What is a stock market bubble? How the AI bubble fits the definition

What is a stock market bubble in plain words?

A stock market bubble is a period when share prices rise far above the value that a company’s earnings and cash flows can support. Prices keep rising because buyers expect to sell later at a higher price, and that expectation feeds on itself. The definition rests on 2 observable parts: a gap between price and value, and a story that explains why the gap is acceptable.

Value is the harder part. Analysts estimate it from expected profits, and estimates differ. A bubble is therefore judged by the size of the gap and by how many assumptions must hold at once for the price to make sense. The more assumptions pile up, the more fragile the price becomes, and the more the label of bubble applies.

Which stages does a stock market bubble follow?

A common model describes 5 stages. A new idea or technology opens the cycle. Prices then rise as early buyers profit, attention grows, and euphoria arrives when ordinary savers join in. Insiders begin to sell at the top, and a panic follows once prices fall below the level where buyers expected to exit. Each stage leaves traces you can observe in volumes, headlines, and funding.

The model helps you place a market on the path. In the euphoria stage, new listings multiply, valuations rest on stories instead of profits, and borrowing rises. In the early stage, prices follow real results. For AI, the useful exercise is to list which traces you see today and note the date, so you can compare the list next quarter.

Which four tests show a stock market bubble?

The first test compares price with earnings: a price to earnings ratio far above its own history suggests a gap. The second traces the funding source: customers repaying the spending, or new investors repaying it. The third checks the buyer mix: professionals buying for cash flow, or newcomers buying for momentum. The fourth rates the story: is it specific and measurable, or does it stretch to cover every price?

No single test settles the question, and the tests complement each other. A high ratio with strong profit growth reads differently from a high ratio with falling profit. Write the four answers down with a date. After 3 quarters you hold a record that shows the direction, and direction carries more information than a single reading.

How does a stock market bubble differ from a correction or a rally?

A rally is a rise backed by improving results. A correction is a fall of moderate size that resets prices without breaking the market. A crash is a sudden, deep fall. A bubble is the setting that can end in a crash: prices detached from value for a long period. The same chart can show a rally or a bubble, which is why the tests look beneath the price.

The distinction also changes the response. After a correction, an investor with a plan keeps the plan. In a bubble, the plan checks exposure, funding, and time horizon before the fall. Naming the situation correctly leads to the right action, and the 4 tests give you the language to name it with evidence.

Does the AI bubble fit the stock market bubble definition?

On the first test, the EQOS Asia AI study records valuations up ×4 in 18 months and about $200B a year invested, while 95% of AI projects fail in production (EQOS Asia AI study, April 2026). That is a visible price gap. On the second test, funding comes from both customers and investors, so the mix is the open question.

On the third and fourth tests the picture is mixed. Professional buyers hold much of the AI trade, and the story is specific, since AI products have real users. The same study projects productivity gains of +40%, which supports the story. As of October 2026 the AI case fits part of the definition and leaves the rest to future data.

How does the stock market bubble definition connect to AI index weight?

A definition becomes useful when it points to a measurement. For AI, the measurement is index weight: how much of a stock market sits in a few AI names. The mother guide, Is the stock market in a bubble because of AI stocks, builds on this definition and adds the concentration numbers that decide how far a fall would spread.

Read the two pages together. This page tells you what to look for, and the mother page tells you where to look. If the 4 tests show a gap and the index weight shows concentration, the bubble reading strengthens. If the tests show a gap and the weight is low, the risk stays local to AI shares.

How can EQOS Asia help you test a stock market bubble claim?

The EQOS Asia method page explains how the φ(S) score is built from 9 dimensions and recomputed from public data. The enterprise AI market scores 0.337 in the study, in the fragile zone where a shock can tip the system (EQOS Asia AI study, April 2026). A score gives the second test, funding and structure, a number you can track.

If a decision depends on the answer, a 30-minute pre-diagnostic applies the same scoring to your case. You bring the decision, such as a fund choice or an AI budget, and the session returns a score and a ranked set of options. That gives you a result you can explain to a partner or a committee.

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About the author

Stéphane Jambu

President, EQOS Forecast Asia

Stéphane Jambu leads EQOS Forecast Asia and works as a consultant in e-commerce, search visibility, and AI. LinkedIn profile