What do AI Stocks, The Tech Bubble,
and Taylor Swift Have in Common?

Author:

Jim Monroe, CFA
Product Manager

What are your chances of scoring Taylor Swift tickets? You'll likely find yourself in the pre-sale queue with odds of 1 in 20, or even 1 in 50. For most, this means turning to the secondary resale market. An "affordable" concert experience can range from $50 to over $1,000 per ticket. But why the surge? It's basic economics—limited seats and high demand cause prices to soar.

Think back to 1995, at the dawn of the digital age boom. Your friends, neighbors, coworkers, and even your uncle are all buzzing about the promise of groundbreaking technology—instant communication, online shopping, personal computing, and enterprise software—scalable, far-reaching, and poised to transform every aspect of life and commerce. Just like Taylor Swift concerts, where fans line up at the counter or wait online for their golden ticket, there are only so many tickets available.

Today there’s a new scalable and transformational technology promising to change many aspects of human social and commercial interaction being made more real every day – artificial intelligence or AI. Just like in 1995, we all don’t want to be left behind. However, there is a common problem with these trends: capacity. There were only so many Tech companies in the 90s, there are only so many Swift concert tickets, and only so many AI stocks today. When there is effectively limitless demand, and scarce few assets, prices are driven up.

The key question is: are these AI stock prices now unattractive? Let’s look to history as a guide.

Exhibit 1: The total market cap of companies in the GICS technology sector as a percentage share of the total US equity market cap. 1981 - 2024.
Source: Confluence Style Analytics

During the infamous Tech Bubble, we saw prices of Tech stocks skyrocket, far beyond what earnings would justify, on the premise that those earnings would eventually come (Exhibit 1). At the apex of the Tech Bubble, the Tech sector was worth 30% of the total US equity market, while earnings were half that. The Tech P/E ratio was 60, while the overall market (including Tech!) was 25. Of course, this all came crashing back to earth.

Exhibit 2: Growth of $100 for the market relative performance of the Tech sector 1981-2024.
Source: Confluence Style Analytics

Was everyone invested in Tech wrong? Not necessarily (Exhibit 2). They were just early. It took years to build out the infrastructure, transform culture and integrate Technology into our daily lives. And eventually, Tech as a sector recouped its gains lost during the Tech bubble. The earnings did later materialize. Tech was just 10% of total US Equity corporate earnings in the 2000s, later rising to 15% by the end of the 2010s (Exhibit 3), doubling from the lows of the early 2000s.

Exhibit 3: Total earnings of the GICS Technology sector as a percentage share of total US equity market earnings 2000–2024.
Source: Confluence Style Analytics

As the Tech sector entered its long-term bull market in the mid-2010s, some began to question whether valuations were becoming excessive. While Tech companies crossed the 30% threshold of market capitalization, their share of total U.S. corporate profits was only 16%. This suggests that investors' expectations of rapid growth, far outpacing the broader economy, and high earnings multiples, were fueling Tech's dominance in the stock market.

Exhibit 4: Price to earnings ratio of the Tech sector and the overall US market 2000–2024.
Source: Confluence Style Analytics

We first saw a significant valuation divergence starting with the COVID crash and COVID recovery (Exhibit 4) which remained relatively steady at a P/E premium of roughly 6. We saw a second divergence which coincided with the release of ChatGPT and the onset of the AI boom in late 2022. This has grown into a P/E spread of nearly 17 over market. In short, the spread is highly correlated to the emergence of AI.

The essential question is the same as it was back in the 90s. Will AI transform and revolutionize our society? Likely. But the other important question is how long will that take? For Tech, it took decades.

For instance, Microsoft reached a market cap of 432 billion at the end of 1999. Microsoft didn’t eclipse this higher water mark until the end of 2016, a total of 17 years. The earnings materialized, but investors misjudged how long it would take. Today, Microsoft has become what many predicted: a global technology powerhouse and the second-largest company in the world, with a market cap surpassed only by the GDP of the top six economies

This leads to a key difference with today’s AI-fueled Tech boom: concentration. At least 8 of the largest 10 stocks in the US market have significant exposure to AI. In the 90s, there were seemingly countless Tech companies with billion-dollar valuations that had scarcely any revenue. Today, investors are getting exposure to AI through these mega caps. There simply aren’t many AI companies to publicly invest in that have the capacity to take on massive sums of AI-seeking capital. We examined the top 10 US stocks' historical dominance to contextualize the current market distortion.

Exhibit 5: The top 10 largest US stocks share of total US market cap and share of total earnings respectively 2000–2024.
Source: Confluence Style Analytics

This is by far the highest level of concentration we’ve seen this century, far higher than the nearly 20% at the end of the Tech bubble. The top 10 stocks were only 20% of the US equity market, now they equate to nearly 30% (Exhibit 5). For most of the century, this cohort represented 12 – 17% of US profits, and likewise corresponded to roughly 15% of total US capitalization.

While we’ve seen an uptick coinciding and starting with the Tech boom of the mid-2010s. We have the biggest leg up coinciding with the AI boom. Essentially, investors are betting that the biggest stocks will further dominate at unprecedented levels, with AI as the primary engine of long-term revenue growth. This is further evidenced by the fact that the equal-weighted S&P 500 has risen 8% since the previous high in January 2022, while the standard S&P 500 has increased by 18% over the same period.

Are the top US stocks, the torchbearers for AI in the current market, overvalued? By historical standards, things seem out of whack. The P/E ratio for the top 10 stocks is about 37, while the market average is 23. While this is a significant premium, the top companies are simply much more profitable and have better growth prospects. The return on invested capital for these mega caps is nearly 23% while for the rest of the market the average is just 15%. If we adjust P/E ratios by forecasted growth rates, the P/E ratio per unit of growth (PEG) is 1.4 for mega caps and 2.5 for the market. This means that investors must pay 80% more for the same growth on average for the rest of the market.

There are fundamentals backing up what appears to be distortions in the market but long term the mega caps can’t justify these valuations without AI. If we take Nvidia, for example, they’ve seen massive revenue growth, nearly 200% YoY (July 31, 2024). But this revenue is fueled by selling to other businesses. These other businesses include other mega caps like Microsoft, Meta, and Amazon, who are spending billions on Nvidia’s technology to build AI solutions. While there are commercial applications, the big money is being bet on consumers adopting AI, and then ultimately paying. We’re simply not there yet. The business models are unclear and the path to monetizing AI-driven consumer products is uncertain. It will likely happen, but that may take significant time. Paying a monthly subscription to a chatbot alone won’t get the market to the required billions in AI related revenue to justify these valuations in the next few years.

Let’s conclude with what AI has to say. Here is a response from ChatGPT:

In the long run, I believe the AI revolution will justify higher valuations, especially for companies with dominant positions in the space. However, I think the current P/E ratios are somewhat inflated due to overly optimistic timelines and expectations for how quickly AI will impact revenues and profitability. If you're a long-term investor, the AI trend seems like a solid bet, but short-term corrections or volatility are likely if the market resets its expectations. Therefore, while these stocks may still be worth owning, investors should approach with a degree of caution and not expect uninterrupted upward momentum.

In essence, the AI boom may justify some of the premium, but the market might be pricing in a perfect scenario that is unlikely to unfold without setbacks.

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