NEAR / FET ratio and spread
1 NEAR = 21.87 FET. Below is the price ratio chart and the regression spread z-score. Hedge ratio β is 0.390 and the correlation between the legs is 0.70.
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Key numbers
over 357 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 0.70, with a hedge ratio of 0.39. Signals from this pair carry more noise than on a tightly linked one.
The spread currently sits at 4.07 standard deviations above its rolling mean — NEAR is expensive relative to FET by the standards of this window.
The spread has not shown mean reversion over the sample: estimates longer than the available history are discarded rather than reported. Trading this pair on reversion has no statistical footing here.
The current ratio sits in the upper part of its range — 100% of the way from the low to the high of the last 357 daily candles.
Frequently asked
How many FET is 1 NEAR?
1 NEAR is worth 21.8713 FET at the latest exchange quotes. The figure is the ratio of the two USDT prices and updates every minute.
What is the NEAR/FET range?
Over the last 357 daily candles the ratio traded between 4.64717 (28.03.2026) and 21.8713 (20.09.2026).
Are NEAR and FET correlated?
The correlation of daily log returns between NEAR and FET is 0.70, 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 NEAR/FET spread z-score now?
The z-score is 4.07 — 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 NEAR/FET suitable for a pair trade?
Not on a reversion thesis. The spread has not returned to its mean within the available history, so there is nothing to trade back to.
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.