Value Area (POC / VAH / VAL)

Market-profile-style volume distribution. Buckets the last period candles' volumes into bin_count price bins (each bar's volume spread uniformly across its [low, high] range), finds the Point of Control (highest-volume bin), then expands outward from the POC until the configured percentage of total volume (default 70%) is enclosed — Value Area High (VAH) and Value Area Low (VAL).

Quick reference

Item	Value
Family	Market Profile
Input type	Candle (uses high, low, volume)
Output type	ValueAreaOutput { poc, vah, val }
Output range	unbounded (price-units)
Default parameters	period, bin_count, value_area_pct (typical (20, 50, 0.70))
Warmup period	period
Interpretation	Volume-weighted "fair value" zone over recent history

Formula

1. Spread each candle's volume uniformly across [low, high]
   among bin_count fixed price bins.
2. POC = price of bin with maximum cumulative volume.
3. Starting at POC, alternately absorb the higher-volume neighbour
   above or below the current Value Area until the absorbed volume
   reaches value_area_pct · total_volume.
4. VAH = upper boundary of absorbed bins; VAL = lower boundary.

Single-print bars (low == high) dump their whole volume into a single bin. See crates/wickra-core/src/indicators/value_area.rs.

Parameters

Name	Type	Default	Constraint	Description
period	usize	none	> 0	Rolling window of candles.
bin_count	usize	none	> 1	Number of price bins.
value_area_pct	f64	none	finite, (0, 1]	Target volume fraction (0.70 = classic 70%).

ValueArea::new returns Error::InvalidPeriod for out-of-range parameters.

Inputs / Outputs

Indicator<Input = Candle, Output = ValueAreaOutput> with three fields. Python: (n, 3) array; Node: flat number[] of length n * 3.

Warmup

warmup_period() == period. The bin distribution needs the full window to stabilise.

Edge cases

• Single-print bars. low == high dumps full volume into one bin; no spreading needed.
• Bin resolution. Higher bin_count increases price precision but slows computation.
• Volume = 0 candle. Contributes nothing; doesn't change the distribution.
• Reset. Clears the rolling window.

Examples

Rust

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

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let candles: Vec<Candle> = (0..50).map(|i| {
        let b = 100.0 + (f64::from(i) * 0.3).sin() * 3.0;
        Candle::new(b, b + 1.0, b - 1.0, b, 10.0, i as i64).unwrap()
    }).collect();
    let mut va = ValueArea::new(20, 50, 0.70)?;
    if let Some(o) = va.batch(&candles)[30] {
        println!("POC={}  VAH={}  VAL={}", o.poc, o.vah, o.val);
    }
    Ok(())
}

Python

import numpy as np
import wickra as ta

n = 50
base = 100 + np.sin(np.linspace(0, 15, n)) * 3
candles_h = base + 1
candles_l = base - 1
candles_v = np.full(n, 10.0)

va = ta.ValueArea(20, 50, 0.70)
print(va.batch(candles_h, candles_l, candles_v))  # (n, 3): [poc, vah, val]

Node

const wickra = require('wickra');
const va = new wickra.ValueArea(20, 50, 0.70);
// ... high, low, volume arrays

Streaming

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

let mut va = ValueArea::new(78, 100, 0.70).unwrap();  // ~1 day on 5-min bars
let candle_stream: Vec<wickra::Candle> = Vec::new(); // your live OHLCV candle feed
for bar in candle_stream {
    if let Some(o) = va.update(bar) {
        // POC = "magnet" price; VAH/VAL = boundaries of fair-value zone
    }
}

Interpretation

• POC. The price level where the most volume traded — a "magnet" that price tends to revisit. High-frequency mean-reversion systems target the POC.
• VAH / VAL. Boundaries of the fair-value zone. Price trading outside VAH or below VAL signals "out-of-value" — a potential trend day or breakout setup.
• Vs. session-level Market Profile. This is a rolling Value Area, not the session-anchored TPO profile from Steidlmayer's original work. Useful for continuous adaptive fair-value reference.

Common pitfalls

• Bin resolution mismatch. bin_count = 10 with high-priced instruments → coarse POC. bin_count = 200 on low-priced → over-resolution. Match bin count to typical price range.
• Period choice. Too short → noisy POC; too long → stale POC. ~1-day equivalent on the timeframe is typical.
• Volume sensitivity. Outlier high-volume bars dominate the distribution. Pre-filter or cap if necessary.

References

• J. Peter Steidlmayer & Steven B. Hawkins, Steidlmayer on Markets (2003) — formal Market Profile / Value Area treatment.

See also

• InitialBalance — first-bars range.
• OpeningRange — opening-range breakout reference.
• Vwap — closely-related volume-weighted price.
• Indicators-Overview — full taxonomy.