More Concentrated Than My Orange Juice

Hey, Alpha fam!

“You come at the king, you best not miss.”

Jensen doesn’t miss.

Much has been said recently about stock market concentration. Microsoft, Nvidia, and Apple (now above $3T in market cap) are worth more than the combined Chinese stock market.

This week, Nvidia briefly surpassed Apple and is quickly closing in on Microsoft for the spot as the top dog on the market leaderboard.

Most analysts will pull up a truncated chart of historic concentration that leads only back to the dotcom bubble and cry, “We are in frothy concentration! This won’t end well!” Michael Mauboussin is not like most analysts. Excellent as always, in his most recent piece, he encourages us to zoom out to look at historic concentration:

He reasons that concentration can be justified if the market capitalizations reflect the companies’ value creation. He concludes that economic profit, which considers return on invested capital (ROIC) minus the weighted average cost of capital (WACC), supports the current concentration level.

Regarding market leaders, the top-weighted industry by market cap in the S&P500 has shifted with market cycles. Energy led from 1990-1996 before hardware’s meteoric rise in the dot-com bubble from 1998-2022. Pharma briefly led between 2002 and 2005 before Energy again claimed the top spot from 2005 to 2014. Software has held the highest weighting in the S&P500 for the last decade. But there’s a new sheriff in town—semiconductors.

This is an excellent chart, and one thing is driving this - artificial intelligence.

When Salesforce posted anemic growth numbers in the most recent quarter, the IGV software index tanked. The IGV is now down 1.3% compared to the SOXX iShares Semiconductor index, up 26%, and the NASDAQ, up 14.5%.

Many are trying to determine if AI will ultimately lead to the demise of the dominance that Software-as-a-Service (SaaS) business models have enjoyed. This is due to several factors:

IT wallet share is shifting from software to AI. Executive teams frequently discussed IT departments delaying major software decisions throughout this earnings quarter before formulating an AI strategy. These incremental dollars are then allocated to AI-first companies instead of traditional software.

Lowering seat count hurts SaaS models. AI is the next revolution in productivity enhancement. By layering AI solutions across nearly every department, it is now possible for 3 people to do the job of 10. AI applications are a substitute for an army of interns at a fraction of the cost. This significantly lowers the TAM for all seat-based SaaS models.

Barriers to entry are now lower. It used to take a team of software engineers to build version one of an application. However, as Jensen Huang, Nvidia CEO, said in a fireside chat, “The new coding language is English.” When low/no-code solutions are prevalent across the space, this greatly reduces the technical frictions around barriers to entry for entrepreneurs who can’t afford to hire software engineers. This effectively reduces the marginal cost of creating code to near zero.

Conversely, semiconductors continue to surge. Much of this is attributable to the meteoric rise in Nvidia:

Recent revenue in AI is being recognized solely by semiconductor companies and cloud providers. Semiconductor revenue is recognized through selling GPUs to cloud providers (AWS, GCP, Azure), who then recognize revenue from renting out those GPUs to AI startups initially training these models and subsequently calling these models (inference).

If you check across every value network node of the semiconductor supply chain, all signs lead to even more growth for this industry. There is a massive demand for computing, driving energy demand, the machines that make the chips, and the most monetizable - the chips themselves.

When you have step-function changes in a new era of prevailing technologies, these cycles typically don’t last only one or two years. They can last a decade.

And we’re just getting started.

Cheers,

The GRIT Alpha Team

The author of this newsletter owns a position in Nvidia (NVDA), Apple (AAPL), and Microsoft (MSFT) in their portfolio or in the funds they manage. There is no guarantee that the author will maintain such a position in the future.

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