The Big Picture
Briefing.com Summary:
*Markets are struggling to price AI's long-term impact, creating volatility and delaying broad-based confidence in future earnings durability.
*Earnings growth remains strong, but surprise levels haven't been as strong.
*Companies across industries must prove AI enhances profitability rather than disrupts business models and compresses profit margins.
We are going to share a story about valuation. It is going to begin with a picture and end with a twist.
Multiple Compression
We have seen some multiple compression to begin the year thanks largely to a rollback in many of the mega-cap stocks. Specifically, the S&P 500 entered 2026 trading at 22.1x forward twelve-month earnings and 25.4x trailing twelve-month earnings. Today, those P/E multiples sit restlessly at 21.8x and 25.1x, respectively.
In other words, they haven't come down that much and are still stretched appreciably relative to averages covering the period from 2000 to present. Another interesting consideration is that the multiple compression stems from earnings growth rising faster than prices.
The S&P 500 is up 0.2% year-to-date versus a 3.0% increase for the forward twelve-month estimate and a 3.2% increase for the trailing twelve-month estimate. On the plus side, these things are all moving in the right direction, but on the downside, the existing stretched valuations are standing in the way of multiple expansion.
Said another way, the good earnings news has been mostly priced in. That is partly why a stock like NVIDIA (NVDA) would trade down 5.5% after the AI leader reported quarterly revenue up 73% year-over-year, a non-GAAP gross margin of 75.2%, and adjusted diluted EPS up 82% year-over-year.
Positive Feedback Loop
There were other factors involved with NVIDIA's post-report decline, as was the case with Amazon's (AMZN) post-report decline, Microsoft's (MSFT) post-report decline, and declines in many stocks, either immediately after their reports or in subsequent weeks, like in the cases of Meta Platforms (META), Tesla (TSLA), and Alphabet (GOOG/GOOGL).
The hangup for NVIDIA is that its results were too good. Investors appeared skeptical that NVIDIA could continue to deliver the same monstrous growth as it contends with the law of large numbers, budding competition, and a potential scaling back of capex budgets by the hyperscalers.
Ironically, hyperscalers faced investor backlash for investing too much in their AI buildout plans without a quantifiable pathway to meaningful returns on their investment. At this point, it is a bill of sale that the returns will be there eventually. Other companies, meanwhile, got pummeled on the notion that their business models, cash flows, and earnings prospects will be weakened by the rise of AI models, tools, and agents borne out of the heavy investment in AI.
This positive feedback loop has thrown the market for a loop to begin the year, never mind that each of the major indices is higher year-to-date.
The fact that the consumer staples sector has outperformed the information technology sector by nearly 2100 basis points year-to-date and the financial sector by nearly 2300 basis points, that the 10-yr note yield has declined 20 basis points, and that the CBOE Volatility Index is up 34% underscores how loopy the stock market has been even though the earnings growth, in aggregate, has been better than expected... or has it?
The S&P 500 is on pace for its fifth consecutive quarter of double-digit earnings growth. According to FactSet, companies, in aggregate, have reported earnings 7.2% above expectations, but here is the relative rub: that is below the one-year average of 7.4% and the five-year average of 7.7%.
In short, the fourth-quarter earnings reporting has been good, as expected. It just hasn't been as good as past periods from a surprise perspective, so it hasn't led to multiple expansion.
Briefing.com Analyst Insight
When you have a rich valuation, it gets harder to provide a true positive surprise. The reason being is that the rich valuation is a byproduct of investors frontrunning the expected good earnings news, so much so that by the time the good earnings news arrives, it is already in the stock price (and then some).
It gets even harder, though, when doubts emerge about being able to follow through quarter after quarter with impressive earnings results. That is the predicament the mega-cap stocks find themselves in, and the predicament many other industries are facing with respect to being disrupted by AI advancements.
That is why the market cap-weighted S&P 500, anyway, has been range-bound since October even though the forward twelve-month earnings estimate has continued to be revised higher.
The hyperscalers are going to have to prove that they are getting meaningful returns on their massive AI investments. Hardware companies that need memory are going to have to prove that the spike in memory costs is not adversely impacting their profit margins. Software companies are going to have to prove that they aren't being disintermediated by AI tools. The same goes for logistics companies and financial services firms, and right on down the line.
AI is a change agent, but it is unclear to what degree for just about every business out there. It will be better for some than others, but every publicly traded company is a show-me story now.
How long it takes to convince investors that AI is a change agent for the better is the great unknown. That uncertainty will be a headwind for multiple expansion, certainly at the index level, which is dictated by the behavior of the mega-cap stocks, but it will infiltrate (and already has) other industry groups.
It will take some patience to watch things get sorted out. We expect many twists and turns along the way. We just don't expect any significant multiple expansion at this juncture when the AI plot twist has thickened.
