FundingRateZScore

The latest funding rate expressed in standard deviations from its rolling mean. Makes funding extremes comparable across regimes and assets — a contrarian-fade gauge.

Quick reference

Item	Value
Family	Derivatives
Input type	DerivativesTick — a perp / futures market tick
Output type	f64 (standard deviations)
Output range	unbounded around zero
Default parameters	window
Warmup period	window
Interpretation	Funding extreme / mean-reversion

Formula

zScore = (fundingRate − mean) / population_stddev   over the last `window` ticks

Population standard deviation (window denominator), maintained in O(1) via running sum and sum-of-squares. A window with zero dispersion yields 0. See crates/wickra-core/src/indicators/funding_rate_zscore.rs.

Parameters

Name	Meaning	Constraint
window	number of ticks in the z-score window	>= 1

Construct with FundingRateZScore::new(window); window == 0 is rejected.

Inputs / Outputs

Indicator<Input = DerivativesTick, Output = f64>. The bindings expose only the field this indicator reads: update(funding_rate). Python / Node batch accept a single funding_rate array and return a 1-D array (NaN during warmup); WASM is streaming-only.

Warmup

warmup_period() == window; the first z-score lands on the window-th tick.

Edge cases

• Flat window. Zero dispersion (a constant funding series) returns exactly 0 rather than dividing by zero.
• Precision. The variance uses E[x²] − E[x]² with a non-negative clamp; compare z-scores with an 1e-9 tolerance, not 1e-12.

Examples

Rust

use wickra::{DerivativesTick, FundingRateZScore, Indicator};

fn tick(rate: f64) -> DerivativesTick {
    DerivativesTick::new(rate, 100.0, 100.0, 100.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0)
        .unwrap()
}

let mut z = FundingRateZScore::new(2).unwrap();
assert_eq!(z.update(tick(0.001)), None);
assert!((z.update(tick(0.003)).unwrap() - 1.0).abs() < 1e-9);

Python

import wickra as ta

z = ta.FundingRateZScore(2)
print(z.update(0.001))  # None
print(z.update(0.003))  # ~1.0

Node

const { FundingRateZScore } = require('wickra');

const z = new FundingRateZScore(2);
console.log(z.update(0.001)); // null
console.log(z.update(0.003)); // ~1.0

Interpretation

A reading of +2 means funding is two standard deviations richer than its recent norm — an unusually crowded long, often faded; −2 is the mirror. Because it is unit-free it compares funding stress across assets and time in a way the raw rate cannot.

Common pitfalls

• Population, not sample, stddev. The denominator is window, not window − 1; small windows read slightly larger than a sample z-score.
• Regime shifts. A structural change in the funding level inflates the z-score transiently until the window rolls past it.

See also

• FundingRate — the raw rate.
• FundingRateMean — its rolling mean.
• ZScore — the price-series equivalent.
• Indicators-Overview — the full taxonomy.