The large cap has closed higher for three consecutive days, finally stabilizing at 3300.

Although the trading volume has fallen to 1.6 trillion, with individual stock fluctuations averaging, the market has returned to a state that opens up partially structural opportunities.

As American technology companies gradually disclose their financial reports, AI application company AppLovin has greatly exceeded expectations, with a 46% surge in stock price. The concept of AI applications is highlighted in the A-share market.

Of particular note is Mobvista in the Hong Kong stock market, whose stock price has surged by 277% since November 7th.

AI, back again?

01

AI+ Application Mapping

The market opened lower in the morning and then traded narrowly. By the close, there were no significant fluctuations. In terms of sectors, the internet, precious metals, and power equipment led the gains, while education, telecommunications, and diversified finance sectors experienced declines.

In terms of themes, the controllable nuclear fusion concept led the gains, with Guangdong Dongfang Precision Science & Technology seeing a 6-day consecutive increase. Jusheng Electric, Ningbo Techmation, Suzhou Hailu Heavy Industry, Jiangsu Etern, and Rongfa Nuclear Equipment all hit the daily price limit.

On the news front, the recently developed quasi-symmetric mimic system testing platform made in China passed the experiment. The mimic system is a controlled nuclear fusion device, with nuclear fusion reactions used to obtain continuous energy, which is an essential way to solve the ultimate energy problem for humans and has enormous commercial and strategic value.

This issue is no longer limited to laboratory discussions, with the recent surge in the AI industry, a huge and stable energy infrastructure support is needed behind it. Nuclear power stocks, along with hardware such as chips and optical communication, have entered the scope of AI investment.

Hardware and cloud service companies like Nvidia, Microsoft, are the first ones to benefit from the initial wave of opportunities. Their performance and profit growth started to pick up first. With the continuous penetration of AI applications, companies using AI tools have achieved improvements in quality and efficiency. As a result, companies providing these tools have seen an increase in business volume. An example is the third-quarter report of the top AI advertising company AppLovin in the US stock market.

Q3 revenue of 1.2 billion USD, +39% year-on-year, net profit margin of 36%; among which, software platform revenue including the AI recommendation engine AXON-driven AppDiscovery advertising engine increased to 0.835 billion USD, +66% year-on-year, verifying the commercialization logic of AI advertising, with a stock price increase of up to 716% from the beginning of the year.

The business model of AI applications has been certified, and income covering token costs is the premise that the industry is willing to invest and is also a prerequisite for the prosperity of AI applications. The emergence of applications is expected to bring new demands for hardware, which in turn is expected to significantly reduce energy and reasoning costs.

This virtuous cycle not only stimulates the continuous emergence of new technology stocks in the United States but also reflects in the A-share market.

In the market volatility of the past three days, AI applications have shown a relatively bright structural market. Among them, what directly corresponds to AppLovin is the marketing track in the media sector here, with major advertising platforms like Tencent, ByteDance, and small media service providers such as Beijing Quanshi World Online Network Information (acquired Shanghai Jiatou, known as a small AppLovin), as well as Mobvista (with its Miteraral platform specializing in overseas marketing).

The overall profitability of A-share listed companies in the marketing sector is low, which effectively confirms the performance increment and profit improvement brought by AI marketing. Its adjusted EBITDA profit margin is as high as 60%, far exceeding the industry average.

Expectations are not only fermenting in one application scenario, the logic also applies to other application scenarios. Therefore, the mapping of various branches of AI is on the rise, but some are just speculating related concepts without actual business promotion.

AI Marketing: Beijing Quanshi World Online Network Information, Easy Point World, Bluefocus Intelligent Communications Group, Leo Group Co.,Ltd., Inly Media Co., Ltd., Zhewen Interactive Group, etc.

AI Agent: Kunlun Tech, Wondershare Technology Group, Beijing Kingsoft Office Software, Inc., Shanghai Weaver Network, etc.

AI Search: Kunlun Tech, 360, etc.

AI Audio: Kunlun Tech, COL Group Co.,Ltd., Hubei Century Network Technology Inc., Zhejiang Jinke Tom Culture Industry, etc.

AI Video: Mango Excellent Media, Shanghai Film, Zhejiang Huace Film & TV, Hunan TV & Broadcast Intermediary, etc.

AI E-commerce: Beijing Zhidemai Technology, Fanli Digital Technology, Focus Technology, Foshan Yowant Technology, etc.

AI Education: Dou Shen Education, Astro-Century Education & Technology, iFlytek Co.,Ltd., etc.

AI Games: Ourpalm Co., Ltd., Kingnet Network, Giant Network Group, 37 Interactive Entertainment Network Technology Group, etc.

AI Hardware: Doctorglasses Chain, Guoguang Electric, Edifier Technology, etc.

AI Toys: Alpha Group, Shifeng Cultural Development, Guangbo Group Stock, Beijing Yuanlong Yato Culture Dissemination, Shanghai Yaoji Technology, Zhejiang Jinke Tom Culture Industry, Rastar Group, etc.

Just this week, a major event hit the US stock AI sector. Nvidia's third-quarter financial report yesterday once again exceeded expectations, but revenue growth year-on-year ultimately slowed down. The guidance for the next quarter was also slightly conservative, causing a 5% drop after hours.

Is the adjustment due to overly high expectations, or is the slowdown in revenue causing market concerns?

