29 May 2024 – This essay attempts to answer a question I ran across on social media recently: “Is now a good time to invest in the stock market?” My knee-jerk reaction to this question, based on over half a century of armchair investment-strategy study plus a couple of decades’ experience investing my personal funds, is always: “Yes. Any time is a good time to invest in the stock market.” More specifically, the time to invest in equities is whenever you have cash available to invest in equities—regardless of transitory economic or market conditions. Being a management-science professional, however, I’m going to try to provide a little more backup for this answer.
Folks who dabble in equities markets fall into two broad categories: Traders and Investors. Traders use a market-timing strategy to achieve better-than-average gains. They hold equities for short periods of time—a few months or less (often much less)—making frequent trades in the hope of using superior investing acumen to achieve outsized gains. Their underlying assumption is, of course, that they actually possess superior investing acumen! Otherwise their results will, in the long run, confirm John Bridges’ 1587 observation that “a foole and his money is[sic] soone parted.”
Investors, on the other hand, display more humility (or a better appreciation of reality). They recognize that they do not possess superior investing acumen! Assuming they aren’t trading on inside information, don’t know something about investing that the majority of professional investors are ignorant of, and don’t have more than the typical human being’s allotment of good luck, they don’t expect to magically achieve greater than market-average gains. Their goal is to put together a portfolio of equities (stocks and bonds) that will, over time, achieve no less than market returns. This is called the buy-and-hold strategy.
The Research Project
If your goal is to meet or exceed market-average gains, you probably should know what constitutes average market gains. That’s where I can make a contribution because I’ve spent a lot of time over recent decades building skills for data analysis. I should, therefore, be capable of analyzing the vast treasure trove of economic data that folks have been amassing for…a very long time!
A couple of years ago, I started a research project to figure out how and why markets behave as they do. First, I decided to concentrate on the U.S. economy because not only is it the one I happen to be immersed in, but it has historically been pretty stable. Especially, the period between the Great Depression and the economic shock of the COVID-19 pandemic was one of relatively mild economic and social disruption. At least, there was little in the way of Shakespeare’s “slings and arrows” directed at the U.S. economy by “outrageous fortune” (AKA the outside environment).
The how is easy. Just seek out economy-related data collections and graph the data. The data is out there in freely available public databases. Professionals have been obsessively monitoring and recording everything of economic interest for well over a century. Specifically, overall economic performance, measured as gross domestic product (GDP) per person, is tracked by the Bureau of Economic Analysis (BEA), an agency of the U.S. Department of Commerce. The BEA publishes annual GDP data nominally (without correction for inflation) and as real data (corrected for the effects of inflation). You just go to their website and download it for free.
Market-performance data is tracked on various timescales and published in real time by the companies that run the markets. Market indices (e.g., Dow-Jones Industrial Average, or DJIA) are compiled from stock prices and published in near real time by various organizations (e.g., S&P Dow Jones Indices LLC produces the DJIA). I decided to use DJIA because it is marginally the longest-running market-data index extant.
The why takes a little more cogitating.
To begin with, it’s important to understand how markets work. That is, the mechanisms that determine prices of goods and services that make civilized society possible. Folks have tried to understand how this works for as long as people have used specialized labor to fulfill their needs and wants. The earliest attempt (that we know about) to explain such economic ideas was written by the ancient Greek poet Hesiod. His Works and Days (Hesiod, ca. 700 B.C.E.) vaguely hinted at the idea that prices for goods and services depended on a balance between their supplies and demands. In the 17th century, John Locke accurately described the workings of the Law of Supply and Demand, but it was not until the late 18th century that Adam Smith provided a coherent explanation, and not until the mid-20th century that Friedrich Hayek used the law to explain how markets determine prices of securities through negotiations between buyers and sellers.
Finally, in 2022 Glendon Williams and I showed that Hayek’s mechanism for setting equities-market prices involved a trend based on long-term GDP growth plus a chaotic “excess volatility” that defied accurate prediction but averaged out to nothing (Masi & Williams, 2022). The graph at the top of this posting shows the results for the “quiet” period between the economic shock of the Great Depression and that of the COVID-19 pandemic. The smooth red line is an increasing-exponential model that tracks the growth of the U.S. GDP per person quite accurately, while the jagged blue line shows the DJIA market index. The excess volatility is the difference between the two. Our 2022 analysis showed it to display signs of chaos.
Comparing the Strategies
The buy-and-hold investment strategy relies on maintaining a portfolio of equities whose prices, on average, mimic the underlying GDP trend line while using portfolio diversification to smooth out the excess volatility. It turns out that this long-term trend has a growth rate of just under five percent (5%) per year. This is approximately three times the size of the excess volatility that traders attempt to take advantage of by timing the market.
If (and only if) an individual trader is able to predict the rapid swings of the excess volatility, and make trades that track those variations accurately enough, they can achieve additional gains. Any mistakes in timing their trades can, of course, be disastrous.
The fact that this excess volatility is chaotic means it follows Zipf’s Law. This law applies to many natural systems that behave chaotically. In general, it says that in any finite system, there is more room for little things than for big things. That is, if you graph the number of things in any population against the size of those things, you find a decreasing power law: There are more little things than big things. In this case, the frequency of variations in the excess volatility is inversely proportional to their size. This means that the shorter your trading time scale (i.e., the more often you trade) the smaller the difference between your selling and buying prices can be, so the smaller your profits can be for any given trade.
What I haven’t yet pointed out here is the fact that everyone—all traders at least—is trying to time the same market. If you think you’ve found a pattern in the excess volatility of some equity or group of equities, you may be able to exploit it to achieve spectacular gains for a while. In time, however, everyone else finds the same pattern and tries to exploit it. That changes the pattern! Suddenly it shifts so that instead of buying low and selling high, you find yourself buying high and selling low! That erases your once-spectacular gains with spectacular losses. That is how chaos works: Short-term predictability more-or-less quickly turns into long-term unpredictability.
