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Traders work on the floor of the New York Stock Exchange in New York City on June 5.BRENDAN MCDERMID/Reuters

Back in 1923, writer and journalist Edwin Lefevre wrote, “Nowhere does history indulge in repetitions so often or so uniformly as in Wall Street. When you read contemporary accounts of booms or panics, the one thing that strikes you most forcibly is how little either stock speculation or stock speculators today differ from yesterday. The game does not change and neither does human nature.”

The S&P 500 has been on a tear since the beginning of the year and recently it entered bull-market territory. But if you exclude the U.S.’s seven largest tech stocks, which were up more than 53 per cent year to date, the S&P 500 was mostly flat over the period.

Many wonder whether we have we seen this movie before and whether another bubble is being formed, one that will target the most profitable U.S. tech stocks. For the first time in the last 40 years, we may be witnessing a bubble forming around highly profitable companies, as opposed to prior bubbles that were centred on unprofitable ones. It has happened before, though, involving the 50 large-cap/blue chip stocks on the New York Stock Exchange, which in the 1960s propelled the bull market higher and subsequently crashed and underperformed.

Growth is difficult to assess with any precision, so investors tend to overpay for it. You can buy the best company, but if you overpay you will not make any money. For example, researchers at the Darden School of Business examined a portfolio of high-growth companies, comparing it with that of low-growth companies over the period 1968 to 2007. They found that the low-growth stock portfolio, on average, outperformed the high-growth stock portfolio by 22 per cent per year. Valuation risk is a lot higher in high-growth companies.

But what is a bubble? A bubble is defined as a significant deviation of an asset’s price from its fundamental value.

Which begs the question: What drives the fundamental value of the stock market? Fundamental value is a function of profits and the return investors expect. Or, as it is easier to understand, fundamental value is a function of profits and an earnings multiple. The earnings multiple is, in turn, a function of expected returns, driven by interest rates, while profits are a function of revenues, driven by the state of the economy, and costs, driven by the state of the labour and commodity markets.

The lower the expected return, the higher the earnings multiple and equity values. Similarly, the higher the profit expectations, the higher the equity values.

Bubbles and their chances of bursting are difficult to see until it is too late. They need a catalyst to burst – and historically, the most frequent catalysts have been rising inflation and interest rates. Bubbles, and related exuberance, encourage large amounts of borrowing and margin investing, both of which suffer when rates rise. Moreover, fast-growth companies, whose valuations incorporate over-optimistic assumptions about the future, are severely impacted by rising interest rates and downwardly revised profit expectations.

Large-cap U.S. tech stocks are currently trading at extreme valuations. Nvidia trades at a PE ratio of 205x, Apple 30x, Tesla 62x and Alphabet 28x earnings. The S&P 500 PE is 24x, the U.S. tech sector PE is 42x and the semiconductor 51x. Large-cap tech stocks are expensive relative to markets in general and to historical averages. Tech companies are booming based on optimism and related artificial-intelligence euphoria that global productivity will soar with the new technologies and the belief that inflation and interest rates are heading down.

What will happen if the markets realize that inflation and interest rates are on a secular upclimb, and that euphoria about productivity improvements based on AI is overblown? In this case, falling earnings multiples and profit expectations will burst the bubble.

We should never forget AI involves machines not people, and can be inaccurate, incomplete or biased. In my opinion, AI and machine learning will not be able to replace investor insight and “between the lines” reading of nuanced economic numbers, will not significantly reduce the demand for labour to the extent markets expect and will not be the panacea about profitability expected by the markets. And inflation and interest rates are, in my opinion, on a secular rise, despite the short-term business cycle downward effect we are currently witnessing.

Nobel Prize-winning experimental economist Vernon Smith has demonstrated via experiments that investors (both novices and professionals) are normally overconfident momentum traders chasing winners and avoiding losers, a process that according to his experiments eventually leads to bubbles and market crashes.

While quant funds were doing much of trading earlier this year, recently the fear of missing out on AI and the belief that the U.S. Fed has won the fight against inflation have incentivized retail investors to enter the market in mass with their net purchases of U.S. stocks hitting US$1.5-billion on May 30 and 31, as reported by VandaTrack.

It is well-known that retail investors are the worst market timers, as a recent study by Blackrock clearly indicated. The study showed that while the average equity fund in the U.S. made about 8 per cent over a 30-year period, investors who invested in these funds made only about 2 per cent. How is this possible? It is because retail investors are trying to time the market. They are exuberant at market peaks and buy, and panic stricken at market bottoms, when they sell. Their timing, unfortunately, is upside-down.

George Athanassakos is a professor of finance and holds the Ben Graham Chair in Value Investing at the Ivey Business School, University of Western Ontario.

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