Price Imbalance
Latest three-bar untraded range on each side: top, bottom, whether price has traded through the far side, and whether the gap exceeds a multiple of Wilder ATR.
Visual Example
Bars (high, low, close) = (10, 8, 9), (11, 9, 10), (14, 12, 13). The third bar's low is above the high from two bars earlier, so a bullish range opens with top 12 and bottom 10. A later bar with low 10.5 leaves it open. A later bar with low 9.5 trades through the bottom and closes it. The stored boundaries stay 12 and 10.
Description
Latest three-bar untraded range on each side: top, bottom, whether price has traded through the far side, and whether the gap exceeds a multiple of Wilder ATR.
Read bull_open / bear_open as the range that is still unfilled, and bull_top / bull_bottom as the two prices. Break of structure stays on Market Structure; this does not emit one.
Price-action tooling with streaming and Polars batch parity. Rich outputs feed backtest signals, regime filters, and ML feature pipelines.
Not Ehlers. Three-bar range from Build Alpha CustomIndicators.xml (Bergstrom). Bull gap is strict low[0] > high[2]. Size uses Wilder ATR, length 20 in that file (the article prose says 14).
Typical applications:
- Size stops and position risk from band width or ATR expansion
- Detect squeeze conditions (narrow bands) before breakout systems
- Warm-up: first
20bars build rolling volatility state - Combine with trend direction (SuperTrend, MACD) for breakout bias
QuantWave implements this via the universal Next<T> trait — bit-identical across Rust streaming, Python streaming, and Polars .ta() batch plugins.
Formula / Specification
Implementation (market_structure):
Parameters
| Parameter | Default | Description |
|---|---|---|
atr_period |
20 | Wilder ATR length for the size test. |
size_k |
0.5 | Minimum gap as a multiple of ATR. Bull uses >, bear uses >=, matching the source file. |
Usage Examples
Streaming (Rust)
use quantwave_core::indicators::PriceImbalance;
use quantwave_core::traits::Next;
let mut ind = PriceImbalance::new(20);
for price in &prices {
let value = ind.next(price);
}
Streaming (Python)
from quantwave import PriceImbalance
ind = PriceImbalance(20)
for price in prices:
value = ind.next(price)
Polars Batch (Python)
import polars as pl
import quantwave as qw
def apply_price_imbalance(series: pl.Series) -> pl.Series:
ind = qw.PriceImbalance(20)
return pl.Series([ind.next(float(v)) for v in series.to_list()])
df = (
pl.read_csv('ohlcv.csv')
.lazy()
.with_columns(
pl.col("close").map_batches(apply_price_imbalance, return_dtype=pl.Float64).alias("price_imbalance")
)
.collect()
)
All surfaces are bit-identical via the single Next<T> implementation and proptests.
Edge Cases & Limitations
- Warm-up: first
20bars may return NaN or partial state per implementation. - Parameter sensitivity: smaller periods increase noise; larger periods increase lag.
- Sudden gaps or bad ticks can distort rolling windows — consider pre-filtering.
- Single-series indicators ignore volume unless otherwise documented.
- Validated via proptests against gold-standard vectors where available.
- No look-ahead bias; streaming and Polars batch paths are bit-identical.
Boundary Behavior
| Condition | Behavior |
|---|---|
| Warm-up | Early bars return empty event lists or default structs (no scalar NaN). |
| period > len | Insufficient history yields no events rather than NaN scalars. |
| NaN inputs | NaN OHLC typically suppresses event detection for that bar. |
| Invalid params | Invalid swing_strength or tolerance raises ValueError. |
| Empty data | Empty input returns empty event collections. |
Related Indicators & See Also
Sources & References
Primary Source: David Bergstrom, Build Alpha, https://www.buildalpha.com/backtest-ict-and-smc/ CustomIndicators.xml (ATR length 20, k = 0.5; the article prose says ATR 14).
Implementation: quantwave-core/src/indicators/market_structure (PriceImbalance / _METADATA).
Provenance: Standards bulk upgrade 2026-10-02 IST — see docs/DOCUMENTATION_STANDARDS.md.