BollingerBandwidth

Bollinger Bandwidth — the width of the Bollinger Bands relative to the middle band: a normalised volatility reading.

Quick reference

Field	Value
Family	Volatility & Bands
Input type	f64 (single close)
Output type	f64
Output range	[0, ∞)
Default parameters	(period = 20, multiplier = 2.0) (Python)
Warmup period	period
Interpretation	Band width as a fraction of price; lows flag a "squeeze".

Formula

Bandwidth = (upper − lower) / middle

where upper, middle and lower come from BollingerBands. Since the bands are middle ± multiplier · stddev, the bandwidth simplifies to 2 · multiplier · stddev / middle — volatility normalised by price level. Its extremes name two classic patterns: the squeeze (bandwidth at a multi-month low — a coiled, quiet market that often precedes a sharp move) and the bulge (bandwidth at an extreme high — an exhausted, over-extended move).

Parameters

Name	Type	Default	Valid range	Description
period	usize	20 (Python)	>= 1	Bollinger Bands period. 0 errors with Error::PeriodZero.
multiplier	f64	2.0 (Python)	> 0	Band standard-deviation multiplier. <= 0 errors with Error::NonPositiveMultiplier.

The Python binding defaults the pair to (20, 2.0).

Inputs / Outputs

From crates/wickra-core/src/indicators/bollinger_bandwidth.rs:

use wickra::{Indicator, BollingerBandwidth};
// BollingerBandwidth: Input = f64, Output = f64
const _: fn(&mut BollingerBandwidth, f64) -> Option<f64> = <BollingerBandwidth as Indicator>::update;

A single f64 close in, an Option<f64> out. Python maps this to float | None / numpy.ndarray (NaN warmup); Node to number | null / Array<number> (NaN warmup).

Warmup

warmup_period() == period — identical to the underlying BollingerBands.

Edge cases

• Constant series. Flat prices collapse the bands onto the middle, so the width — and bandwidth — is 0.0 (constant_series_yields_zero pins this).
• Zero middle band. Bandwidth is undefined against a 0.0 middle band; the indicator reports 0.0 for that bar.
• Non-negative. Bandwidth is (upper − lower) / middle with upper >= lower and a positive middle band, so it is never negative (output_is_non_negative pins this).
• Reset. bbw.reset() clears the underlying bands.

Examples

Rust

use wickra::{BatchExt, Indicator, BollingerBandwidth};

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let mut bbw = BollingerBandwidth::new(20, 2.0)?;
    // A flat stretch then a volatile stretch: bandwidth rises.
    let mut prices: Vec<f64> = vec![100.0; 30];
    prices.extend((0..30).map(|i| 100.0 + (f64::from(i)).sin() * 10.0));
    let out = bbw.batch(&prices);
    println!("flat-window bandwidth: {:?}", out[25]);
    Ok(())
}

Output:

flat-window bandwidth: Some(0.0)

While prices are flat the bands sit on top of each other, so bandwidth is 0; once volatility arrives it climbs.

Python

import numpy as np
import wickra as ta

bbw = ta.BollingerBandwidth(20, 2.0)
prices = np.full(40, 100.0)  # flat series
print(bbw.batch(prices)[-1])  # 0.0

Output:

0.0

Node

const ta = require('wickra');
const bbw = new ta.BollingerBandwidth(20, 2.0);
const prices = Array.from({ length: 60 }, (_, i) => 100 + Math.sin(i * 0.3) * 6);
console.log('warmupPeriod:', bbw.warmupPeriod());

Interpretation

BollingerBandwidth is the standard way to quantify the Bollinger "squeeze". Volatility is mean-reverting and cyclical: extended periods of low bandwidth tend to be followed by expansion, and vice versa. Traders watch for bandwidth dropping to a multi-month low (the squeeze) as a heads-up that a directional move is loading — then take the direction from price breaking the band, or from a separate trend indicator.

Common pitfalls

• Treating the squeeze as directional. Low bandwidth says a move is coming, not which way. Confirm direction separately.
• Comparing raw bandwidth across instruments without context. It is normalised by price, which helps, but "low" is relative to each instrument's own history — compare against its own range.

References

John Bollinger, Bollinger on Bollinger Bands (2001). Bandwidth is one of Bollinger's two derived indicators (with %b).

See also

• Indicator-BollingerBands — the bands this measures.
• Indicator-PercentB — the companion derived indicator: price position within the bands.
• Indicators-Overview — the full taxonomy.