PercentB

Bollinger %b — where price sits within the Bollinger Bands, scaled so 0 is the lower band and 1 is the upper band.

Quick reference

Field	Value
Family	Volatility & Bands
Input type	f64 (single close)
Output type	f64
Output range	unbounded (0 = lower band, 1 = upper band)
Default parameters	(period = 20, multiplier = 2.0) (Python)
Warmup period	period
Interpretation	Price position in the band; > 1 / < 0 = band overshoot.

Formula

%b = (price − lower) / (upper − lower)

where upper and lower come from BollingerBands. %b = 1 is price exactly on the upper band, %b = 0 on the lower band, %b = 0.5 on the middle band. The value is deliberately not clamped: a close above the upper band gives %b > 1, a close below the lower band gives %b < 0 — so %b shows band overshoots directly.

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/percent_b.rs:

use wickra::{Indicator, PercentB};
// PercentB: Input = f64, Output = f64
const _: fn(&mut PercentB, f64) -> Option<f64> = <PercentB 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; with zero band width the price is exactly mid-band and %b is reported as 0.5 (constant_series_yields_midpoint pins this).
• Band overshoot. %b is not clamped — values outside [0, 1] are expected and meaningful.
• NaN / infinity inputs. Passed straight to the underlying BollingerBands, which drops them.
• Reset. pb.reset() clears the underlying bands.

Examples

Rust

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

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let mut pb = PercentB::new(5, 2.0)?;
    // A flat series: price is exactly mid-band, so %b is 0.5.
    let out = pb.batch(&[100.0; 20]);
    println!("{:?}", out[10]);
    Ok(())
}

Output:

Some(0.5)

Python

import numpy as np
import wickra as ta

pb = ta.PercentB(20, 2.0)
prices = np.full(40, 100.0)  # flat series -> mid-band
print(pb.batch(prices)[-1])  # 0.5

Output:

0.5

Node

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

Interpretation

PercentB turns "is price near a band?" into a single number. The canonical reads: %b > 1 is a close above the upper band (strong, often overbought); %b < 0 is a close below the lower band (weak, often oversold); %b crossing 0.5 is price crossing the middle SMA. Because it is normalised, %b is the right input when you want to compare band position across instruments, or feed band position into another rule — for example "buy when %b crosses back above 0 from below".

Common pitfalls

• Expecting [0, 1] bounds. %b is intentionally unclamped; values outside [0, 1] are the band-overshoot signal, not an error.
• Confusing it with bandwidth. %b is price position; BollingerBandwidth is band width.

References

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

See also

• Indicator-BollingerBands — the bands this locates price within.
• Indicator-BollingerBandwidth — the companion derived indicator: band width.
• Indicators-Overview — the full taxonomy.