By: Russ Kamp, CEO, Ryan ALM, Inc.
Black Monday’s 39th anniversary came and went with little fanfare. I can recall quite vividly the events surrounding the U.S. equity market’s largest single day decline and wondering at the time if I was going to have a job by the end of that week. For those of you who were working on Wall Street (or even born) at that time, you’ll remember that the Dow declined 108.35 points (-4.6%) on Friday, October 16, 1987, making for a very long weekend, as we wondered what might happen next. I certainly didn’t expect a 508-point decline (-22.6%), and I suspect that most didn’t either. Importantly, the crash didn’t emerge from a weak market. The Dow had risen an extraordinary 44% in the first seven months of 1987, before peaking in August.
As I reflect on that time, I wonder if there are similarities to today’s investing environment, including valuations, interest rates, market concentration, and a powerful theme driving market enthusiasm that should give us some pause.
1. Valuations: Current valuations are stretched, and perhaps more so than in 1987. The Shiller CAPE is currently about 40.7, versus a historical mean around 18. The only comparable recent example was the 1999–2000 technology bubble (44). Another period of note was in September 1929, when the CAPE was about 32.6. If you aren’t a fan of the Shiller CAPE, another current valuation measure puts the S&P 500 at roughly 21× forward earnings. Like any valuation measure, they aren’t timing tools, but they do tell us investors are paying a very high price for future earnings that might limit future gains.
2. Interest Rates: U.S Treasury yields have risen significantly since bottoming in 2020, achieving a level that makes bonds serious competition for stocks. In 1987, the 10-year Treasury note began the year with a yield of 7.2%. By September 30, 1987, that yield hit 9.63%, providing an extremely attractive alternative to equities. Today the absolute yield is much lower at 5.11% (9:13 am) but that’s up considerably from the near-zero-rate environment in which many of today’s equity valuations were established.
3. Market Leadership: Today’s S&P 500 has become increasingly dependent upon a handful of mega-cap technology/AI companies. S&P Global specifically warns that the Magnificent Seven increasingly behave like a single AI-related risk factor, rather than seven independent sources of diversification. In a note from Glen Eagle, they point our that the five largest companies in the S&P 500 are currently so massive that they are worth the same as the bottom 434 stocks in the index combined.
4. Powerful Narrative: Today’s investing narrative surrounding AI may be more obvious than that which was driving markets in the mid-’80s, but not necessarily more powerful. In 1987, markets had experienced years of deregulation, financial innovation, globalization, and economic expansion following a prolonged period of rising rates, that began to reverse in 1981. As I’ve written in previous blog posts, I don’t question AI’s transformative potential. I question whether today’s prices and enormous capital expenditures can generate sufficient economic returns to justify those investments.
I’m certainly not suggesting that equity markets may see another -22% drop in a single day, as I witnessed 39-years ago. Importantly, today’s markets have circuit breakers. A 7% S&P 500 decline triggers a Level 1 halt, while a -13% triggers Level 2, and -20% triggers Level 3, ending trading for that day. These circuit breakers don’t prevent a major decline, but it makes a repeat of October 19th’s –22.6% single day decline much harder to replicate.
Final thought: In 1987, the market crash itself created the crisis. Today, I wonder whether the capital cycle could create the equity correction, as everything AI is consuming enormous amounts of capital and driving interest rates up in the process. Hyperscalers are spending hundreds of billions of dollars, with potentially trillions of $s yet to be invested. Data-center developers are borrowing heavily well before they are likely to see a return on that investment. Power infrastructure requires still more capital, as capacity seems inadequate to meet future demand. As I wrote about last week, CoreWeave debt has repriced dramatically, where their bonds issued at a yield of 9+% during the summer are now trading at roughly 16%. If AI infrastructure returns ultimately fail to exceed these increasingly expensive financing costs, investors may begin questioning the earnings assumptions embedded in AI-related equity valuations. If that happens, all bets are off!
