Overvaluation probability

How it’s calculated

1. Collect the latest reading for each of the seven indicators from public data (FRED and Robert Shiller’s dataset via multpl.com).
2. Fit each indicator against its own long-run trend — a flat historical mean or an exponential regression — and express the current reading as a z-score: the number of standard deviations above or below that trend.
3. Flip the sign for stress gauges where a low value is the dangerous one (the VIX and the 10y–2y yield curve), so that a higher adjusted z-score always means "more overvalued".
4. Convert each adjusted z-score into a probability with the standard normal cumulative distribution function — the percentile the reading sits at within its own history.
5. Average the seven probabilities with equal weight and round to a whole percent. The historical line reconstructs this same calculation for every date on which at least five indicators have data.

Reading the levels

Low (below 40%)

Indicators sit near or below their historical norms — valuations are not stretched.

Elevated (40–59%)

Some indicators are moving into expensive territory; conditions are richer than average.

High (60–74%)

A majority of indicators are meaningfully above their trends — valuations are historically rich.

Very High (75% and above)

Indicators are clustered near historic extremes, comparable to prior market peaks.

Limitations

• The indicators cover different spans — the Shiller CAPE reaches back to the 19th century while the VIX and credit spreads begin in the 1990s. The historical line only starts once at least five of the seven indicators have data, so earlier decades are deliberately excluded rather than shown as a thin, misleading composite.
• Each indicator’s trend and standard deviation are fit over its full history, so the historical line is a descriptive, hindsight view rather than a point-in-time signal that was actually observable on each past date.
• Equal weighting is a deliberately simple choice. It treats a stress gauge like the VIX as just as important as a valuation gauge like the Buffett Indicator, which reasonable people can disagree with.
• This is a summary of long-run valuation conditions, not a market-timing tool. Nothing here is financial advice.

Frequently asked questions

What is the overvaluation probability?

It is a single number from 0% to 100% that blends seven independent US stock-market indicators — the Shiller CAPE ratio, the Buffett Indicator, Tobin’s Q, the S&P 500 to M2 ratio, the VIX, the high-yield credit spread, and the 10y–2y yield curve — into one gauge of how stretched valuations are relative to their own history. 50% means indicators sit near their historical norms; 100% would mean every gauge is at a historic extreme.

How is the overvaluation probability calculated?

For each indicator we take its current reading, express it as a z-score (standard deviations from its own long-run trend), flip the sign where a low value is the dangerous one (the VIX and the yield curve), and pass that through the normal distribution to get a percentile in [0, 1]. That percentile is the probability that this single measure is signalling overvaluation. The headline figure is the equal-weighted average of the seven percentiles, expressed as a percent.

Does a high probability mean a crash is coming?

No. A high reading means valuations are historically stretched across many independent measures, which has preceded past drawdowns — but markets can stay expensive for years, and the gauge says nothing about timing. It is a descriptive summary of valuation conditions, not financial advice or a market-timing signal.

How often is it updated?

Every US market weekday, about an hour before the opening bell, alongside the underlying indicators. The composite is recomputed from the latest available reading of each of the seven inputs.