The dotcom boom, one of the most extreme speculative bubbles in market history, reached its peak 25 years ago today.
Easy capital fuelled a frenzy of overvaluation in internet-related stocks, which spectacularly crashed when reality caught up to the hype. This sent shockwaves through financial markets and reshaped the tech landscape for years to come.
A quarter of a century on from the bust, six industry experts reflect on lessons learned and if there are any parallels with today’s tech sector.
Dom Rizzo, portfolio manager of the T. Rowe Price Global Technology Equity strategy
Reflecting on the dotcom bubble, one of the key lessons learned is the importance of distinguishing between speculative hype and sustainable growth. During the late 1990s, valuations soared to unsustainable levels, driven by speculative metrics like ‘clicks’ and ‘eyeballs’. Today, while AI is a major driver of market enthusiasm, the current cycle is underpinned by tangible earnings growth and real demand for AI applications, which sets it apart from the dotcom era.
AI has the potential to be the most significant productivity enhancer since electricity, offering deflationary benefits by reducing costs and boosting efficiency across industries. However, as with any technological revolution, there is a risk of speculative excess. Currently, we do not observe AI valuations reaching the extreme levels seen during the dotcom bubble, but vigilance is necessary. The market’s healthy scepticism towards AI-related valuations today contrasts with the unchecked exuberance of the late 1990s.
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A critical difference in today’s tech dominance is the financial robustness of mega-cap IT companies, which are funding AI advancements with substantial free cash flows, unlike the debt-laden dotcom firms. This financial strength provides a more stable foundation for growth.
Additionally, the focus on ‘picks and shovels’ investments, such as semiconductors and infrastructure, mirrors the strategic approach of investing in foundational technologies during the early internet era.
Investors must navigate these cycles with prudence, recognising that technological innovation often follows an S-curve trajectory rather than a linear path. While AI presents a generational investment opportunity, it is crucial to remain aware of cyclical patterns and potential supply chain disruptions. By learning from the past, we can better manage the risks and opportunities of today’s tech-driven market.
Greg Eckel, portfolio manager of Canadian General Investments
We lived through an era that was both embryonic and chaotic. The prevailing belief at the time was that capturing ‘eyeballs’ and subscribers would inevitably lead to riches. However, without sustainable business models, uncertainty prevailed, and many ventures collapsed. While technology advanced, the infrastructure and economic foundations were not ready to support the lofty valuations.
Fast forward to today, the digital landscape is fundamentally different. Bandwidth costs have plummeted, networks have evolved, and mobility has transformed how we live and do business. Concepts that once seemed speculative – such as e-commerce, social media, and cloud computing – are now fully embedded in our daily lives. Business models have matured, profitability is prioritised, and valuations, while high, are generally more justified.
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Yet, history offers cautionary lessons. Emerging technologies like AI echo the past – enormous investment, speculative valuations, and uncertainty about long-term viability. As with the dotcom era, some companies will thrive, while others will struggle under the weight of unrealistic expectations.
AI has the potential to reshape industries, but whether it becomes a true revenue driver or just another tool remains to be seen. The risks are significant, and much is yet to unfold.
Chris Elliott, manager of the Evenlode Global Equity fund
There are many similarities between today’s market and the dotcom bubble. In both cases, market enthusiasm has driven up technology valuations with uncertainty over which company, if any, will emerge victorious. At the turn of the Millennium, the presumed winners included companies like AOL, the internet service provider that allowed users to access the web. However, it was not the technology providers that generated the greatest returns.
The cost of technology rapidly declined as the technology became commoditised. From 2002 to 2022, internet traffic increased 1000x and the price of transit fell 1000x – dooming AOL along the way. Instead, the eventual winners included Amazon, Google, and booking.com – the companies that had the best business models to exploit the technology.
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Similarly, if AI does deliver, then we would expect the greatest winners to be those companies that can employ it effectively to provide value-added services to clients. As Satya Nadella, Microsoft’s CEO, said on a recent podcast: “the big winners here are not going to be tech companies. The winners are going to be the broader industry that uses this commodity.”
Companies with unique data assets and deep customer understanding, such as RELX and Wolters Kluwer, are especially well-positioned to benefit.
Paul Middleton, head of global equities at Mirabaud Asset Management
It really struck me, when analysing Checkpoint Technologies, a US listed cyber security company, in 2016, that the share price had not yet caught up to its previous highs made in 2000, despite having grown earnings at 10% per year over the 16-year period. The P/E multiple of this stock got to 180x in 2000, before falling back into a much more palatable range of 15-20x ever since. As a company, it had performed exceptionally well – growing earnings at that rate for that long is incredibly tough. As a stock, the story was somewhat different.
This stock has moved to new all-time highs more recently, but there remain some high-profile examples of stocks, such as Cisco, that have not yet done so but which remain high quality franchises. There are undoubtedly some companies with extremely high valuations in the market now, but a lot of really highly valued.
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Tech companies, especially those which were unprofitable, have already had one massive sell-off in 2022 and many have not yet recovered. More importantly, bubbles tend to be more visible at the index level. The Nasdaq index is trading on 28x P/E, less than half the level it reached in 2001, so the multiple risk is significantly lower by definition. The Nasdaq has also, however, traded at considerably lower multiples.
We are not value investors, but we are valuation disciplined, and we avoid those areas of the market where valuations are most frothy – we avoid buying companies on 180x PE.
Tom Wildgoose, head of equities at Sarasin & Partners
The start of the dotcom era saw excess allocation of capital, by the stock market, to companies using new technology to sell to an unready public. Investors underestimated the challenges and overestimated the achievable returns on capital.
At the start of the AI era, any bubble is much less clear to see because AI has been less reliant on public capital. However, the return on capital that will accrue to AI product makers is not yet clear. Hence, the AI bubble may be the enormous capital spending underway by the large tech companies.
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This allocation of capital might ultimately turn out to be excessive, in the way the stock market excessively allocated capital to companies like Pets.com. But the large tech companies are trading on around 30x earnings – lower for Alphabet – which does not imply bubble type AI expectations. The beneficiaries of that spending might be more at risk.
Eaton, which manufactures power supply components, now has a similar PE multiple to the large tech companies. But if AI spending slows, Eaton earnings will fall significantly and so its PE will rise to bubble type levels, unless the stock price falls. Perhaps this is the hidden bubble.
Maximiliano Rohm, portfolio manager for the global equity megatrends team at Neuberger Berman
The obvious lesson learned from the dotcom bubble era was that ‘price matters’. It is understandable that in periods of innovation and disruption, investors turn their attention to seemingly ever-growing opportunities and focus less on the ‘price-to-play’. So, when the dotcom bubble burst, the blame was on excessive valuations paid by exuberant investors – and rightly so.
However, the less obvious lesson – and perhaps the more relevant one given the current AI boom – is that, during such exciting environments, visibility and predictability become clouded. New business models replace old ones – but do so at a pace that can be hard to predict.
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Interestingly, even many of the more implausible predictions of the late 90’s internet revolution actually went on to occur over the next couple of decades.
A thematic mindset helped to promote the necessary conviction to remain focused on the long term, and to invest opportunistically during a period of unprecedented volatility and uncertainty.