In the dynamic landscape of the investment industry, skepticism often surfaces, and the latest concern revolves around the use of ‘valuation’ as a persuasive tool for retail investors to consider costly assets. The issue at hand involves the introduction of unconventional metrics, and the recent notion of a ‘price to innovation’ ratio for technology stocks has stirred apprehensions.
This metric, declared as attractive by a Morgan Stanley analyst, measures the ratio of a company’s price to its earnings plus research and development expenses. The intention is to present companies with limited earnings but substantial investment budgets as appealing investment opportunities.
The history of introducing novel valuation measures has been met with caution, especially when attempting to provide a semblance of respectability to potentially inflated valuations. The early 2000s witnessed the advent of metrics like ‘price to clicks’ for internet stocks, a phenomenon that did not end well.
The emergence of the ‘price to innovation’ ratio in the market narrative has prompted concerns about a potential stock market bubble, particularly within the realm of artificial intelligence (AI)-driven stocks. While defining a bubble is challenging, the ingredients typically involve innovation coupled with abundant cheap money, resulting in significant outperformance and historically extreme valuations.
The nucleus of a potential bubble seems to be forming around a group of mega-sized technology stocks, often referred to as the Magnificent Seven, with notable mention of chip design firm Nvidia. Using a simple valuation metric like the ratio of price to revenue, it becomes apparent that some of these tech giants, including Microsoft and Nvidia, exhibit high multiples compared to the broader market.
A parallel situation exists in private markets, where venture investors are paying elevated multiples for AI-focused start-ups, driven by the optimistic belief in the potential sales growth of these tech firms.
While many of these tech companies reported healthy earnings in the past week, concerns linger about the substantial optimism regarding the future impact of AI. If AI is poised to be the catalyst for the next bubble, vigilance is warranted, especially considering the historical consequences of asset bubbles.
The current monetary conditions, marked by easy money since the global financial crisis, have led to asset inflation rather than consumer inflation. Despite recent changes in inflation and interest rates, the credit markets have remained relatively stable, prompting questions about the potential existence of another bubble.
The role of central banks in potentially aiding the creation of asset bubbles has shifted over time. In the days before quantitative easing, there was a debate on whether central banks contributed to the formation of bubbles. Today, central bankers often emphasize the ‘wealth effect’ from asset prices rather than express concerns about the risk of bubbles.
The potential dangers associated with asset bubbles, including wealth destruction, wealth transfer from poorer to richer investors, distorted investment across economies, and the aftermath’s economic costs, underscore the need for vigilance.
As of now, the AI bubble seems confined to a small number of companies, comprising a substantial portion of the stock market. To evolve into a full-fledged mania, companies in sectors positively impacted by AI will need to embrace the AI narrative, and the mania must extend to regions beyond the current scope.
Investors are advised to monitor additional indicators for signs of an AI bubble, such as increased public discourse on intricate topics like error correction in quantum computing, which may indicate an excessive market exuberance.