How BAD Are Stock Valuations Really?

The number one question in stock investing right now. Is AI going to kill us? Followed closely thereafter by is AI in a bubble? The AI bubble is bursting. South Korea's AI bubble just popped. The AI bubble just burst. The AI bubble video bubble is about to pop. Wait a minute, that's me. Regardless, to get my point, many people are worried that the stock market, specifically in the United States, is in a bubble. Tech companies have come to dominate major indices while spending hundreds of billions of dollars on infrastructure for AI companies that are ultimately unprofitable, all while facing headwinds from rising oil prices, treasury yields, and heightened inflation. Meanwhile, the stock market has continued to reach new all-time highs, which is why many people have come to the conclusion that the market surely is in a bubble. Surely, valuations are stretched. But are they really? Don't get me wrong, there are a lot of individual AI companies walking around with pretty questionable valuations. SpaceX is a prime example, having set records with its recent IPO and instantly breaking into the top 10 list of largest market caps in the US, despite its revenues not even cracking the top 200 list. And there are plenty of red flags, plenty of reasons why the current stock market run up is not sustainable. But whether the market as a whole is in a bubble or not is actually quite difficult to determine because it depends on what you look at. And some people will argue, hey, listen, yes, AI stocks are expensive, but consider the massive potential they face. The businesses that are in the space with high valuations now might be set to reap the biggest reward from the changes to come. Now, no one knows what the future holds. We're going to end up somewhere between the two extremes of the utopia where everyone retires rich with an Optimus robot folding their laundry, and Armageddon, where AI takes over, and there's not even an economy left because tech bros flew too close to the sun. But truly, there are just too many variables to accurately predict what happens from here. So I thought instead, let's narrow our scope, focus on one aspect here. Is the market, namely the S&P 500, expensive based on historical standards? And well, even here, that question proves more difficult to answer than you might expect, given again, it depends on where you look. Charts like this one definitely suggest that things are overpriced. It could convince most people that we are in a bubble, whereas this one would suggest that things are actually pretty attractive. And regardless of your view, it's important to try and understand why people are on the other side. For example, still buying when so many people think we are in a bubble. So today, let's go through the exercise of trying to answer this question of comparing all these different metrics to better understand why the market looks the way it does. And while it might not give us an explicit yes or no answer, it will give us a more nuanced understanding of the market and why these metrics vary so meaningfully. Now, the S&P 500, the index we'll be using today is naturally 500 of the largest US stocks by market capitalization, but not necessarily the 500 largest US companies, given that there's other inclusion criteria, including time and earnings requirements, which is why companies like SpaceX are currently not in the index. But it's become a proxy for the stock market, covering about 83% of the market's entire market capitalization. And it's become one of the most popular investment vehicles for DIY investors. So I think it's a good representation for today's exercise. But how exactly do we value an index? Because the level alone doesn't tell us a whole bunch. Yes, the S&P 500 has doubled over the past four years, but to put that into perspective, we have to compare it to some fundamental metric of how the underlying companies are performing or how they're expected to perform in the future. Now, normally with an individual company, you could do something like a discounted cash flow, where you estimate all future cash flows a company is going to create, you discount them based on the timing, and then you add that all together and make a few adjustments to come to some estimated value for that stock. With an index, that's not really feasible. Not only do we have 500 companies to do that for, but the amount of estimates we'd be throwing in here would make such a large margin of error that ultimately it would render any value we come to pretty useless. So instead we can do a relative valuation where we compare the index level to, again, some singular market cap weighted average of some fundamental metric across all 500 companies. Today we're going to use the most common one, earnings. which is used commonly for the price-to-earnings or PE ratio of individual stocks, where you take the price of a company's stock and divide it by the earnings per share, the profit they have after accounting for all of their expenses. And if you take this metric for each of the 500 different companies and you calculate a market cap weighted average of the bunch, then you'll come to a PE for the S&P 500. So how does that look? Well, again, it depends on what you're talking about. If you look at this PE, for example, the Shiller's PE or cyclically adjusted price to earnings ratio, CAPE for short, you'd probably convince most people that we're in for the dot-com crash 2.0. We are currently above 40 times a level not seen since the dot-com bubble, and the metric is fast approaching a new all-time high, which yeah, is pretty alarming. But one important point is that the CAPE ratio, as the name suggests, is cyclically adjusted. There's actually an earning smoothing factor that reduces the year-over-year volatility. What that means is that to calculate the CAPE ratio, we actually take the price and divide it by the average inflation-adjusted earnings over the past 10 years, with the idea being that this will help to ensure that short-term factors like where we are in the business cycle don't unnecessarily skew our reading of a company's valuation. It gives us a more long-term view of the stock's value. However, that also means that we're putting less weight on more recent earnings, which matters if we encounter a period of rapid earnings growth, because it will understate the impact of that earnings growth and might overstate