HighLowIndex

The High-Low Index — a simple moving average of the record high percent, 100 * new_highs / (new_highs + new_lows). Above 50 means new highs dominate; below 50 means new lows dominate.

Quick reference

Item	Value
Family	Market Breadth
Input type	CrossSection — the per-symbol state of the whole universe
Output type	f64 (a percentage in 0..=100)
Output range	0..=100
Default parameters	period = 10 (classic window)
Warmup period	period
Interpretation	Leadership breadth (new highs vs new lows)

Formula

record_high_percent = 100 * new_highs / max(new_highs + new_lows, 1)   # per tick
index = SMA(record_high_percent, period)

The record high percent is the share of new-extreme issues that are new highs; smoothing it over a window (classically 10) gives the High-Low Index. The new-extreme count is floored to one so a tick with no new highs or lows contributes 0.0. Backed by an internal Sma, so the window sum is O(1) per tick. See crates/wickra-core/src/indicators/high_low_index.rs.

Parameters

Parameter	Type	Default	Source
period	usize	(10)	high_low_index.rs — HighLowIndex::new(period)

new(period) returns Err(Error::PeriodZero) if period == 0.

Inputs / Outputs

Indicator<Input = CrossSection, Output = f64>:

use wickra::{CrossSection, HighLowIndex, Indicator};

const _: fn(&mut HighLowIndex, CrossSection) -> Option<f64> =
    <HighLowIndex as Indicator>::update;

This indicator reads the new_high / new_low flags. The bindings pass a tick as four equal-length parallel arrays; the constructor takes the window length:

• Python: HighLowIndex(period), update(change, volume, new_high, new_low); batch(...) returns a 1-D ndarray with NaN during warmup.
• Node: new HighLowIndex(period), update(change, volume, newHigh, newLow); batch returns number[] with NaN during warmup.
• WASM: new HighLowIndex(period), update(...) only; flag arrays are numeric.

Warmup

warmup_period() == period; the SMA emits None until period ticks have been seen (tests accessors_and_metadata, averages_the_record_high_percent). A zero period is rejected (test rejects_zero_period).

Edge cases

• Warmup. Returns None (Python/Node NaN) until the window is full (test averages_the_record_high_percent).
• No extremes. A tick with no new highs or lows floors to a 0.0 record-high percent (test no_extremes_floors_to_zero_percent).
• Reset. reset() clears the window and returns the indicator to not-ready (test reset_clears_state).
• Zero period. Rejected at construction (test rejects_zero_period).
• Invalid / empty universe. Rejected by CrossSection::new.

Examples

Rust

use wickra::{CrossSection, HighLowIndex, Indicator, Member};

let mut hli = HighLowIndex::new(2)?;
let highs = CrossSection::new(vec![Member::new(1.0, 1.0, true, false)], 0)?;
assert_eq!(hli.update(highs.clone()), None); // warming up
assert_eq!(hli.update(highs), Some(100.0));  // all new highs

Python

import wickra as ta

hli = ta.HighLowIndex(10)
# 8 new highs, 2 new lows -> record high percent 80.
print(hli.update([1.0] * 10, [10.0] * 10, [True] * 8 + [False] * 2, [False] * 8 + [True] * 2))
# None   (warming up)

Node

const { HighLowIndex } = require('wickra');

const hli = new HighLowIndex(2);
const change = new Array(10).fill(1);
const vol = new Array(10).fill(10);
const highs = [true, true, true, true, true, true, true, true, false, false];
const lows = highs.map((h) => !h);
console.log(hli.update(change, vol, highs, lows)); // null (warming up)

Streaming

import wickra as ta

hli = ta.HighLowIndex(2)
change = [1.0] * 10
vol = [10.0] * 10
# 80% new highs, then 60%.
print(hli.update(change, vol, [True] * 8 + [False] * 2, [False] * 8 + [True] * 2))  # None
print(hli.update(change, vol, [True] * 6 + [False] * 4, [False] * 6 + [True] * 4))  # 70.0

Interpretation

The High-Low Index distils leadership breadth into a single bounded line.

1. Above 50. New highs dominate — a broad, healthy uptrend.
2. Below 50. New lows dominate — broad weakness.
3. 30 / 70 lines. Watched as oversold / overbought breadth thresholds; reversals from those zones are signals.

Common pitfalls

• Flag lookback. The "new high/low" definition lives in how you set the flags; keep it consistent across the universe and over time.
• Sparse extremes. When few issues make new highs or lows the record-high percent is noisy; the smoothing helps but does not eliminate it.
• Universe must be stable. Changing membership makes the percentages incomparable.

References

• Colby, R. W. (2002). The Encyclopedia of Technical Market Indicators (2nd ed.) — High-Low Index / Record High Percent.

See also

• Indicator-NewHighsNewLows — the raw net these percentages are built on.
• Indicators-Overview — the full taxonomy.
• Warmup-Periods — verified warmup table.