The S&P 500 (^GSPC -0.30%) is on its way to its second straight year of outsized returns. After generating a total return of 26.3% last year, including dividends, it’s up about 29% this year, as of this writing.
That has led some some pundits to question whether the market is becoming too frothy. Meanwhile, famed investor Warren Buffett has clearly taken notice of some elevated valuations, selling some of his top holdings and stockpiling cash.
Let’s look at two of the main issues that likely will help determine whether the stock market could crash next year.
1. Valuation
By a number of measures, the S&P 500 is clearly trading at historically high valuations. Last month, Fool.com writer Sean Williams wrote a great article looking at how the index was trading at a level it has seen only three times since 1871, and each time, this was followed by a bear market.
The metric Sean looked at was the Shiller price-to-earnings (P/E) ratio, which is also sometimes called the cyclically adjusted P/E ratio, or CAPE ratio. Popularized by Yale economics professor Robert Shiller, hence the name, this metric calculates earnings based on a 10-year average adjusted for inflation. The purpose of doing this is to smooth out any economic cyclicality and earnings volatility.
The S&P’s Shiller P/E ratio has only hit 38 times in two other periods: during the dot-com bubble, and early in 2022, before the market pulled back. The ratio was sitting at 38.8 times at the start of December.
Now, while the Shiller P/E ratio has predicted two past bear markets, it is worth pointing out that this is a very small sample size. It also is a backward-looking metric, while the market tends to be forward-looking.
The S&P 500 is also currently very top-heavy, with Apple, Nvidia, and Microsoft representing about 20% of the index. Nvidia at about 6.8% of the index is particularly noteworthy, as its earnings per share even two years ago were very different from its earnings in 2024.
Meanwhile, many of the largest companies in the S&P are currently enjoying substantial earnings growth, which is bringing down their future price-to-earnings ratios. For example, Nvidia’s trailing-12-month P/E is 56, but its forward P/E based on next year’s analyst estimates is only 32.
NVDA PE Ratio (Forward 1y) data by YCharts
The Shiller P/E ratio doesn’t account for this explosive growth and assumes it will be cyclical. This leads to the next big factor in determining whether the market may crash next year.
2. Artificial intelligence
Artificial intelligence (AI) will perhaps be the biggest determining factor whether the market continues its strong run or whether it crashes next year. While the S&P’s Shiller P/E ratio may have helped “predict” the dot-com market crash, it was a sudden and unexpected collapse in internet infrastructure spending and the creation of a lot of unviable internet-based businesses (anyone remember Pets.com?) that was ultimately one of the big reasons the market crashed. The Federal Reserve had also started raising interest rates to cool things off, while currently it’s begun cutting interest rates.
About a third of the S&P 500 is very concentrated among eight companies that are very tied to AI right now. And while the Internet boom was being led by a bunch of upstart companies in many cases, the AI boom of today is being led by extremely large, highly profitable companies that in most cases have diversified businesses.
That said, growth from these companies is being spurred by AI, and thus AI is going to be the biggest driver of the S&P in the years ahead. It starts with AI infrastructure spending. If this suddenly collapses, like what happened to Cisco during the Internet boom, then the market likely will crash.
However, this spending is currently being driven by very large, profitable tech companies that are competing to develop the best AI models they can. As long as this competition continues, it should be good for Nvidia, and by extension, the S&P. To advance AI models, companies need exponentially more and more computing power, and thus greater AI infrastructure spending.
That said, this AI spending needs to translate into growth for the big tech companies spending this money. Thus far, the companies with big cloud computing units — Amazon, Microsoft, and Alphabet — have seen strong revenue and operating income growth from their cloud computing segments. Now their customers also need to see strong growth from AI as well, and you are just starting to see AI-related growth ramp up in the software industry. And the software companies, in turn, need their AI solutions to save on costs and create efficiencies for their customers, including those outside the tech industry.
Right now, this still feels like things are still in the early AI innings, which is why I think the market can continue its strong run and won’t crash net year. Bull markets, on average, tend to last about 5 1/2 years, and we are only just a little more than two years into the current one.
At the end of the day, though, I think the performance of the S&P 500 is largely going to come down to how much companies are benefiting from AI and how much they are willing to spend on improving AI. Eventually the law of diminishing returns will catch up with AI and AI spending, but right now, that looks far off.
