To The Moon

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It's almost like a race to the finish line as $NVIDIA Corp(NVDA)$ 's stock price continues to climb, effortlessly breaking through the $700 mark with barely any significant adjustments.

The big banks like $Goldman Sachs(GS)$ $Bank of America(BAC)$ $Morgan Stanley(MS)$ are all jumping on the bandwagon, raising their target prices for Nvidia. Goldman analysts even bumped up their 12-month target price to $800 and reiterated their buy rating.

Nvidia's market cap is now neck and neck with $Amazon.com(AMZN)$ $Alphabet(GOOG)$ $Alphabet(GOOGL)$, poised to become the third most valuable company after $Apple(AAPL)$ $Microsoft(MSFT)$.

At this price point, investors are bound to ask: Is this a bubble or real growth? After all, the stock has surged 45% in just over a month in 2024 and 200% in the past year. That's quite a ride!

Depend on performance!

When it comes to these big tech stocks in the US, the bottom line is the earnings report. Even the Fed's monetary policy can't stop their momentum. It only indirectly affects stock prices by influencing the macroeconomy and, subsequently, the earnings of these tech giants.

So, is Nvidia's stock price expensive or cheap? That depends on its growth potential. Recent slowdowns in earnings growth for companies like Apple and Tesla have clearly reflected in their stock prices, even prompting some media outlets to exclude them from their "Magnificent Seven" lists.

But Nvidia seems to have a solid footing right now. Its smart chip products are in high demand and haven't been affected by concerns about key customer order reductions.

Despite its rapid stock price increase, Nvidia's dynamic P/E ratio, based on earnings expectations for the next 12 months, is relatively low at 25 times. Among growth stocks, it's almost considered "undervalued".

Morgan Stanley has given Nvidia an "overweight" rating, and analyst Joseph Moore cites the strong demand as his reason for the investment recommendation. "GPUs are still in high demand, and developers tell us that the backlog of orders is still long. These customers have to wait months for training," he explains.

As for the delivery delays, Moore attributes them more to infrastructure bottlenecks than a decline in market demand. "Although the wait time is shortening, it's still quite long, which suggests that there's high profitability in configuring GPUs for cloud centers," he adds.

So, when will Nvidia's stock price hit a wall? Maybe we can learn some lessons from Tesla's historical trends.

The biggest fear: issues on the Sales side

In fact, the current US stock market isn't exactly on a roll. Interest rates are still high by historical standards, and only a few big companies can manage to see their stock prices soar thanks to growing earnings. And because there are so few of these winners, there's a bit of a certain capital group effect, resulting in higher valuations for these select few. But the overall market isn't exactly in a frenzy.

In other words, with capital costs this high, the market isn't going to fall for just any concept. It wants to see real results, and for Nvidia, with all this hype surrounding it, any hint of "earnings missing expectations" could be devastating.

Moreover, Nvidia's customers are themselves major tech companies that expect immediate returns on their investments in Nvidia's GPUs.

"Half of the strong demand for Nvidia's GPUs comes from cloud providers, and as long as they can see immediate returns after deploying these GPUs, the demand will likely remain robust," said analyst Joseph Moore.

There are two main scenarios where Nvidia's performance could take a hit:

One is if the industry demand slows down, and the overall AI industry doesn't grow as fast as expected.

To assess this, we'll have to see if the increasingly large-scale training efforts lead to substantial improvements in model capabilities. That'll determine whether cloud computing companies are willing to further increase their capital expenditures.

Feedback from OpenAI suggests that the scarcity of large AI chips is already a major constraint on their growth. Sam Altman has even gone on record complaining about the lack of GPU chips needed to pursue general AI.

The latest news is that Altman, CEO of OpenAI, is reportedly in talks with investors, including those from the UAE, to raise anywhere from $5 to $7 trillion to boost global chip manufacturing capabilities and further their AI efforts.

Just to put that figure into perspective, consider that global chip sales in 2023 were worth $527 billion, and they're expected to reach $1 trillion by 2030. This proposed investment is even bigger than the national debt of some major economies and larger than the total corporate debt issued in the US in 2023, which was around $1.44 trillion.

Altman is reportedly suggesting a collaboration between OpenAI, various investors, chip manufacturers, and power suppliers to jointly fund and build chip manufacturing facilities. These facilities would then be operated by existing chip manufacturers, with OpenAI being a key customer.

While this rumor hasn't been confirmed, it does suggest that industry demand isn't the only issue Nvidia faces. The company could also lose market share to intense competition, resulting in slower growth.

Currently, Nvidia enjoys a dominant position in the global AI chip market, with some estimates putting its market share at a staggering 90%. However, competitors like $Intel(INTC)$ $Advanced Micro Devices(AMD)$ are gearing up to launch competitive AI chips, aiming to challenge Nvidia's dominance.

At the same time, Nvidia's big customers, such as Microsoft and other large companies have begun to independently develop chips, coupled with the current rumors of large funds in the OpenAI group, are trying to enter the market, which may have some impact on Nvidia's growth.

For now, though, these threats don't seem to be causing too much concern. The market might see some fluctuations as investors cash out their profits, but Nvidia's industry advantages are still intact.