by Bill Smead and Cole Smead, Smead Capital Management
We’ve been doing a great deal of reading about prior exciting and maniacal periods in the U.S. stock market. This is as much to remind us of why the tortoise won the race in Aesop’s fable. Once in Golconda and The Go-Go Years by John Brooks covered the 1920s and 1930s (Golconda), as well as the late 1960s (Go-Go). Eboys, the story of Benchmark Capital and eBay, covered 1998-2000. Most recently, we read a terrific article in The Wall Street Journal titled “Spending on AI Is at Epic Levels. Will It Ever Pay Off,” written by Eliot Brown and Robbie Whelan.
The purpose of all this reading is to gain historical context for where we are in the normal historical cycles of the stock market (and to figure out when the hare is going to run out of gas). The great investor Sir John Templeton always said, “There will always be bull markets followed by bear markets followed by bull markets.” Therefore, let’s analyze where we are in the market cycle to see if this exuberance is giving us the right warning. Remember, for all intents and purposes, we have been in a bull market off and on since March of 2009, with numerous violent and/or short-term interruptions.
The first thing we learn from the 1920s, 1960s and late 1990s mania was that it was rooted in excitement about technology. There were 4,000 cars sold in 1900 and 2.5 million sold in 1925. Airplane travel started in the 1920s. In 1923, we started with 1% household penetration of radio ownership and finished in 1937 with 75% ownership.
The 1960s were all about the space race and all the technologies born out of those expenditures. The semiconductor was one of those emerging technologies (Intel went public in 1971), just in time for the 1973-1974 bear market slaughter. Lastly, the Internet of things was the technology that drove the mania that peaked out in early 2000. Ebay went public at $18 and quickly rose to over $600 per share. I personally was using it as my poster child for what was wrong with the mania at the time, but loved that they were trying to become the New York Stock Exchange of pre-owned items. We bought many shares in 2008 below the original offering price.
The second thing we learn is that spectacular long-term bull markets stretched investor confidence in each of these episodes. However, warning shots were fired across the stock market’s bow well before the massive declines that came afterward. In the 1920s, the transition away from agricultural employment, the 1925 collapse of the Florida land bubble and the 1929 stock market crash teamed up to lay the groundwork for the Economic Depression of the 1930s. In the 1960s, it was U.S. Vietnam War debts and the inflation caused by the baby boom of the 1950s and 1960s that killed the goose that laid the golden eggs. In the late 1990s, Fed Chairman Alan Greenspan identified the mania as “irrational exuberance” about 30 months before it died. He raised interest rates dramatically and helped to strangle the bull market from 2000 to 2003. Most of the stars of 1999 got washed out, and Microsoft, Intel and Cisco took years to get even (MSFT) or never have (CSCO and INTC).
This brings us to today’s mania courtesy of The Wall Street Journal:
The windswept town of Ellendale, N.D., population 1,100, has two motels, a Dollar General, a Pentecostal Bible college—and a half-built AI factory bigger than 10 Home Depots.
Its more than $15 billion price tag is equivalent to a quarter of the state’s annual economic output.
Money is being spent building out AI capabilities like drunken sailors on leave. It looks a lot like Lucent Technologies, which loaned the equivalent of 45% of annual revenue to customers to buy their products in 1999!
Brown and Whelan go on:
The artificial-intelligence boom has ushered in one of the costliest building sprees in world history. Over the past three years, leading tech firms have committed more toward AI data centers like the one in Ellendale, plus chips and energy, than it cost to build the interstate highway system over four decades, when adjusted for inflation. AI proponents liken the effort to the Industrial Revolution.
A big problem: No one is sure how they will get their investment back—or when.
The building rush is effectively a mega-speculative bet that the technology will rapidly improve, transform the economy and start producing steady profits. “I hope we don’t take 50 years,” Microsoft CEO Satya Nadella said at a May conference with Meta CEO Mark Zuckerberg, referring to the initially slow adoption of electricity.”
The following chart shows an amazingly intertwined set of AI-oriented companies investing in each other, while selling to each other:
History says that the hare will exhaust itself and the tortoise will keep cruising along at a steady pace. We continue to own meritorious companies with very repeatable products with solid balance sheets and defendable market positions. We are hopeful, just like in 2000-2002, when the tortoise ran out of gas, that a slice of the money which came out of the maniacal sectors will reach out-of-favor industries like energy (APA Corp. [APA], Diamondback Energy [FANG], ConocoPhillips [COP], Occidental Petroleum [OXY]), healthcare (Merck [MRK], Amgen [AMGN], UnitedHealth [UNH]) and homebuilders (D.R. Horton [DHI] and Lennar [LEN]), to name a few.
In the fable, slow and steady wins the race. Back in 1998-2000, at the height of the tech mania, the portfolios I was running at the time made no money while the internet hare was running at max speed. However, 45 years of experience tell us that the risk-reward relationship is heavily leaning toward the tortoises of the investing world.
Play the Long Game,
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The recent growth in the stock market has helped to produce short-term returns for some asset classes that are not typical and may not continue in the future. Margin of safety is the difference between the intrinsic value of a stock and its market price. The price-earnings ratio (P/E Ratio or P/E Multiple) measures a company’s current share price relative to its per-share earnings. Alpha is a measure of performance on a risk-adjusted basis. Beta is a measure of the volatility of a security or a portfolio in comparison to the market. FAANG is an acronym for the market’s five most popular and best-performing tech stocks, namely Facebook, Apple, Amazon, Netflix and Alphabet’s Google. Growth investing is focused on the growth of an investor’s capital. Leverage is using borrowed money to increase the potential return of an investment. Momentum is the rate of acceleration of a security’s price or volume. The earnings yield refers to the earnings per share for the most recent 12-month period divided by the current market price per share. Profit margin is calculated by dividing net profits by net sales. Quality is assessed based on soft (e.g. management credibility) and hard criteria (e.g. balance sheet stability). Value is an investment tactic where stocks are selected which appear to trade for less than their intrinsic values. The dividend yield is the ratio of a company’s annual dividend compared to its share price.
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