HurstChannel

SMA centerline wrapped by the rolling high-low range. A simpler, range-based volatility envelope than Bollinger's stddev or Keltner's ATR.

Quick reference

Field	Value
Family	Bands & Channels
Input type	Candle (uses high, low for the range; close for the midline)
Output type	HurstChannelOutput { upper, middle, lower }
Output range	unbounded; lower ≤ middle ≤ upper
Default parameters	period = 10, multiplier = 0.5 (inner channel)
Warmup period	period (exact — first emission on bar period)
Interpretation	Hurst-cycle "inner" / "outer" channel. Inner (≈0.5) contains the short-term swing; outer (≈1.0) the medium-term cycle.

Formula

middle = SMA(close, period)
range  = max(high, period) − min(low, period)
upper  = middle + multiplier · range
lower  = middle − multiplier · range

With multiplier = 0.5 the channel reduces to a centerline that hugs the midpoint of the corresponding Donchian envelope. Bressert and Brian Millard's cycle-trading work commonly uses an "inner" multiplier around 0.5 for short-term swings and an "outer" multiplier near 1.0 for medium-term cycles.

Parameters

Name	Type	Default	Constraint	Source
period	usize	10	>= 1	HurstChannel::new (hurst_channel.rs:65)
multiplier	f64	0.5	finite, > 0	hurst_channel.rs:66

period == 0 returns [Error::PeriodZero]; a non-finite or non-positive multiplier returns [Error::NonPositiveMultiplier]. Python defaults come from #[pyo3(signature = (period=10, multiplier=0.5))]; the Node constructor takes both arguments explicitly.

Inputs / Outputs

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

• Python streaming. update(candle) returns (upper, middle, lower) or None.
• Python batch. HurstChannel.batch(high, low, close) returns an (n, 3) np.ndarray with columns [upper, middle, lower]; warmup rows are NaN across all three columns.
• Node streaming. update(high, low, close) returns a { upper, middle, lower } object or null.
• Node batch. batch(high, low, close) returns a flat Array<number> of length n * 3 interleaved per row [u0, m0, l0, u1, m1, l1, …].

Warmup

warmup_period() reports period and the figure is exact: the SMA centerline needs a full window before the channel is defined, so the first non-None output lands on candle period (index period − 1). The rolling high/low deques are kept in lock-step with the SMA, so readiness is governed entirely by Sma::is_ready() — pinned by the reference_values test (out[3].is_none(), out[4] set for period = 5).

Edge cases

• Flat market. A constant-OHLC series collapses range to 0, so upper == middle == lower (test flat_market_collapses_bands).
• Ordering. upper >= middle >= lower always holds because range >= 0 and multiplier > 0 (test upper_above_middle_above_lower).
• Reset. reset() clears the SMA and both high/low deques; the next update restarts the warmup countdown.
• Non-finite inputs. Candle::new rejects non-finite OHLC up front, so the indicator never sees NaN/inf.

Examples

Rust

use wickra::{BatchExt, Candle, HurstChannel, Indicator};

fn main() -> Result<(), Box<dyn std::error::Error>> {
    // Five identical candles: high = 12, low = 8, close = 10.
    let candles = vec![Candle::new(10.0, 12.0, 8.0, 10.0, 1.0, 0)?; 5];
    let mut hc = HurstChannel::new(5, 0.5)?;
    for v in hc.batch(&candles) {
        println!("{:?}", v);
    }
    Ok(())
}

Output:

None
None
None
None
Some(HurstChannelOutput { upper: 12.0, middle: 10.0, lower: 8.0 })

SMA(close, 5) = 10, range = 12 − 8 = 4, and with multiplier = 0.5 the bands sit at 10 ± 0.5·4 = {12, 8}. This matches the reference_values test in hurst_channel.rs.

Python

import numpy as np
import wickra as ta

hc = ta.HurstChannel(5, 0.5)
high  = np.full(5, 12.0)
low   = np.full(5, 8.0)
close = np.full(5, 10.0)
print(hc.batch(high, low, close))

Output:

[[nan nan nan]
 [nan nan nan]
 [nan nan nan]
 [nan nan nan]
 [12. 10.  8.]]

Node

const ta = require('wickra');
const hc = new ta.HurstChannel(5, 0.5);
for (let i = 0; i < 4; i++) hc.update(12, 8, 10);
console.log(hc.update(12, 8, 10)); // { upper: 12, middle: 10, lower: 8 }

Interpretation

The Hurst Channel sizes its envelope by the realised high-low range of the window rather than by a statistical dispersion measure. Two canonical uses:

1. Cycle channels. Run two instances on the same period — an inner channel at multiplier ≈ 0.5 and an outer at ≈ 1.0. Price oscillating inside the inner channel marks the short-cycle swing; tags of the outer channel mark medium-cycle extremes. This is the Hurst/Bressert cycle-trading reading.
2. Mean reversion. A close beyond the inner channel that fails to reach the outer channel is a fade candidate back toward the SMA midline.

Prefer the Hurst Channel over BollingerBands when you want the band width to track the visible trading range instead of a sigma estimate that a single outlier bar can inflate.

Common pitfalls

• Confusing the channel with the HurstExponent. Despite the shared name they are unrelated — this is Brian Millard's range channel, not the fractal H statistic.
• Treating multiplier as a sigma count. It scales the raw price range, not a standard deviation, so a multiplier of 2.0 here is a far wider band than 2σ Bollinger.

References

• Brian Millard, Channel Analysis, John Wiley & Sons, 1990.
• Walter Bressert, The Power of Oscillator/Cycle Combinations (1991), for the inner/outer channel interpretation.

See also

• Donchian — pure rolling high/low (no midline offset).
• BollingerBands — sigma-based dispersion.
• Keltner — ATR-based dispersion.
• MaEnvelope — fixed-percent band around an SMA.