the valuation of these stocks, something that we are currently experiencing. In Q3 of this year, for example, the S&P 500 saw its earnings grow by nearly 30%, the third consecutive quarter of growth above 25% year over year. For reference, the 25-year average earnings growth for the S&P 500 has been 6.4%. Now, that's not to argue that this is sustainable. Certainly, that figure will come down at some point. A lot of the short-term growth is related to the AI build-out. And at some point, as with the internet build-out, we're not going to have three to four data centers popping up a week in the US. But if you subscribe to this idea that AI is this revolutionary technology that will unlock a company's ability to grow more rapidly into the future, then the CAPE ratio might again overstate a company's valuation, and you might want to consider something like a more simplified trailing PE, which only takes earnings from the past 12 months. Naturally, you'll see the figure is much more volatile since we aren't smoothing things, which is why it skyrocketed here in 2008. But today, the measure, while certainly more elevated, is well below what we saw during the peak of the dot-com bubble so already we're starting to see a bit of a different picture yes things do seem expensive but not as far stretched as they were during the dot-com bubble they at least have earnings behind these companies to justify some of this performance we've seen but so far we've only looked at trailing valuations pricing a company based on what it's done in the past in truth most investors invest in stocks based on what they expected to do in the future So we should also consider forward-looking PE ratios, which take the price of a stock and divide it by the next 12 months of earnings. Now here we run into a similar problem as with the discounted cash flow model, which is that we're talking about the future. And no one knows what the future holds for many of these companies. Nonetheless, people do try to estimate the earnings a company will see over the next several years. and we can take what's called the consensus estimates for all of these companies. Consensus just meaning the average of all the analyst forecasts for these earnings. Now there's no one single source for consensus estimates so depending on where you pull it you might get a slightly different figure but I'm going to be using the numbers from Yardeni Research which is a platform run by the famous economist Ed Yardeni who actually has a financial model named after him. This is not a paid promotion but Yardeni Research excellent free resource with a lot of charts published daily about the stock market. And you can see here that they have the forward PE for the S&P 500 based on consensus estimates. And if you take a look, you'll see that the metric is indeed heightened at around 19 times above the long-term average of 16 times. However, it is again below the dot-com peak of 25 times, and it's actually been on the decline over the past year. Finally, since I know you guys are having a blast here, we're going to look at one more forward metric, which is the forward PEG ratio, the forward PE for these companies divided by their five-year estimated earnings growth rate. With this ratio giving us an idea of whether a company's valuation is justified. Any ratio above one is generally considered on the more expensive side, whereas ratios below one are generally considered cheaper. You're growing faster than the valuation might otherwise suggest. And this is going to be the most controversial metric here because it actually suggests that the S&P 500 is cheap. And not just cheap, but the cheapest it's been in decades. So trailing valuations certainly are elevated, but this suggests that analysts are expecting the growth of earnings for these companies to actually outpace these higher valuations. And sure enough, if you look at the consensus five-year earnings growth estimate, it has surged over the past two years and currently sits at 27.3%. So the S&P 500 is actually cheap. End of story, right? Wrong. We're not done beating this dead horse till I say so. So far, we've only categorized things as expensive or cheap based on their historical performance. We can also compare the index's valuation levels to other indices to get an idea of how they stand in the group. For example, we can look at the S&P 600 and the S&P 400, which are the S&P indices of US stocks in the small cap and the mid cap range respectively. So small and medium sized companies. And you can see here that looking at the four PE ratios, these indices are cheaper with valuations of around 14 and 15 times versus the S&P at nearly 20 times. But again, if we look at the peg ratio, the S&P 500 is actually on the low end. This chart is a little crowded, but you can see the S&P 400 has a peg of 0.8, the 600 is at 0.96, and the 500 is the lowest at 0.69. Finally, of course, we can compare the S&P 500 to other international markets to see how the U.S. stands against other countries. Here we'll use the MSCI All Country World Index ex the United States, which as the name implies, is an international index with 22 developed and 24 emerging countries capturing 85% of global equities outside the US. Now, while the US market has gotten a lot of attention over the past several years, this index has actually itself done quite well over 2025 and this year to date. But how does its valuation look? Well, with the forward PE, you can see that the index is actually fairly cheap by historical standards at 12.5 times with a big part of this being that earnings estimates for this index are themselves surging suggesting meaningful earnings growth over the next few years and now we don't have the same five-year earnings average growth rate that we do with the U.S. to compare peg ratios but you can see that international markets are actually expected to grow earnings at a similar pace to the S&P 500 despite trading at a pretty meaningful discount now I know what you're thinking by god Richard, we've been all over the place now. Just give it to me straight. Is the S&P 500 expensive or not? Correct. But to further our understanding of the valuations here, we need to finish things off with a few important caveats, constraints, and considerations. The first biggest one, again, being that when we're talking about forward valuations, we're relying on forecasts, which we all know how great people