In the financial markets as in life, there are striking divergences between the haves and the have-nots. The rich get richer and the poor get poorer – and similarly, the large-caps get larger while the small-caps get smaller.

It’s shocking but perhaps not surprising in a time when some people practically worship the handful of technology companies that are currently leading and supporting the S&P 500. Among them is Apple, which just announced a pair of virtual reality goggles that some folks are apparently eager to buy at a starting price of $3,499.

It won’t be available until next year, but you can be sure that shoppers will line up for the $3,499 headsets instead of just waiting a few more months and then buying them at a significant discount. When hype rules the tech landscape, price distortions are all too commonplace.

The analogy isn’t hard to see here, as financial traders are eager to buy Apple stock at $180 even though it was worth $125 at the beginning of the year. Perhaps they’re pricing in the assumption that a $3,499 headset will be a bestseller; if so, then Apple now has to live up to that expectation.

Still, Apple stock isn’t the frothiest of the bunch. The latest celebrity stock is a surprising winner of the AI arms race: Nvidia, which supplies the types of chips that are needed to run power-intensive generative AI applications.

The result is a data set that should make any value investor bristle: Nvidia currently trades at 204.4 times earnings, 135.06 times sales, and 50.44 times the company’s book value. But then, who’s even reading the book anymore when analysts are climbing over each other to praise Nvidia, the newly crowned king of AI hardware?

Courtesy: Charles Schwab, Bloomberg

The implications of this reach far beyond the small number of tech leaders in the S&P 500. While most technology stocks are above their 200-day mean, the majority of other sectors are either just average or below average; the worst laggards are financials, energy, and utilities stocks.

To put it another way, most stocks aren’t participating in the ongoing rally in large-cap U.S. stocks. Thus, we have an appearance of a sustainable S&P 500 rally, but that index is really only being held up by a few richly valued tech names.

This is possible because the S&P 500 is weighted by market cap, so you have the biggest companies (which, unsurprisingly, happen to be famous tech titans like Apple, Google, Microsoft, etc.) being strongly represented in the index. Meanwhile, hundreds of comparatively smaller listed companies have very little influence – individually, and even collectively – over the S&P 500.

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    Again, the rich only get richer. As these technology stocks move higher, analysts are practically forced to raise their price targets; financial traders then celebrate these price-target hikes by purchasing more shares. It’s a virtuous cycle, assuming greed is a virtue.

    Here’s another way to look at it: If you track an equal-weighted index of the S&P 500 (which you can actually do through the ETF with the ticker symbol RSP), you’ll notice that it’s actually on a downtrend, not an uptrend. Yet, the actual S&P 500 isn’t egalitarian, so it’s able to hide the laggards and deceive the inattentive and uninformed.

    Courtesy: Bloomberg, Liz Young

    The extreme outperformance of “info tech” stocks relative to the S&P 500 overall (shown above) can create rare and bizarre disparities and dislocations. Whether this is tradable is a different story entirely, though: Would you dare to short-sell tech stocks and risk getting run over by a steamroller?

    I certainly don’t recommend that, as the market can remain irrational longer than any of us can remain solvent. The most sensible approach, as I see it, would be to trim any large-cap tech-sector holdings that are up by double-digit percentages this year.

    Then, start looking for new opportunities that hardly anybody’s talking about. Just imagine the returns you would have gotten by investing in AI-related stocks prior to 2023, or e-commerce stocks a decade ago.

    You could potentially achieve similar results by looking forward in your research instead of looking at whatever outperformed today and yesterday. Or, you can take your chances with a deceptive, lopsided benchmark index with 500 components but only a few that actually move it.

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