Telemus Weekly Market Review February 19th, 2024 - February 23rd, 2024
The dominant story driving the stock market this week was Wednesday evening’s earnings report from semiconductor company, NVIDIA. Heading into Wednesday, shares of the stock were up nearly 40% thus far in 2024. The company’s results were not only better than had been expected, but the company’s financial guidance for the coming quarter supported a further rally in the stock. This led to shares rising another 16% in Thursday’s trading session.
Adding more color to the NVIDIA’s story, it isn’t just the strength of the past quarter that captivated investors, it was NVIDIA’s CEO Jensen Huang’s comment that AI demand is now at a tipping point. Moreover, Nvidia noted that demand is expected to outpace supply throughout 2024. This provided comfort to investors that the insatiable demand for NVIDIA’s Graphics Processing Units (GPUs) is likely to remain throughout 2024 and added optimism that the growth trajectory can continue into 2025.
Going into Wednesday’s earnings, the debate was whether one should follow the old trading adage of ‘buy the rumor, sell the news’, or whether results would be strong enough to fuel further advancement in the share price. Thursday’s strong rally answered that question. Behind the scenes there were some additional influences helping to support the strength in the share price. An elevated number of call options had been purchased on the stock going into the earnings release. As NVIDIA’s share price went higher on Thursday, it required the counterparties (traders) on the other side of the call option to buy shares of NVIDIA to hedge their risk. This created a feedback loop where indiscriminate buyers were purchasing shares to hedge risk, with their added demand only sending the share price even higher.
It is becoming increasingly clear that artificial intelligence is a major technological trend that will influence economic growth and productivity over time. Historically, major technological breakthroughs begin with a wave of elevated investment where capital is deployed to build out the infrastructure to support technological adoption. This is exactly what’s occurring today as capital is being deployed into computing infrastructure (hardware) to support AI adoption. A key source of the funding today comes from cloud service providers such as Amazon, Microsoft and Google.
As the infrastructure is scaled, we’d expect software applications that embed AI capabilities or support the training of generative artificial intelligence models to begin to experience increased demand. The cadence of adoption is always hard to predict, and past episodes of technological innovation have come with episodes of digestion as use cases for the technology evolve.
In a recent conversation we had with a data center developer, they indicated that many of the data centers under construction today are being developed to focus explicitly on artificial intelligence applications. Therefore, the insatiable demand for GPUs is stemming from new data center capacity that has yet to be utilized. This leads to a key debate surrounding AI infrastructure spending and whether the current level of demand is persistent or whether the industry is experiencing a more traditional semiconductor cycle where once capacity is reached, we could see a slowdown in demand.
This ultimate cadence and path of spending on infrastructure is just one of many areas of ambiguity and uncertainty that persists around the artificial intelligence trend. As it stands today, NVIDIA clearly has the early mover advantage and dominant position in the chipsets required to train generative artificial intelligence models. Others such as Advanced Micro Devices are trying to catch up. Moreover, cloud service providers such as Microsoft, Amazon and Google are thought to be exploring the development of their own semiconductors.
While the big picture around AI is becoming a bit clearer, and capital is quickly being deployed to build out the infrastructure, there remains a great deal of uncertainty on how this technological breakthrough will play out. The early beneficiaries, such as NVIDIA, have become clearer. The next leg of beneficiaries could extend to cloud service providers, software applications, or users that disproportionately benefit from the productivity enhancements that AI can provide. In this exciting time of technological innovation, we are not only focused on the current stage of growth but who may benefit in future phases.
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