PHA / QNT ratio and spread
1 PHA = 0.0005221 QNT. Below is the price ratio chart and the regression spread z-score. Hedge ratio β is 2.224 and the correlation between the legs is 0.34.
If you hold PHA · If you hold QNT
Sign in to keep favourite pairs.
Alerts
Sign in to set your own alerts.
Key numbers
over 364 daily candles
How each of these is computed: regression spread, hedge ratio, spread z-score, half-life, correlation.
What the numbers say
The legs barely move together: correlation of daily log returns is only 0.34. A spread built on such a weak link reverts by coincidence rather than by mechanism.
The spread currently sits at -5.39 standard deviations from its rolling mean — PHA is cheap relative to QNT by the standards of this window.
Historically the spread covers half the way back to its mean in about 5 days, so a divergence here tends to resolve within weeks rather than months.
The current ratio sits mid-range — 29% of the way from the low to the high of the last 364 daily candles.
Frequently asked
How many QNT is 1 PHA?
1 PHA is worth 0.000522086 QNT at the latest exchange quotes. The figure is the ratio of the two USDT prices and updates every minute.
What is the PHA/QNT range?
Over the last 364 daily candles the ratio traded between 0.000322222 (01.08.2026) and 0.0010064 (10.10.2025).
Are PHA and QNT correlated?
The correlation of daily log returns between PHA and QNT is 0.34, which counts as a weak link. Log returns are used rather than prices: two rising assets correlate almost by default, joint day-to-day movement is what matters.
What is the PHA/QNT spread z-score now?
The z-score is -5.39 — the spread is stretched beyond two standard deviations. It measures how far the regression residual log(A) − β·log(B) sits from its rolling mean, in standard deviations.
Is PHA/QNT suitable for a pair trade?
Weakly. Correlation is only 0.34, so the legs do not reliably move together and the spread carries mostly idiosyncratic noise.
Related pairs
Other pairs sharing a leg with this one.
All figures are computed from exchange data and describe past behaviour. Nothing here is investment advice.