An 11-component statistical measure of whether an asset is historically stretched (overbought) or compressed (oversold) relative to its own history. Z-Scores above +2.0 or below -2.0 indicate extreme territory.
The Z-Score calculates how many standard deviations the current value of each component is from its historical mean. By compositing 11 independent metrics — spanning price, volume, momentum, and volatility — the model reduces the noise of any single measure and provides a statistically grounded valuation read.
A Z-Score of +2.0 means the composite is 2 standard deviations above its historical average — territory that has historically preceded mean reversion. A Z-Score of -2.0 suggests the asset is statistically compressed.
Current composite valuation readings across tracked assets. Red = historically stretched (Z > 1.5). Green = historically compressed (Z < -1.5).
| Asset | 1D Z-Score | 1W Z-Score |
|---|---|---|
| BTC | +0.93 | -0.61 |
| ETH | +0.73 | -0.50 |
| SOL | +0.07 | -0.81 |
| SUI | — | — |
| XRP | +0.10 | -0.90 |
| AVAX | +0.31 | -0.37 |
| LINK | +0.15 | -0.59 |
| DOGE | +0.26 | -0.60 |
Z-Scores are a framework for understanding where an asset sits relative to its own history. They describe a statistical condition, not a prediction. An asset can remain overbought (Z > 2.0) for extended periods during strong trends — the Z-Score indicates stretch, not reversal timing.
The model is most useful in conjunction with trend data (TPI) and regime classification (MRDM). An overbought Z-Score in a trending regime has different implications than the same reading in a mean-reverting regime.
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