WilliamsR

Williams %R — Larry Williams' negated mirror of fast Stochastic %K, plotted on [−100, 0] instead of [0, 100].

Quick reference

Field	Value
Family	Momentum Oscillators
Input type	Candle
Output type	f64
Output range	[−100, 0]
Default parameters	period = 14 (Python)
Warmup period	period (14 for period = 14)
Interpretation	overbought above −20, oversold below −80

Formula

For each new candle, let HH and LL be the highest high and lowest low over the last period candles:

HH_t = max(high_{t-period+1}, …, high_t)
LL_t = min(low_{t-period+1},  …, low_t)

%R_t = −100 · (HH_t − close_t) / (HH_t − LL_t)        when HH ≠ LL
%R_t = −50                                            when HH == LL (flat range)

This is the negation of fast Stochastic %K measured from the top of the window: when the close sits at the window high, %R = 0; when it sits at the window low, %R = −100.

Parameters

Name	Type	Default (Python)	Valid range	Description
period	usize	14	>= 1	Lookback window for the HH / LL extrema.

WilliamsR::new(0) returns Error::PeriodZero.

Inputs / Outputs

From impl Indicator for WilliamsR:

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

Python's WilliamsR.batch(high, low, close) returns a 1-D float64np.ndarray (warmup → NaN). Node's WilliamsR.batch(high, low, close) returns a flat number[] (warmup → NaN); only batch is exposed on the Node binding.

Warmup

warmup_period() returns period. Williams %R works on a rolling range, not a rolling diff, so once period candles have arrived the indicator is ready — there is no off-by-one. The first period − 1 calls to update() return None; the period-th call returns the first Some(value).

Edge cases

• Close at the window high. %R == 0 exactly. The unit test close_at_high_yields_zero pins this case (with H, L = 8, 10, 12 and closes ending at 12, the result is 0). Note that floating-point zero can print as -0 when scaled by -100; both compare equal to 0.
• Close at the window low. %R == −100 exactly (test close_at_low_yields_minus_100).
• Flat range. When HH == LL, the implementation returns −50 as the neutral convention.
• Reset. reset() clears the candle buffer; the next period updates return None.

Examples

Rust

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

let candles = vec![
    Candle::new(9.0, 10.0, 8.0, 9.0, 1.0, 0).unwrap(),
    Candle::new(10.0, 11.0, 9.0, 10.0, 1.0, 0).unwrap(),
    Candle::new(12.0, 12.0, 10.0, 12.0, 1.0, 0).unwrap(),  // close == HH
];
let mut w = WilliamsR::new(3)?;
let out = w.batch(&candles);
println!("Williams %R(3) at idx 2 = {}", out[2].unwrap());
# Ok::<(), wickra::Error>(())

Verified output:

Williams %R(3) at idx 2 = -0

(-0.0 is bit-equal to 0.0 in IEEE-754; the negative sign is just a side effect of multiplying +0.0 by -100.0.)

Python

import numpy as np
import wickra as ta

high  = np.array([10.0, 11.0, 12.0])
low   = np.array([8.0,  9.0,  10.0])
close = np.array([9.0,  10.0, 12.0])
w = ta.WilliamsR(3)
out = w.batch(high, low, close)
print('warmup:', w.warmup_period())
print('row 2 :', out[2])

Verified output:

warmup: 3
row 2 : -0.0

Node

const wickra = require('wickra');

const high  = [10.0, 11.0, 12.0];
const low   = [8.0,  9.0,  10.0];
const close = [9.0,  10.0, 12.0];
const w = new wickra.WilliamsR(3);
const out = w.batch(high, low, close);
console.log('row 2:', out[2]);

Verified output:

row 2: -0

Interpretation

• Larry Williams' thresholds. %R > −20 is overbought; %R < −80 is oversold. Because the scale runs from −100 (oversold) to 0 (overbought), the inequalities feel inverted to anyone used to Stochastic — but the positions of the bands are identical.
• Failure swings. A %R value that pokes into overbought, retreats, then fails to reach overbought on the next rally is the classic Williams "failure swing" — interpreted as bearish exhaustion.
• Use alongside trend. %R is a pure range oscillator; in a strong trend it can stay pinned at 0 or −100 for many bars. Pair with ADX or a moving-average filter before reading it as a reversal cue.

Common pitfalls

• Sign inversion. Williams %R lives in [−100, 0], not [0, 100]. Code that assumes "higher value = more bullish" will work; code that assumes a positive range will silently mis-classify every value.
• Mirror of fast %K, not slow. Williams %R has no built-in smoothing; it tracks raw %K (with a sign flip and a shift). If you need a smoothed version, drive %R through your own Sma or Ema via a Chain.

References

• Larry Williams, How I Made One Million Dollars … Last Year … Trading Commodities, Windsor Books, 1973 — the original %R publication.

See also

• Indicator: Stochastic — the positive-axis sibling; %R and %K are linked by %R = %K − 100.
• Indicator: Rsi — slower bounded oscillator, better behaved in trending markets.
• Warmup Periods — bare period (no off-by-one).