Investors Turn to Dotcom-Era Tactics to Navigate AI Market Volatility

Dotcom Playbook Resurfaces for AI Investments

Major investors are reportedly reviving strategies from the 1990s dotcom era to navigate the current artificial intelligence market surge, according to recent financial analysis. Sources indicate that professional money managers are shifting from hyped-up AI stocks into potential next-in-line winners, mirroring approaches that helped some investors sidestep the worst of the dotcom crash.

Dotcom Playbook Resurfaces for AI Investments
Recognizing Market Parallels
Timing the Market Phases
Diversification Within AI Ecosystem
Alternative Approaches and Concerns

Recognizing Market Parallels

As U.S. stocks hit successive records and AI chipmaker Nvidia’s valuation reportedly surged beyond $4 trillion, investors are increasingly looking to historical precedents. Francesco Sandrini, multi-asset head and Italy CIO at Europe’s largest asset manager Amundi, stated that their current approach mirrors what worked from 1998 to 2000. Analysts suggest this involves identifying “the highest growth opportunities that so far the market had failed to spot,” with moves into software groups, robotics and Asian tech.

According to the report, investors are showing signs of concern about irrational exuberance on Wall Street, particularly regarding frenzied trading in risky options pegged to big AI stocks. However, most expect the technology enthusiasm to continue and are positioning to bank gains via reasonably valued assets that might rally next.

Timing the Market Phases

Historical analysis reportedly shows that timing the phases of a bubble has been an effective strategy for professional investors. A study by economists Markus Brunnermeir and Stefan Nagel indicated that hedge funds during the dotcom era mostly avoided betting against the bubble, instead riding it skillfully enough to beat the market by approximately 4.5% per quarter from 1998-2000 while avoiding the worst downturn impacts.

Simon Edelsten, CIO at Goshawk Asset Management, who worked on telecom IPOs during the original dotcom boom, suggested the current environment resembles 1999. “The odds of this AI boom being a bust are very high because you’ve got companies spending trillions and all fighting for the same market that does not yet exist,” he reportedly stated. Edelsten compared the strategy to buying “the local hardware store where the prospectors will buy all their shovels” during a gold rush.

Diversification Within AI Ecosystem

Investors are reportedly attempting to maintain AI exposure while reducing direct risk to the sector’s largest players. According to the analysis, this involves taking profits on Magnificent Seven stocks after substantial gains and building positions in companies that support the AI infrastructure.

Fidelity International multi-asset manager Becky Qin reportedly identified uranium as a favored AI trade because power-hungry data centers could significantly increase nuclear energy consumption. Meanwhile, Carmignac investment committee member Kevin Thozet indicated he was taking profits on major tech stocks and building positions in companies like Taiwan’s Gudeng Precision, which manufactures delivery boxes for AI chipmakers including TSMC.

Alternative Approaches and Concerns

Not all investors favor the relative value approach to AI investing, according to the report. Oliver Blackbourn, portfolio manager at Janus Henderson, stated he was hedging U.S. tech positions with European and healthcare assets as protection against potential AI-related market declines affecting the broader U.S. economy.

Asset managers reportedly express concern that the rush to build data centers could result in overcapacity, similar to the fiber-optic cable boom in the telecommunications industry. Arun Sai, Pictet Asset Management senior multi-asset strategist, noted that “in any new technological paradigm we don’t get from A to B without excesses along the way,” while favoring Chinese stocks as a potential hedge.

Sources indicate the prevailing sentiment among professional investors is that calling the peak of the AI market movement remains challenging, with most acknowledging that identifying the bubble’s end typically only becomes clear in hindsight.