SEAN NEETHLING: Bear in bull’s clothing? Paying the price for AI in US tech

One of the most captivating stories in financial markets today is based on the transformative potential of artificial intelligence (AI) and the companies best positioned to benefit from the technology.

The real challenge for investors is separating fact from fiction in that story and establishing what a fair price is to pay for uncertainty. 

The Magnificent Seven 

US equities have delivered exceptional returns since the start of  2023 — fuelled by the growth prospects of companies focusing on the development and integration of AI technologies. The ramp-up in performance has led to a new bull market, which can loosely be defined as a return of 20% or more from the market lows experienced during a particularly volatile 2022. 

The market has coined the phrase “The Magnificent Seven” to refer to a narrow group of disruptive, high-growth, capital-light companies leading the world towards the fourth industrial revolution.  

Separating fact from fiction is not easy as the incumbent market leaders are established companies with strong competitive advantages, but whose valuations appear to be discounting especially linear growth prospects.

Alphabet (Google), Amazon, Apple, Meta (Facebook), Microsoft, Nvidia and Tesla may all be magnificent companies, but they may not necessarily be magnificent investments if investors are forced to pay too high a price to buy into a story that is likely to have multiple chapters with a few unexpected plot twists.

The “greater fool” theory  

The democratisation of financial markets should theoretically be a good thing in that it allows access to a more diverse pool of potential investors. The caveat, though, is that less experienced investors often succumb to market euphoria and are more likely to continuously bid up prices for companies with especially intriguing stories.  

This is colloquially referred to as the “greater fool” theory. Investment returns are an outcome of less informed (or more perversely incentivised) investors paying continuously inflated prices to participate in market rallies. The effect is that valuations become detached from fundamentals as too much money ends up chasing too few good ideas. It’s the stuff market bubbles and boom-bust cycles are made of. 

Price does not equate to value 

The pre-pandemic stock frenzy fuelled by social media and online forums (such as Twitter and Reddit) contributed to investors suffering permanent capital losses in companies like Gamestop, Blackberry and AMC. The post-pandemic surge in new listings backed by private equity (PE) and venture capital (VC) firms has also yielded especially poor outcomes for investors buying into the hype of high-growth, technology-led disrupting companies with outdated business models.  

The graphs show that returns on PE and VC-backed initial public offerings were deeply negative after deal activity slowed dramatically following the mania that saw sizeable amounts of capital allocated to these companies in 2021. The story framing their growth prospects turned out to have substantially less substance than market participants had anticipated.  

This time is different ... or is it? 

The US tech sector leaders are in a significantly better position than the internet companies that failed after the dot-com bubble burst in early 2000. The current cohort is made up of established companies with durable business models supported by strong network effects and high switching costs.

Their ability to capture users in their ecosystem and integrate technology across different business segments allows them to leverage significant economies of scale and develop sustainable competitive advantages over potential market entrants. 

However, there is no guarantee that established incumbents will emerge as the market leaders in the AI race. The nature of innovation is that it’s not uncommon for the disrupters to be disrupted. 

The business of running these companies is far more complex than the linear assumptions the market is making about their growth prospects. At current valuation levels investors need to price for a wider range of potential outcomes to allow for the uncertainty of developing, integrating and scaling AI technologies. 

Buyer beware

Market structure is also playing an outsize role in driving market performance. Market cap weighted indices tend to overweight stocks performing exceedingly well, which leads to an investment universe that is less representative of the broader market.  

The graph compares the performance of the leading US tech companies using a cap-weighted versus equal-weighted approach. It shows that the return contribution from these companies is substantially amplified by their higher index weights. Investors need to be mindful that any meaningful change in sentiment will also amplify drawdowns.  

Separate fact from fiction

While most of the leading US tech companies may be high-quality businesses, they are trading at expensive valuations and are likely to require significant ongoing investment to develop and integrate AI technologies into their business models.  

While the recent rally in US equities meets the technical definition of a bull market, the market is largely retracting the drawdowns experienced in 2022.  

Embedding the AI story into the investment thesis for US tech does have merit but separating fact from fiction and maintaining a valuation framework that caters for uncertainty is especially important.  

• Neethling is head of investments at Morningstar SA.