Are markets over- or under-valued?
It's 2020, and COVID-19 has upended the world economy, ending the longest bull market in the history of bull markets. Investors who had been waiting on the sidelines because they considered the market to be overvalued are now still waiting on the sidelines for the dust to settle...by which time the market will likely be back to prior levels, thus starting the dance again.
So: which is it? Are the markets over- or under-valued? What does that even mean?
The Efficient Market Theory, or: don't bet against the house
As I mentioned recently, the value of a share of stock takes into account not just present circumstance, but the future, and is a combination of many different predictions and probabilities. As the present continues its inexorable march towards said future, the value will adjust as the probabilities tend towards certainty one way or the other.
So in theory, making money in the stock market is simple: find those stocks whose prices indicate an incorrect set of probabilities, and buy (or short) accordingly. Once the present becomes the future and you are proven right, the price will adjust accordingly, and you can sell and make your profit. Wash, rinse, repeat. Easy, right?
The efficient-market hypothesis, in a nutshell, states that this is a loser's game. Well, technically, it doesn't say that; rather, it states that "asset prices reflect all available information". In other words, speaking in the language above, the probabilities indicated by an asset's value are always correct.
(Some parenthetical geekery on the EMH)
Now, I could stop there, but we're all nerds here, so let's talk about the EMH some more. First, why is it a called a "hypothesis"? Engineers get hung up on this, because they come from a natural science background: hypotheses are tested, and when proven, become a law. So the fact that this is a hypothesis and not a law means that it's flimsy at best, right?
Markets are based on statistical analysis of human behavior, not natural science. In statistical analysis, hypotheses are used differently that in natural science: rather than attempting to prove a universal truth, they are used to to determine a truth specific to the particular experiment. If you know enough statistics to be familiar with the null hypothesis, you know exactly what I'm talking about: the null hypothesis is how you figure out whether the conclusion you're attempting to draw from the data is real or just a result of sampling error. It's a tool, not a postulate about the universe.
The EMH is exactly the same: it's a hypothesis you apply to a given model of risk and sample of data in order to determine whether you can effectively outguess the markets. The EMH itself doesn't specify a specific risk model, so by definition you can't actually prove or disprove it! And thus engineers like you and me get confused, even though the statisticians know exactly what they mean.
In reality, there is a lot of evidence in research going back nearly 100 years that the efficient market hypothesis holds true in most markets, especially ones that have the structural advantages of the stock market. Given this, some people (properly) refer to the efficient-market theory when discussing it in a broader context. Why it hasn't caught on more, I don't know.
And while we're nerding out, there are three different forms of the Efficient Market Hypothesis: strong (testing whether all information and historical prices are included in the current price), semi-strong (testing whether all public information and historical prices are included in the current price), and weak (testing whether historical prices are included in the current price). Why divide them up this way? Testing the strong, semi-strong, and weak forms determine whether you can consistently outguess the given market with insider information, fundamental analysis, and technical analysis, respectively.
What efficient-market theory means to you, Mr. Investor
But enough geekery: why do we care? Efficient-market theory (as I'm going to call it from now on) says that the markets are correct, that you can't consistently outguess them. Why not? Because given that the probabilities are correctly included in the prices, betting against the market means consistently betting on low-probability outcomes, and eventually the Law of Large Numbers will catch up to you.
Note, however, that this doesn't mean the market is always "right"; just because something is only 20% likely to happen doesn't mean that it won't! In other words, you could simply get lucky -- and in a system as complex (and poorly understood!) as the stock market, it's very, very difficult for us humans to discern skill from luck. Even engineers. Especially engineers!
Moreover, you have to be right and timely. So you say that a given asset is over- or under-valued, and that eventually the price will reflect the reality that you have predicted. When is "eventually"? Tomorrow? Next year? Ten years from now? Ten years is a long time to wait...and in the meantime, you're suffering the opportunity cost of the other investments you could have made!
Another way of thinking about it is this: efficient-market theory says that there is no such thing as over- or under-valued in the stock market. The market reflects the actual value at the time. It's like Gandalf says: "A wizard is never late, nor is he early. He arrives precisely when he means to."
If there's no such thing as under- or over-valued, then is it true that the only thing to do is invest in the market and go where it takes you? Not exactly. Just because prices are set efficiently doesn't mean there's nothing you can do to optimize your investments.
First and foremost, there's always cost. The ETF's and mutual funds you invest in come with a price tag, and research consistently shows an extremely clear correlation between lower cost and higher performance. Want to outperform the pack? Pick a lower cost solution. That's not to say that low cost is the end-all and be-all -- but it's important!
There's also your asset allocation. Uncorrelated asset classes are one of the cornerstones of good portfolio design: by investing in asset classes whose volatility is out of sync with each other (stocks v. bonds v. real estate v. other alternatives), you can achieve a sort of "noise-cancellation" effect which can potentially lower volatility while keeping returns intact. Sadly, I've yet to find a portfolio that works as well as Bose headsets, but the benefits are tangible!
Also, some ETF's and mutual funds make use of a similar phenomenon by tilting their holdings towards multiple "factors of increased returns" -- small stocks, value stocks, profitable stocks, etc. While these increased returns generally come with higher volatility, the better funds are able have the best of both worlds.
Finally, let's not forget about taxes! In your taxable accounts, you can engage in tax-loss harvesting to defer taxes, and you can also implement tax-efficient asset location, putting the optimal asset classes in the optimal types of accounts.
A final note: while all of these can lead to outperformance over the general market or a given benchmark, the benefits are almost always incremental. The Big Goal is to set up an asset allocation that matches your risk tolerance and risk capacity, and everything else is gravy. Getting "just" the market return is a huge win over leaving the money in a savings account!
Britton is an engineer-turned-financial-planner in Austin, Texas. As such, he shies away from suits and commissions, and instead tends towards blue jeans, data-driven analysis, and a fee-only approach to financial planning.