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Statistical

Mayer Multiple

Price divided by the 200-day moving average. The simplest, most transparent deviation-from-trend gauge in Bitcoin — no fitted parameters, nothing to repaint.

Data: PriceUSD · Coin Metrics community API · computed live in your browser, nothing uploaded

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What this chart shows

Created by Trace Mayer, the multiple is exactly what it says:

Mayer Multiple = Price / 200-day Simple Moving Average

Its virtue is honesty. There is no curve fitting, no parameter chosen to match past tops, and nothing that gets redrawn when the market misbehaves. The 200-day average is a convention older than Bitcoin itself.

How to read it

Below 0.8, price sits at a deep discount to its own yearly trend — historically an accumulation condition. The 2.4 threshold comes from Mayer's original observation that buying above it produced poor forward returns; every cycle top printed well above it. Around 1.0 the market is simply on trend.

Limitations

This is a thermometer, not a forecast. It says how stretched price is versus its own average and nothing about where it goes next; strong trends can hold the multiple above 1.5 for a year. The 0.8 / 2.4 thresholds are empirical observations from a small number of cycles, and the multiple's extremes have compressed as volatility declines — 2021's top printed far lower than 2013's.

Further reading

Mayer Multiple Explained: Bitcoin Price vs Its 200-Day Average

FAQ

What is a good Mayer Multiple to buy Bitcoin?
Historically, accumulating below 0.8 — price 20% under its 200-day average — produced strong forward returns. But the threshold is descriptive of four past cycles, not a guarantee about the next one.
Why 2.4?
Trace Mayer's original backtest found that long-term returns of purchases made above 2.4× the 200-day MA were poor. It's an empirical cut-off, and its relevance fades as volatility compresses each cycle.
Why is the Mayer Multiple more trustworthy than fitted models?
Both of its inputs are fixed and public. A model with no free parameters cannot be quietly re-fitted after it fails — which is exactly what happened to the Rainbow Chart and Stock-to-Flow.