloud computing architectures, have cost and high energy efficiency computing power advantages on one hand, and on the other hand, ease the severe shortage of ai computing resources brought about by nvidia's Blackwell and Hopper architecture ai GPUs (GB200/B200/H100/H200).

As ai companies and massive cloud computing giants reassess their financial capacities to invest in emerging ai clusters, broadcom's expertise in customized ai chips is expected to lead the next phase of explosive growth. Given that the design and production of customized ai chips require achieving a certain scale to realize cost-effectiveness, broadcom's expertise in inter-chip connectivity and long-term focus on customized chip design are expected to be key advantages, as demand for customized ai chips is expected to increase significantly.

Broadcom is also partnering with companies like google to break the absolute monopoly of nvidia's CUDA ecosystem on ai training/inference programming acceleration libraries. Broadcom usually collaborates with partners to build specialized software development kits (SDKs) and hardware-software collaborative acceleration libraries specifically for its ai chips. These SDKs and acceleration libraries are typically designed to optimize the performance of broadcom's self-developed ai hardware, similar to the libraries offered by nvidia based on the CUDA platform, such as cuDNN and TensorRT, used for ai training and inference acceleration.

Broadcom CEO Hock Tan shared in September that customized ai chips accounted for two-thirds of its ai revenue. Additionally, broadcom has established solid partnerships for customized ai chips and ethernet switch chips with three massive datacenter operators. The geopolitical headwinds faced by technology giants from china are expected to drive some of the most valuable tech companies in the country to turn to collaboration with broadcom to develop customized ai chips, as it becomes increasingly challenging and complex to obtain nvidia's ai chips.

The scale expansion of OpenAI has made collaboration with broadcom to develop customized ai chips a viable business proposition, potentially improving operational efficiency and reducing costs. Therefore, some analysts suggest that broadcom's assessment that customized ai chips could play a more prominent role in massive datacenter ai workloads within the next five years is not unreasonable; while nvidia is still expected to hold over a 60% share, the market size for broadcom's customized ai chips is likely to exhibit a compound annual growth rate of up to 50%. amazon AWS's experience in collaborating with cloud computing clients using customized ai chips indicates that as massive datacenter operators compete to enhance cost competitiveness and significantly expand computing resources, the customized ai chip business has high growth feasibility and long-term sustainability.

Although broadcom is the market leader in the ethernet chip field, as nvidia seeks to develop more cost-effective "ai hardware system bundles" to support the adoption of its ethernet and InfiniBand network products, broadcom may face more intense challenges. Nevertheless, broadcom's executives still believe that the semiconductor giant can maintain the "industry standard" due to its extremely high market share in ethernet products, demonstrating scalability and energy efficiency. Therefore, it can be anticipated that the competition between nvidia and broadcom will become increasingly fierce, but broadcom's advantage lies in its diversified business sectors focused on different endpoints, which can mitigate unexpected weaknesses in a single business.

Editor / jayden