are at those. In fact, Yardeni Research has a graph that illustrates this perfectly called squiggles. This might be a bit confusing at first, but this line here is actual operating earnings per share for S&P 500 companies. And each squiggle represents estimates for one data point over a 25 month period leading up to the release of that data point. It extends a bit beyond the actual date because there's a delay between when a quarter finishes and when the results are announced. But you get the point. Each of these lines is for one data point being estimated over time. And one thing you'll notice beyond the fact that the estimates move quite a bit is that analysts are often too optimistic when things are going well. Most of these squiggles during the upward slope in the purple line themselves have downward slopes. So forecasts can only get us so far. The second thing of course to mention is S&P 500 concentration. Despite covering 500 different companies, the index's performance is largely determined by just a handful of companies. For example, you might have heard of the Magnificent Seven, which includes Google, Amazon, Apple, Meta, Microsoft, Tesla, and NVIDIA. They themselves represent a third of the entire index, and you can see that they have above average valuations compared to the other 493 constituents. We also don't yet have stocks available for the AI poster kids, OpenAI or Anthropic, but those companies are likely to skew things even further, especially given that Insider report suggests highly unprofitable operations. So when those companies come to market, that's going to impact valuations further. Now, the third thing I'll highlight is that this massive earnings growth that analysts are forecasting seems to be coming predominantly from cost savings rather than rapid revenue growth. This chart here breaks it down quite well. You can see that revenue growth is actually only forecasted to grow 15.6%, which is still a lot to be sure, but it suggests that most of the earnings growth is coming again from cost savings which can only move so much. We also have to consider that if these cost savings are coming from AI adoption that at some point they'll likely be diminished by rising AI usage prices. We know that most AI companies are unprofitable at some point they're going to have to have a more sustainable pricing model. And again the current high growth we have seen is likely not sustainable long term. The CAPE ratio was actually invented to help see past these periods of unsustainable growth. So it shouldn't be completely written off. Finally, the fourth thing worth highlighting here is that costs may be underrepresented in the earnings figures we're using here. Most of the spending in AI that we've seen has come predominantly in the form of capital expenditures, buying chips, investing in data centers, things of that sort that don't actually appear on the income statement as an expense, but rather go into the balance sheet as an investment, something that will be monetized at a later date that isn't considered an upfront cost, which is important because a lot of these companies have been spending all of their earnings on AI investments. And some question the assumptions going into these accounting practices. For example, there are concerns that the chips these companies are buying will have a shorter lifespan than their accounting assumptions call for. It's why you need to treat the PE ratio with a bit of skepticism. We're effectively trying to value the entire US stock market off of A, a metric that could be skewed, and B, oftentimes one year of performance, which may or may not offer a good gauge of all future performance from here on out. So we've said a lot today, and at the same time, nothing at all. But there is a takeaway here, that being that analysts are expecting pretty meaningful earnings growth from AI here. And if things work out, even given the current stock valuations we have, stocks could experience solid performance or even good performance from here. But the good performance we've seen today is pretty abnormal from a historical basis. And there is a lot of upside already priced into stock valuations today, which leaves investors with a lot of risk. I'll treat everyone here with one more metric, the equity risk premium, which takes the inverse of the PE ratio called the earnings yield, effectively your earnings return that you achieve buying a stock at its current price, and you subtract the 10-year treasury yield. It essentially shows the marginal return investors receive for investing in stocks rather than just in treasury bonds and collecting that annual yield. On a four basis, this premium today is only around 4%, which is not as low as it was during the dot-com bubble but is still the lowest it's been in some time. What that means is that investors are taking on equity risk investing in the stock market rather than just treasury yields for a lower marginal equity return effectively. Now this is because the 10-year treasury yield has spiked recently but that itself is also a risk faced by the market given that higher treasury yields tend to act as a gravity for stock market valuations. As yields rise it can pull investor capital out of the stock market, which can be quite meaningful for AI companies that are currently relying on investor capital to fund their growth. Now, the flip side argument is that AI faces remarkable upside here. That's not going to be captured by any of these metrics. And none of this is to argue that people should be trying to time the market. If anything, the hope is to communicate just how complicated it is to answer even a very basic single facet of what's going on here, and while you should be careful with overconfidence about yes, the market is in a bubble, or no, Sam Altman and the other AI execs are going to deliver us Valhalla. And sure, maybe I didn't actually clear anything up for anyone, but hopefully it gives you a more nuanced understanding of where we are today, and hey, we had fun together, didn't we? What a fun journey that was together, huh? Thanks for watching, I hope you still found this video helpful, if you did, please do make sure to like, subscribe, all that good stuff, it does help the channel tremendously, and let me know your thoughts on the market the AI revolution and your thoughts on the different metrics we covered today thanks again and as always be safe out there