Woodie Pivots

Tom Williams' close-weighted pivot variant. The double-weighted close shifts the pivot toward where most of the session's activity actually settled — useful in trending markets where the close is more meaningful than the typical-price midpoint. Two resistances and two supports (vs Classic's three).

Quick reference

Item	Value
Family	Pivots & S/R
Input type	Candle
Output type	WoodiePivotsOutput { pp, r1, r2, s1, s2 }
Output range	unbounded (price-units)
Default parameters	none — WoodiePivots::new()
Warmup period	1
Interpretation	Close-weighted reference levels for the next session

Formula

PP = (H + L + 2·C) / 4

R1 = 2·PP − L        S1 = 2·PP − H
R2 = PP + (H − L)    S2 = PP − (H − L)

R1/S1 use the same 2·PP − L / H formula as Classic; R2/S2 use the same range-width extension. The difference from Classic is purely in the pivot itself. See crates/wickra-core/src/indicators/woodie_pivots.rs.

Parameters

None — WoodiePivots::new() takes no arguments.

Inputs / Outputs

Indicator<Input = Candle, Output = WoodiePivotsOutput> with five fields (pp, r1, r2, s1, s2).

• Python. WoodiePivots().batch(high, low, close) returns an (n, 5) float64 array.
• Node. Flat number[] of length n * 5.

Warmup

warmup_period() == 1. First candle emits the first set.

Edge cases

• H == L. All R/S collapse to PP.
• Strong closes near the high. The doubled-weight close pulls PP up, lifting R1/R2 and S1/S2 in tandem. Compared to Classic Pivots on the same bar, Woodie levels are biased toward the close.
• Reset. Stateless.

Examples

Rust

use wickra::{Candle, Indicator, WoodiePivots};

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let prev = Candle::new(100.0, 110.0, 90.0, 108.0, 1.0, 0)?;
    let mut w = WoodiePivots::new();
    let l = w.update(prev).unwrap();
    // PP = (110 + 90 + 2·108) / 4 = 416/4 = 104
    // R1 = 2·104 − 90 = 118
    // S1 = 2·104 − 110 = 98
    println!("PP={}  R1={}  S1={}", l.pp, l.r1, l.s1);
    Ok(())
}

Python

import numpy as np
import wickra as ta

high  = np.array([110.0])
low   = np.array([ 90.0])
close = np.array([108.0])  # close near the high

w = ta.WoodiePivots()
out = w.batch(high, low, close)
print(out[0])  # pp, r1, r2, s1, s2

Node

const wickra = require('wickra');
const w = new wickra.WoodiePivots();
console.log(w.batch([110], [90], [108]));

Streaming on session bars

use wickra::{Candle, Indicator, WoodiePivots};

let mut w = WoodiePivots::new();
let session_aggregator: Vec<wickra::Candle> = Vec::new(); // your stream of completed session bars
for bar in session_aggregator {
    let levels = w.update(bar).unwrap();
}

Interpretation

• Trending-day bias. Compared to Classic Pivots, Woodie's levels shift in the direction of the previous close. A strong bullish close raises the next session's pivot and resistances, reflecting market memory of where buyers ended the day.
• R1 / S1 reactions. Same 2·PP − L / H formula as Classic, so R1 / S1 react at similar widths but at the shifted pivot.
• Two-tier vs three-tier. Woodie deliberately stops at R2/S2 — Williams felt R3/S3-style extensions added more noise than signal. If you want R3/S3, use Classic or Fibonacci.

Common pitfalls

• Treating Woodie pivot as Classic with adjusted close. The PP formula is genuinely different — (H + L + 2C) / 4 instead of (H + L + C) / 3. Don't try to map it.
• Indecisive doji bar. When close ≈ midpoint of high/low, Woodie and Classic produce nearly identical levels — the doubled-close weighting only matters on directional bars.
• Session aggregation. Same as all pivots — feed session-aggregated bars only.

References

• Tom Williams (the Volume Spread Analysis author of the same name) popularised the close-weighted pivot variant in the late 1990s. The formulation circulated through trading forums before being formally documented in commercial charting packages.

See also

• ClassicPivots — non-weighted variant.
• FibonacciPivots — Fib-spaced alternative.
• Camarilla — close-anchored four-tier alternative.
• DemarkPivots — conditional open-aware variant.
• Indicators-Overview — full taxonomy.