However, right after that, Open AI is about to launch another major product. Does this mean that the market paradigm around hardware investment will shift towards the continuously emerging application side?

02

AI Investment: Processing power or applications?

Looking at the two major segments of the current AI industry - the underlying infrastructure and the upper application, the truly strong performance still lies in the underlying infrastructure, especially in AI computing power, as can be seen from the strong performance growth of nvidia.

Because nvidia is the only global GPU supplier in an absolute monopoly position, and customers - cloud computing companies, are still rushing to purchase nvidia's blackwell products. Therefore, unless significant bearish news related to demand emerges, such as cloud computing companies drastically reducing capital expenditures in AI computing power, there is no need to worry about nvidia's fundamentals.

However, it is also a fact that nvidia fell after its performance. Looking back, nvidia's stock price has risen for 2 years, with an increase of 10 times. Although some investment banks optimistically predict that the EPS will reach 5-6 dollars by 2025, with a 30 times PE calculation, nvidia's target price for next year can reach 150-180 dollars, but after all, it has risen so much, it should not be blindly bullish like in the past two years, but should be more cautious, especially since it has twice in a row, shown discrepancies in guidance from the buying demand in the next quarter.

This reminds me of Tesla from 3 years ago.

Since the second half of 2019, after Tesla's production bottlenecks were broken, Tesla's shipments soared, exceeding expectations every time, and fortunately experienced global easing due to the outbreak of the pandemic. As a result, Tesla's stock price experienced a super Davis double-click. In just two years, it rose more than 10 times, reaching a peak of 414 dollars.

However, as the high growth in shipments came to an end, coupled with the U.S. high inflation leading to the strong rate hikes by the Federal Reserve, Tesla's stock price fell all the way in 2022, and by early 2023, the stock price had dropped by 76% relative to its historical peak.

Will nvidia follow in Tesla's footsteps?

I cannot be certain, but this does not mean that nvidia is not worth investing in.

In fact, the competitive environment in which Nvidia operates is far better than that of Tesla in the past. Tesla needed to face many besieging competitors, but Nvidia does not need to, even in the foreseeable future, such as 2-3 years. And in terms of the growth and certainty of AI performance, Nvidia is the unrivaled and far ahead.

Therefore, the core issue for Nvidia is valuation.

If the valuation is high, naturally there will be a lack of interest from investors to continue buying, but if the valuation drops significantly, funds will immediately come in to bottom fish. In the next year, a valuation of around 20-30 times, I think it is still reasonable, if it is too high, we need to be cautious.

As for the application layer, it will undoubtedly become the focus of the future. Because the ultimate goal of infrastructure construction is for applications. Although applications are still in the relatively early stages and are often criticized for not having any particularly profitable applications, we are pleased to see the release of performance from some application companies, such as Applovin.

The global technology community unanimously agrees that the AI industry is one of the most important technology industries in the future, and agrees on the development path of building infrastructure first and then applications.

Therefore, for AI investors, a balanced investment portfolio of infrastructure development and application development is relatively reasonable.

03

Conclusion

Returning to the most concerning operational level for everyone, first of all, it needs to be clear that investing in AI funds now is much more rational than last year. Only when specific AI-generated business performance growth is seen, will there be a large-scale long position. It's difficult to easily trigger the capital nerve solely based on promises like last year.

This determines that when investing in AI at present, it's best to pay more attention to the winning rate than simply looking at the odds.

From the perspective of pursuing a high winning rate, for companies like Nvidia, the current hot companies, the more comfortable trading positions need to meet the following two conditions:

Firstly, if there is a collective large-scale retreat in the US stock market, like the one in July-August, where all tech stocks fell, it shows the market is clearing itself, with Nasdaq plummeting by 15% within a month, and Nvidia dropping as much as 34%. A retreat like the one in April, where Nasdaq fell by 8% and Nvidia by 21%, can also be acceptable.

Secondly, there should be no fundamental changes, including the US economic fundamentals and the company's fundamentals. Because economic fundamentals can guarantee the overall rebound of US stocks, while company fundamentals can ensure individual stock rebounds.

This kind of fundamental-independent, short-term, and large-scale sell-offs are clearly opportunities created by the market, making a very high probability of a violent rebound. Companies like Nvidia, with the most active trading, once the market rebounds, often become the target of capital priority purchases.

If we simply apply the above experience, then if Nvidia's stock price could retreat by 20-30% in the short term, for example, within 1-2 months, reaching $100-120, that would be a good buying position.

Don't forget the premise: No change in fundamentals!

As for the A-share computing power concept stocks influenced by Nvidia's mapping, they can also follow the above trading strategy, provided that the impact of geopolitical issues is excluded first.

For application-oriented companies, positioning ahead of time can be done, especially for companies with reasonable valuation and high future performance certainty, whether they are A-shares or U.S. stocks. Although it's difficult to predict when these companies will have explosive performance, and it's possible that the stock price won't rise much for quite a long time after buying, if you are a medium to long-term AI investor, the overall direction is fine, leaving the rest to time is a simple, efficient, and time-saving strategy.

Because in the next 10-20 years, the application of AI will continue to release commercial value and investment returns, creating numerous opportunities.

Buffett once said that investing does not require high intelligence, but it does require a good direction.

Compared to chasing hot topics every day, which may not necessarily be profitable and could be mentally and physically taxing, focusing on the certain broad direction of AI, selecting leading companies, and making more medium to long-term arrangements would be a better approach. (End of Full Text)