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Indicators/Z-Score Probability Waves
Market · Statistical Updated daily · 00:00 UTC

Z-Score Probability Waves.

Rolling 52-week log z-score. The asset's distance from its own mean, in standard deviations.
Mode
Smart DCA
Asset
τ TAO
Backtest
1 year
Algorithm
52 weeks
Buy zone ≤ Buy zone When the indicator drops to or below this threshold, the strategy doubles its weekly buy (Smart-DCA) or opens a long (Trade). It's the "cheap" regime — time to accumulate.
σ
Trim zone ≥Sell zone ≥ Trim zoneSell zone When the indicator climbs to or above this, the strategy skips the weekly buy and trims 5% of the stack. Stretched regime. When the indicator climbs to or above this, the strategy exits to cash. Distribution regime.
σ
Compare with
Signal
Set alert
Smart-DCA edge Trade P&L
— more coins vs Flat DCA cumulative return
Capital saved Alpha vs hold
less capital required per coin outperformance vs Buy & Hold
Activations Time in market
— signals in — weeks —% in cash
TAO Price Z-Score
τao/minal
COMPUTING
τao/minal · offchain · daily aggregates
Allocation rule Now · in — zone
0
Buy
When z-score is ≤ −2.0σ → deploy 2× weekly budget (statistical extreme — price is two standard deviations below its rolling mean).
Hold
When −2.0σ < z-score < +2.0σ → deploy 1× weekly budget (baseline DCA, within normal range).
Trim Sell
When z-score is ≥ +2.0σskip buy and trim 5% (statistical extreme — price is stretched two σ above mean).
Price Latest close
Current Z log-price deviation
Alpha vs Hold Strategy − hold
> +2.0σ
Overextension to the upside.

Price is trading more than 2 standard deviations above its 52-week geometric mean — historically rare and often coincides with cycle peaks. Forward returns from this band are skewed negative across 3-12 month horizons.

< −2.0σ
Deep undervaluation.

Price has collapsed more than 2 standard deviations below its 52-week mean — a statistically extreme accumulation zone. Historical congruent states produce >75% positive forward returns over 12-24 month horizons.

How to read it
The number of standard deviations the current price sits from its own rolling mean, in log space. A pure statistical mean-reversion gauge.

For each weekly close, we take the trailing 52 weekly log prices, compute their mean μ and standard deviation σ, then express today's log price as a z-score: z = (log P − μ) ÷ σ. A z of zero means price equals its trailing mean. A z of +2 means price is two standard deviations above — statistically rare.

The chart shows two regimes selectable from the toggle. Long mode uses a 52-week window with an EMA smoothing pass over the z-series, surfacing macro cycle phase. Short mode uses an 8-week window with no smoothing, surfacing short-term mean-reversion swings for traders.

Once μ and σ are known, every z-band projects back to a concrete USD level via price(z) = exp(μ + z·σ). The snapshot row shows the ±0.5σ, ±1.5σ, and ±2.5σ price levels — they update each day as the rolling window advances.

Log space is essential for assets that span orders of magnitude. A 50% drop and a 50% rise have equal weight, which makes the z-score interpretable across full cycles rather than only the most recent regime.