QNT / XPL ratio and spread
1 QNT = 1089.93 XPL. Below is the price ratio chart and the regression spread z-score. Hedge ratio β is 0.185 and the correlation between the legs is 0.47.
If you hold QNT · If you hold XPL
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Key numbers
over 363 daily candles
How each of these is computed: regression spread, hedge ratio, spread z-score, half-life, correlation.
What the numbers say
The legs move together only moderately — correlation of daily log returns is 0.47, with a hedge ratio of 0.18. Signals from this pair carry more noise than on a tightly linked one.
The spread currently sits at 4.43 standard deviations above its rolling mean — QNT is expensive relative to XPL by the standards of this window.
Historically the spread covers half the way back to its mean in about 9 days, so a divergence here tends to resolve within weeks rather than months.
The current ratio sits in the upper part of its range — 100% of the way from the low to the high of the last 363 daily candles.
Frequently asked
How many XPL is 1 QNT?
1 QNT is worth 1089.93 XPL at the latest exchange quotes. The figure is the ratio of the two USDT prices and updates every minute.
What is the QNT/XPL range?
Over the last 363 daily candles the ratio traded between 68.2891 (29.09.2025) and 1089.93 (26.09.2026).
Are QNT and XPL correlated?
The correlation of daily log returns between QNT and XPL is 0.47, which counts as a moderate 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 QNT/XPL spread z-score now?
The z-score is 4.43 — 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 QNT/XPL suitable for a pair trade?
The mechanics hold up: correlation is 0.47 and the spread historically covers half the way back to its mean in about 9 days. That is a description of past behaviour, not a forecast or a recommendation.
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.