Bubbles, AI hype and the second law of dialectics

Financial bubbles are fuelled by compelling narratives, abundant liquidity and the belief that ‘this time is different’. However, history shows that markets eventually reconnect with fundamentals, and when they do, the adjustment is often swift and unforgiving. The recent unwind in AI-related equities is a reminder of this timeless investment lesson.

Recent months have highlighted the dangers of confusing speculation with investing. One high-profile example was the collapse of a heavily leveraged AI-focused fund managed by a 24-year-old with virtually no professional investment experience. The speed of its decline was striking, but perhaps even more surprising was the willingness of sophisticated investors to allocate capital to a strategy with little demonstrable track record.

This episode provides a timely reminder of the importance of investment discipline. Strong conviction in a prevailing theme can generate impressive returns while conditions remain supportive, but navigating periods of market stress requires a different set of skills: understanding downside risk, managing leverage and maintaining discipline when market dynamics change.

It also raises questions around ‘circular investing’, where overlapping relationships between prime brokers, trading firms and venture capital investors can allow capital and confidence to reinforce one another. Echoing concerns around ‘circular financing’ in AI, such dynamics make rigorous, independent due diligence even more important.

This is not the first disruption either, over the past 30 years, global markets have experienced several major disruptions. The second half of the 1990s was largely defined by crises across emerging markets, culminating in the 1998 Russian financial crisis, when Russian bonds traded as low as five cents on the dollar at one point. By contrast, the dot-com bubble and subsequent crash were primarily US-driven events. The same was largely true of the 2008 financial crisis, although its impact quickly spread across global markets.

Against these market disruptions, the rigorous standards traditionally applied by institutional investors are particularly relevant. For decades, institutional investing has required years of proven performance, a clearly articulated investment philosophy, a repeatable process and experienced portfolio managers. Those disciplines exist for a reason. Experience is no guarantee of success, but it provides something that is difficult to acquire quickly: the judgement and perspective that come from investing through different market environments. Over more than 30 years investing in emerging markets, our team has observed how market narratives repeatedly evolve, while the principles of valuation, discipline and risk management endure.

When markets are driven by excitement rather than due diligence, there is a risk that these fundamentals are overlooked and capital allocation itself becomes distorted. Hype may attract capital, but experience, discipline and a robust investment process are what matter when conditions change.

The warning signs were visible

It should not have been particularly difficult for most experienced investors to recognise that the stretch in AI-related stocks was both real and extraordinary. While valuation is not necessarily a catalyst in itself, it is ultimately a limiting factor. Even after this ‘correction’ which, in many cases, involved significant percentage declines, several stocks still appear expensive on the most relevant valuation metrics.

The data makes a compelling case that the selloff was not primarily driven by a deterioration in short-term earnings expectations. Rather, it reflected multiple compression, de-rating, positioning unwinds, and, to some extent, a moderation in the pace of earnings upgrades.

Entire value chains and supply chains, particularly in markets such as Korea and Taiwan where numerous smaller, more speculative ‘picks and shovels’ companies had become market favourites, were repriced lower. Bond yields were rising while the equity risk premium had fallen to historically low levels (see Figure 1 and 2), leaving investors with increasingly little compensation for taking equity risk. In that environment, a repricing of richly valued AI-related companies was a logical outcome.  

Several broader market signals were also flashing caution. Increasing leverage, record retail participation, leveraged ETFs and persistent media enthusiasm all combined to create conditions typically associated with speculative excess. None of these factors alone causes a bubble to burst. Together, however, they create an environment where sentiment can reverse rapidly and losses become self-reinforcing.

In philosophical terms, this dynamic echoes the second law of dialectics: ‘the transformation of quantitative accumulation into qualitative change’. Excesses accumulate incrementally until a tipping point is reached. The same principle can be observed in markets, where excesses build gradually until a tipping point is reached and behaviour changes. What begins as a correction or rotation can quickly become a self-reinforcing cycle of losses, margin calls and forced selling. Recognising when these pressures are approaching an inflection point is where experience can prove particularly valuable.

A lesson learnt

Investors sometimes forget that investing is about time arbitrage. Bubbles almost always last longer than expected, drawing in more believers along the way. But when sentiment finally turns, the reversal tends to be swift and painful. The real challenge is not reacting after the fact but recognising the warning signs early enough to prepare.

The recent correction is another reminder. Markets change, but investor behaviour rarely does. Having invested through more than three decades of emerging market cycles, our team has seen first-hand how periods of exuberance can give way to sharp reversals. These experiences reinforce a timeless lesson, valuation, discipline and risk management remain just as important as the latest market narrative.

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