As stock markets plunged, there was a mad rush to explain the correction by way of the “fundamentals”, and in particular the possibility that the US economy is not as strong as previously assumed and may even be slipping into recession.

It’s all the fault of the Federal Reserve, many pundits said. In attempting to quell inflationary pressures, policymakers had held interest rates too high for too long and were now about to reap the whirlwind by tipping the US and world economies into recession. The hoped-for “soft landing” was transmogrified into the hardest of crashes.

In the event, the whole thing was over almost before it had begun. There’s plenty of evidence of a slowing economy, but not much of an outright recession.

No immediate need, then, for the Fed to come riding to the rescue, even if it is now under the strictest of instructions to urgently start cutting rates at the next available opportunity. Woe betide Jay Powell, the Fed chairman, if he fails to do so.

Like the riots, the sell-off in markets already looks like just another outbreak of algorithmically driven madness.

The comparison in this regard is with “Black Monday” back in 1987, when the correction in stock markets was neither caused by developments in the real economy, nor had much impact on them.

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Tremors such as these are, on the other hand, rarely without any significance at all, and in this case point to some fairly obvious fault lines that threaten much greater destruction down the line.

Perhaps the biggest of them is the hype surrounding artificial intelligence (AI), which has helped drive extraordinary gains in big tech and distorted the entire equity market in the process.

At its peak in mid-July about a half of the weighting in the S&P 500, which is meant to be broadly representative of the US economy as a whole, was accounted for by the technology sector, an unprecedented state of affairs which had become self-perpetuating.

Even today, after the correction of the past few weeks, Apple still commands a stock market value that at £2.5 trillion ($4.9 trillion) is bigger than the annual GDP of the entire UK economy.

Not far behind are Microsoft, Nvidia, Alphabet, Amazon and Meta. Even Tesla, which despite the anticipation around the much-delayed launch of the company’s Robotaxi autonomous vehicle, is in essence just a car company, is worth £500 billion.

You have to go a long way down the list of top market capitalisations before you encounter companies that better represent the great hinterland of the US economy, such as JP Morgan Chase, Walmart and ExxonMobil.

The effect of the AI bubble is particularly pernicious, in that the greater the weighting, the more it sucks passively invested funds into just a handful of “mega stocks”, making it virtually impossible to bet against them.

The best way of looking at this phenomenon is via what has become known as the “Gartner hype cycle”. When a supposedly transformational technology comes along, investors pile in hoping to hit gold, until eventually a “peak of inflated expectations” is reached.

Inevitably, these expectations will not be met. Implementation struggles to deliver, excitement wanes, and many of the early adopters fail. Much of the gain is then wiped out as sentiment slumps into a “trough of disillusionment”.

Phase three is “the slope of enlightenment”, when the benefits of the technology become better appreciated and win widespread application. Finally comes the “plateau of productivity”, where the tech is widely adopted and has a significant impact on economic growth.

This was broadly the pattern followed by the dotcom boom and bust. Eventually, we saw significant productivity gain from the internet revolution, but there was a major shakeout before the positive impact was properly felt.

With generative AI, we seem already to be entering the “trough of disappointment” phase, though it is possible there will be one last surge of greed-inspired buying before fear of loss fully takes hold.

The second major fault line is partially connected, in that the easy money of recent years has been very much part of the frenzied pursuit of the “magnificent seven” technology plays.

The sell-off in markets already looks like just another outbreak of algorithmically driven mid-summer madness.

Years of quantitative easing have fed an asset price bubble of monumental proportions. When money is cheap and plentiful, it promotes risk-taking and misallocation of capital; that’s precisely what we have seen.

Central banks have sought to dampen these effects through macro-prudential regulation, but their reach doesn’t stretch to the “shadow banking” sector, which has grown like Topsy in recent times, feeding such nonsense as the “Japanese carry trade”, where money is borrowed cheap in Japan for investment in tech and other higher-risk assets.

Taken together, leveraged lending and private credit have roughly doubled in size over the past decade. The regulatory crackdown on the banks has simply pushed credit expansion out to the less well-regulated fringes.

Since the banking system went belly up in the financial crisis of 2008-10, non-bank forms of finance have ballooned, and today account for around half of all UK and global financial sector assets.

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There was no particular reason that markets should have sold off last week. Beyond a slightly disappointing US jobs report, the economy shows few signs of slumping into recession.

But just as Britain’s riots may be indicative of a sick and divided society, last week’s financial tremors are symptomatic of deep systemic anomalies that will one day crystallise into a wider bust.

Timing is another matter. Not quite yet, is my guess.

The Telegraph, London

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