More or Less: "Is there a stock market crash coming?"

Air Date: November 22, 2025
Host: Nathan Gower (BBC Radio 4)
Guests: Simon French (Chief Economist, Panmure Liberum), Katie Martin (Markets Columnist, Financial Times)

Episode Overview

This episode addresses the burning question on many investors’ minds: Is the current stock market boom – especially the tech sector surge driven by artificial intelligence (AI) hype – a bubble on the brink of bursting? Host Nathan Gower guides listeners through the data, enlisting the help of economics and markets experts, to cut through speculation and use numbers to assess risk, bubbles, and the likelihood of a crash.

Key Discussion Points & Insights

1. How Big is the Current Stock Market Rally?

Timestamps: [02:48] – [03:54]

• Simon French explains:

  • The recent rebound in global stock markets, led by the US, has added about $28 trillion to global shares' value since the post-Liberation Day low in the US, and now sits at $30 trillion.
  • For context, this is almost equal to the US economy’s annual output and represents a 31% rise in six months.
  • This scale of rebound has only occurred three times in recent history: 1987 (Black Monday), 1999 (dot com bubble), and 2009 (post-GFC).

  “That number… that’s a 31% increase in just six months… and that has only happened on three previous occasions in modern market history.”
  — Simon French [02:48]

2. How Much of the Rise is Due to AI?

Timestamps: [03:54] – [04:29]

• It's hard to separate "AI companies" from broader tech, but:

  • Of the $30 trillion added to global stock values, about $12.5 trillion is in the technology sector.
  • Thus, tech accounts for almost half the total market gains.

  “If you just take the sector classification of technology, it’s about half that… about $12.5 trillion.”
  — Simon French [03:54]

3. Are There Signs of a Bubble? (Valuations & Historical Parallels)

Timestamps: [04:29] – [06:15]

• Analysis through the Shiller Price/Earnings Ratio:

  • Currently hovers around 40 times earnings in the US market, matched only at the peak of the dot com bubble in 1999–2000.
  • Katie Martin draws direct parallels to the dot com bubble:
    • Some companies like Amazon survived and thrived, but many were dramatically overvalued (“hundreds of multiples of earnings”) and crashed spectacularly (e.g., Pets.com).
    • After the bust, it took years for many investors to recover.

  “That measure [Shiller PE] is hovering around 40 times earnings… it’s only been there once before… at the height of the dot com bubble in 99, early 2000.”
  — Simon French [04:29]

  “There was this cluster of stocks that were worth well in excess of the money that they were actually making. And inevitably that ran out of road and they all crashed all at once.”
  — Katie Martin [05:08]

4. Is This Boom Limited to a Few Companies? (Market Breadth Issues)

Timestamps: [06:15] – [07:31]

• The US S&P 500 index is highly weighted to the biggest companies.

  • Nvidia is now worth $4.4 trillion.
  • The so-called "Magnificent Seven" (Apple, Amazon, Microsoft, Nvidia, Alphabet, Meta, Tesla) are disproportionately responsible for index gains.
  • Many other companies are not doing well, but the overall index stays high because of these few giants.
  • This concentration creates “a small number of potential points of failure.”

  “We are talking about a tiny number of companies… there’s a lot of companies that are having a stinker of a year. But the index is being held up… and to me that means you have quite a small number of potential points of failure, which worries me somewhat.”
  — Katie Martin [06:26]

5. Are Non-Profitable Tech Companies Rallying – a Classic Bubble Signal?

Timestamps: [08:06] – [08:38]

• The sharpest post-April increase is among US tech companies with no current profits.

• Echoes of dot-com era, when unprofitable tech saw wild valuations leading up to the crash.

  “The biggest rally since April is amongst non-profitable technology companies, those that don’t make any earnings at the moment. And that has uncomfortable parallels with the dot com era…”
  — Simon French [08:06]

6. Can We Identify Bubbles Before They Burst?

Timestamps: [08:38] – [09:28]

• No expert, however senior, can reliably time a market crash.

• Referencing classic economist wisdom:

  • "The market can remain irrational longer than I can remain solvent."

• The best one can do is to "calibrate risk."

  • Simon French personally sees "more risky signals than I've seen for quite a long time."

  “…none of us really know how to time the market. The best investors of all time acknowledge that… the market can remain irrational longer than I can remain solvent. And that is an important message to remember.”
  — Simon French [08:44]

  “On the balance, there are more risky signals than I’ve seen for quite a long time in the stock market. So I’d be more cautious in that environment.”
  — Simon French [09:20]

Notable Quotes

• "The rebound in global stock markets, led by the US stock market, has added about $28 trillion to the value of global shares."
  — Simon French [02:48]

• "That measure is hovering around 40 times earnings in the US stock market. Now it’s only been there once before… at the height of the dot com bubble…"
  — Simon French [04:29]

• "We are talking about a tiny number of companies… to me that means you have quite a small number of potential points of failure. Which worries me somewhat."
  — Katie Martin [06:26]

• “The biggest rally since April is amongst non profitable technology companies… that has uncomfortable parallels with the dot com era.”
  — Simon French [08:06]

• "The market can remain irrational longer than I can remain solvent." (famous quote cited by Simon French) [08:44]

Important Timestamps

• Stock market rally stats & context: [02:48]
• AI’s role in the rally: [03:54]
• Dot com parallels: [04:29] – [06:15]
• Market concentration/Magnificent Seven: [06:26]
• Non-profitable tech stocks surge: [08:06]
• Bubble prediction/risk signals: [08:44]

Conclusion

The episode provides listeners with a nuanced, data-driven look at the current stock market rise, its similarities to past bubbles, and why even seasoned experts find it hard to forecast a crash. Tech – especially the AI-hyped "Magnificent Seven" – drives much of the surge, creating concentration risk and familiar warning signs. There are risky signals, especially in overvaluations and the rallying of unprofitable companies, but no one can time the end of a bubble.
Caution is advised, but certainty is impossible.