Extreme Reclaim

Price Action price-action reclaim false-break atr

Prior N-bar high or low is pierced and the close finishes back inside, with penetration at least k times Wilder ATR.

Visual Example

Eight bars with high 11, low 10, close 10.5, then a bar with low 9 and close 10.2. That bar pierces the prior low and closes back above it. With window 5, ATR length 5, and size_k 0.5, the penetration of 1 still passes after that bar's true range lifts ATR to 1.2. A close that stays below the prior low is a pierce, not a reclaim.

Description

Prior N-bar high or low is pierced and the close finishes back inside, with penetration at least k times Wilder ATR.

bullish is the full three-part test. bull_pierce and bull_reclaim are the parts, so a caller can drop the size filter. A close that stays beyond the extreme is a break, not a reclaim.

Price-action tooling with streaming and Polars batch parity. Rich outputs feed backtest signals, regime filters, and ML feature pipelines.

Not Ehlers. Pierce-and-reclaim from Build Alpha CustomIndicators.xml (Bergstrom): window 20, ATR 20, k = 0.5, penetration compared with >=.

Typical applications:

Size stops and position risk from band width or ATR expansion
Detect squeeze conditions (narrow bands) before breakout systems
Warm-up: first 20 bars 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):

\[\text{bull}: low_0 \le \min(low)_{1..N},\ close_0 > \min(low)_{1..N},\ \min(low)-low_0 \ge k\cdot ATR\]

Parameters

Parameter	Default	Description
`window`	20	Bars in the prior extreme. The current bar is excluded.
`atr_period`	20	Wilder ATR length for the penetration test.
`size_k`	0.5	Minimum penetration as a multiple of ATR.

Usage Examples

Streaming (Rust)

use quantwave_core::indicators::ExtremeReclaim;
use quantwave_core::traits::Next;

let mut ind = ExtremeReclaim::new(20);
for price in &prices {
    let value = ind.next(price);
}

Streaming (Python)

from quantwave import ExtremeReclaim

ind = ExtremeReclaim(20)
for price in prices:
    value = ind.next(price)

Polars Batch (Python)

import polars as pl
import quantwave as qw

def apply_extreme_reclaim(series: pl.Series) -> pl.Series:
    ind = qw.ExtremeReclaim(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_extreme_reclaim, return_dtype=pl.Float64).alias("extreme_reclaim")
    )
    .collect()
)

All surfaces are bit-identical via the single Next<T> implementation and proptests.

Edge Cases & Limitations

Warm-up: first 20 bars 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.

Sources & References

Primary Source: David Bergstrom, Build Alpha, https://www.buildalpha.com/backtest-ict-and-smc/ CustomIndicators.xml (window 20, ATR length 20, k = 0.5).

Implementation: quantwave-core/src/indicators/market_structure (ExtremeReclaim / _METADATA).

Provenance: Standards bulk upgrade 2026-10-02 IST — see docs/DOCUMENTATION_STANDARDS.md.