IS THE STOCK MARKET too high? It’s a question I’ve heard a lot recently. Each time, I’ve offered this recommendation: It’s impossible to predict where the market will go next, so your best defense is to have an appropriate asset allocation. But how exactly can you determine an ideal allocation?
The textbook method originated in the 1950s, with the work of a PhD student named Harry Markowitz. Up until that point, investors had mostly picked stocks and bonds in a vacuum, without giving much thought to how each individual investment might interact as part of a larger portfolio. In other words, the concept of diversification was not well understood and received little attention.
Even Benjamin Graham, who came before Markowitz and who’s considered the father of investment analysis, never talked about diversification in his work. For Graham, the question was always, “Is this specific investment a good choice?” It was never, “What combination of investments should I choose?” Then came Markowitz, who made the observation that the second question was at least as important as the first.
This is how Markowitz described it in an early article: “A portfolio with sixty different railway securities, for example, would not be as well diversified as the same size portfolio with some railroad, some public utility, mining, various sorts of manufacturing, etc. The reason is that it is generally more likely for firms within the same industry to do poorly at the same time than for firms in dissimilar industries.”
In other words, if you’re trying to build a diversified portfolio, you need to do more than simply buy a collection of assets. Instead, you need to buy a collection of assets that you expect to behave differently from one another—in statistics talk, to exhibit low correlations with one another. While this might seem obvious today, it wasn’t obvious in 1952 when Markowitz published his first paper. His work was so new, in fact, that it came to be known—and is still known—as Modern Portfolio Theory (MPT).
The mathematical details are dense, but the promise of MPT was appealing. You may have heard the term “efficient frontier.” This was Markowitz’s invention, and it lies at the heart of his framework. In simple terms, the efficient frontier offers investors a menu of “efficient”—or optimal—portfolios to choose from. Each portfolio is optimal because it offers either the maximum potential return for a given level of risk, or the minimum amount of risk for a given level of return.
Suppose, for example, your goal is to earn 5% annual returns. You could simply locate that point on the efficient frontier, and it would tell you how to construct a portfolio geared to that goal. Prefer 7% returns or maybe 10%? Those options, along with others, could all be found on the efficient frontier.
The efficient frontier can be used to build a portfolio of stocks, as Markowitz illustrated in his initial work. It can also be used—and today is more commonly used—to build portfolios that combine multiple asset classes. Suppose, for example, you wanted to build a portfolio combining stocks, bonds and real estate. An efficient frontier could provide you with the optimal combinations of those asset classes—or any others. For this reason, MPT seems ideal.
But here’s the problem: It’s a little too good to be true. To build an efficient frontier requires that you have data about the future—and not just a little bit of data, but a lot. Here’s the data you need for each asset class:
All of this data is readily available on a historical basis, of course. But it’s impossible to predict going forward. William Bernstein, writing in his book The Intelligent Asset Allocator, described the problem this way: “It’s a little like trying to generate electrical power by placing a battery and a lightning rod at the last place you saw lightning strike. It isn’t likely to strike there again.”
As Bernstein notes, “Next year’s efficient frontier will be nowhere near last year’s.” To illustrate, he cites Japan’s stock market, which peaked in 1989 and still—more than 30 years later—hasn’t fully recovered. If you had built an efficient frontier using data prior to 1989, it would have recommended a hefty allocation to Japan. But data since 1989 would recommend the opposite. In short, Modern Portfolio Theory, as appealing as it sounds in theory, is difficult to implement in practice.
That said, Markowitz’s fundamental insight—for which he won a Nobel Prize—does carry a key lesson for every investor: Correlations are paramount. I can’t tell you when or if the stock market will see a correction. But the good news is, you don’t need to worry about building a strictly optimal portfolio, in the textbook sense, to protect yourself. You just need a sensible mix of stocks, bonds and other asset classes that aren’t tightly correlated. As you think about your portfolio and the risk posed by today’s stock prices, this is, I think, the most important thing.
Adam M. Grossman is the founder of Mayport, a fixed-fee wealth management firm. In his series of free e-books, he advocates an evidence-based approach to personal finance. Follow Adam on Twitter @AdamMGrossman and check out his earlier articles.