As the stock market sets record after record, many are starting to recall the dot-com bubble of the 2000s and notice certain similarities.
The popular financial advice goes: “When you hear the shoeshiner talking about stocks, it’s time to sell.” Today, the latest tech trend that everyone is talking about is artificial intelligence (AI). This phenomenon, for example, is behind the rise of Nvidia — the global leader in AI computing, which briefly became the most valuable public company in the world in June. Just a week after this spectacular surge, Nvidia’s value dropped by 14%, and many experts immediately recalled Cisco and the dot-com bubble of the late 1990s, when investors lost $5 trillion.
Indeed, these events share several characteristics. First, there are high investor expectations that new technologies will lead to significant economic changes. Second, both Cisco and Nvidia are major suppliers of IT infrastructure to their clients. Third, there are the low interest rates set by the U.S. Federal Reserve, which have fueled speculation.
Thus, it is not surprising that the question has arisen in professional circles: could the AI boom be a potential financial “bubble”? A “bubble” in the stock market occurs when the prices of assets, such as stocks or real estate, significantly exceed their fundamental value, which is determined by the expected future cash flows, adjusted for the risk of receiving them.
For example, during the late 1990s internet boom, there was widespread belief that key operations would quickly move online. Many startups emerged that didn’t fully understand how to commercialize the new trend but were full of enthusiasm and believed in the “new reality.”
Today, companies are actively investing in developing new AI models, as AI holds enormous potential for solving human problems, from simulating climate change and discovering new medicines to advancing space systems. Whether market players can effectively commercialize AI remains an open question. What works in their favor is that the IT sector has become more mature over the past decades and has accumulated a large amount of data that can be used to make effective decisions. However, it is important to consider that not all countries have legislative frameworks to regulate this field, especially in the context of growing concerns about data privacy and the rise of “robophobia.” This means that commercialization may take longer than the optimistic forecasts suggest.
Looking back at past experiences, it is worth noting that during the dot-com bubble, leaders of the tech sector demonstrated extraordinary growth. For example, companies in the top 10 grew by factors ranging from 2.5 to 35 over three years. As a result, the tech sector’s share in the S&P structure increased from 12% in 1997 to 35% in 2000.
A similar picture is emerging today: the S&P index is rising primarily due to the tech sector, but the growth dynamics are significantly weaker, with the sector’s share increasing only slightly, from 26% in 2020 to 33% in 2024.
At the peak of the dot-com bubble, the P/E (price-to-earnings) ratio of the entire S&P index rose from 19 to 30 over three years, with an average P/E of 21.6 over the last 10 years, meaning the P/E increased by 50%. In contrast, today’s P/E has only risen slightly, from 27 in 2021 to 28 in 2024, with an average P/E of 23.
A price higher than the fundamental value can be justified if investors expect high growth rates for a company’s cash flows. And there are reasons for this: Nvidia has shown excellent financial results over the past three years, with revenue growing by an average of 54% and net profit increasing by 90%. In comparison, Cisco’s figures were much more modest, yet its P/E ratio was significantly higher than Nvidia’s — 74 vs. 196.2.
Thus, while the AI boom shares similarities with the dot-com bubble, it is not yet a “bubble” — strong fundamental indicators support the high valuation, which has not yet reached the level of the dot-com bubble.
However, it is important to consider that stocks of tech companies are sensitive to economic recessions. Currently, many indicators suggest a possible recession. For example, the inversion of the U.S. Treasury yield curve is a strong warning sign of an impending recession. Additionally, the rise in unemployment claims in the U.S. may also indicate an approaching recession, which could lead to falling tech stock prices.
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