Blog

Unlock the Editor’s Digest for free

Roula Khalaf, Editor of the FT, selects her favourite stories in this weekly newsletter.

Questions over the colossal investment by US tech companies in artificial intelligence, now running at $400bn a year, continue to come thick and fast.

Will it, sceptics ask, ever be recouped, let alone generate the magical returns AI zealots expect? Leaders of the financial world from Kristalina Georgieva, IMF managing director, to Jamie Dimon of JPMorgan Chase have warned of an abrupt market correction. Could this be one of history’s more extreme cases of irrational exuberance?

That phrase, you may recall, was coined by Fed chair Alan Greenspan at the start of the dotcom bubble. He later backtracked, declaring that bubbles could only be detected after the event. The revisionist Greenspan view overlooked that in any bubble there are always shrewd people who see what is coming. For example, on the eve of the 1929 Wall Street crash statistician Roger Babson warned that a “terrific” crash was imminent. More recently Jeremy Grantham, co-founder of US fund manager GMO, famously predicted the bursting of the great Japanese bubble, the dotcom bust and the 2007-08 financial crisis. In the UK fund manager and philanthropist Jonathan Ruffer earned strong returns for his clients around the dotcom blow-up, the great financial crisis and the Covid market plunge. Yet such contrarian voices are always drowned out by those who claim that “this time is different”.

Whether today’s stock market valuations are irrational is a matter of judgment. But whether investors are behaving irrationally is a different issue. Clearly in all market manias going back to the South Sea Bubble, punters have been intoxicated by stories of untold riches and driven by the fear of missing out (Fomo). Fomo falls short of exuberance but is not exactly irrational. More importantly, in the 21st century when professional investors dominate markets, a paradoxical and perverse rationality is at work among them.

This arises because large amounts of money are delegated by asset owners such as pension funds to asset managers. The job of active managers has traditionally been to maximise returns by assessing fundamental values arising from long-term corporate cash flows. Yet there is a principal-agent problem here. To monitor the managers, asset owners usually benchmark them against an index.

So where managers have a below-index weight in stocks that are rising strongly this puts pressure on them to adopt momentum, or trend following, strategies to improve short-term performance. They thus become late-stage buyers of rising stocks and sellers of falling stocks at the cost of longer-term underperformance. This helps reduce the risk of their being fired, or at least of being fired sooner rather than later.

Research by Paul Woolley and Dimitri Vayanos of the London School of Economics suggests that such momentum trading helps explain the poor performance of active managers and is conducive to a persistent bias to overvaluation. Passive investing, now all-pervasive, is momentum writ large. As well as amplifying mispricing it reduces the liquidity of individual stocks and increases their volatility. Misallocation of capital results, especially where companies use overpriced equity to make acquisitions that encourage industrial and portfolio concentration.

AI brings a further twist to these market dynamics. The Bank of England worries that the use of advanced AI-based trading strategies could lead to firms taking increasingly correlated positions, thereby amplifying shocks. Yet the technology could also hold a key to addressing the resulting instabilities.

Woolley and Vayanos have teamed up with AI experts at Oxford university under Sir Nigel Shadbolt to develop new forms of portfolio analysis designed to disaggregate momentum from fundamental values. This has involved running synthetic portfolios using real price data for periods of up to 30 years.

Initial results reveal managers’ skill (or lack of skill) in establishing fundamental value as opposed to their luck in using momentum. In effect, the methodology unpicks the principal-agent conflict. And because this AI diagnostic process provides aggregate data showing how far the market is dominated by momentum, it should help identify bubbles.

The potential here for a big leap in the quality of performance attribution could clearly be valuable for asset owners. But it can never eliminate bubbles. The innate tendency of investors towards exuberance and the corporate compulsion towards leverage will together periodically defy the wisdom of the ages. The snag for shrewd naysayers in any bubble is that the timing of the burst is next to unforecastable.

john.plender@ft.com

China has heavily invested in education, science, technology, and innovation since it launched reforms and opened up in 1978. In early days, China sent its youth to world-class universities all over the world and developed quality human resources. In the next stage, China focused on upgrading their own universities and invested within Chinese universities. Curricula were modernized, and teaching methods were improved. Exam systems were changed, and they started to catch up with the global universities and struggled to achieve global ranking. As a result, today, around a dozen universities have achieved status in the top hundred universities of the world, and nearly a hundred universities fall among the top 500 universities of the top global universities.

In the third stage, China focused on research and development. Invested generously in establishing state-of-the-art laboratories. Equipped laboratories with modern, advanced, and the latest equipment, instruments, and materials. Research infrastructure was improved immensely.

For research, three things are essential: research human resources, research infrastructure, and above all, research culture. China developed research human resources by sending millions of youths to top universities all over the world. Invested heavily in research infrastructure and created a research culture through various monetary incentives.

Now it is time for China to reap the fruits of education, research, development, and innovation. China is comprehensively utilizing sci-tech as an engine of economic growth.

One of the case studies is described below:

China’s expertise in minerals and mining, particularly for rare earth metals, is built on decades of strategic, long-term planning that includes control over the entire supply chain from mining and refining to manufacturing. Its dominance stems from a combination of vast resources, the ability to manage the complex and hazardous separation and purification processes, and heavy investment in R&D, which has led to a leading position in patents and the production of critical materials like permanent magnets. China also benefits from lower development costs due to state support for national champions, vast human resources, and an abundance of natural resource reserves, giving it a significant global advantage. 

Key areas of Chinese expertise

Mining and extraction:

China accounts for around 70% of global rare earth mining, a process that is often difficult due to the elements’ co-occurrence with other materials like uranium.

Processing and refining:

China holds a dominant position (around 90-94%) in the highly complex and specialized processes of separating and purifying rare earth elements.

Manufacturing:

The country is a leader in manufacturing finished products, producing over 90% of the world’s rare earth permanent magnets, which are vital for high-tech and industrial applications.

Research and development:

China has filed a significantly larger number of patents related to rare earths than other countries, indicating a strong focus on technological advancement in the field.

Chinese dominance on rare earth metals and critical minerals;

China controls up to 90 percent of global rare earth metals and critical minerals either physically or through Chinese technology, machinery, or processes. The October 2025 decisions—outlined in MOFCOM’s announcements (Nos. 57, 58, 61, and 62)—mark an important refinement of China’s export governance framework. These include:

Export Control on Rare Earth Items and Technologies: Covering mining, smelting, refining, and magnet-making processes for medium and heavy rare earth elements, including holmium, dysprosium, terbium, yttrium, and gadolinium.

Control on Dual-Use Technologies: Exports involving rare earth production line services and technology transfers will require dual-use export licenses.

Control on Superhard Materials and Synthetic Graphite: Including artificial diamond materials, lithium battery-related items, and synthetic graphite anodes—critical for the global electric vehicle (EV) industry.

Unreliable Entity List Update: Addition of 14 foreign entities (including firms such as Dedrone by Axon, BAE Systems Inc., Tech Insights, and Elbit Systems of America) for engaging in activities that undermine China’s national security and economic interests.

These steps are consistent with China’s Export Control Law of 2020 and international practices established under the Wassenaar Arrangement and UN frameworks. They neither target specific countries nor disrupt global trade arbitrarily. Instead, they ensure that technologies of strategic value are exported responsibly and with full regard to China’s national interests.

It is time for China to reap the economic benefits of its decades of huge investment in education, science, technology, and innovation.