Skip to content

TTM Squeeze

Classic volatility momentum breakout squeeze classic

Uses the EMA-smoothed Atr, not Wilder's ATR

The Keltner leg of the squeeze test is built on QuantWave's Atr, which smooths true range with an EMA (alpha = 2/(period+1)) rather than Wilder's RMA (alpha = 1/period, SMA-seeded) used by TA-Lib and TradingView Pine's ta.atr. Squeeze on/off transitions can differ near the threshold from implementations that use a Wilder ATR.

No source has been recorded for the EMA smoothing — the formula_source recorded for this indicator describes the Wilder-based construction. See Average True Range for the full surface-by-surface breakdown, and quantwave.conventions("ttm_squeeze") to read the divergence programmatically.

TTM Squeeze measures the relationship between Bollinger Bands and Keltner Channels to identify volatility consolidations.

Visual Example

TTM Squeeze — annotated preview mapping to core implementation

Synthetic ideal per library logic. Generated 2026-07-01 IST via docs/generate_all_previews.py (reproducible; maps to core Next<T> implementation).

Description

TTM Squeeze measures the relationship between Bollinger Bands and Keltner Channels to identify volatility consolidations.

Use to identify periods of compressed volatility (Bollinger Bands inside Keltner Channels) followed by high-energy breakouts. The momentum histogram direction at squeeze release indicates trade direction.

Native Rust implementation with gold-standard or TA-Lib parity tests where applicable.

The TTM Squeeze, developed by John Carter, identifies market consolidation by detecting when Bollinger Bands contract inside Keltner Channels — a squeeze condition indicating coiling energy. When the bands expand back outside the Keltner Channels, the squeeze releases and a momentum histogram shows the expected breakout direction. — Mastering the Trade, John Carter

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 (quantwave-core/src/indicators/ttm_squeeze.rs):

\[ \text{Squeeze} = BB_{width} < KC_{width} \]

Gold-standard parity vectors: quantwave-core/tests/gold_standard/ttm_squeeze.json.

Parameters

Parameter Default Description
bb_period 20 Bollinger Bands Period
bb_mult 2.0 Bollinger Bands Multiplier
kc_period 20 Keltner Channel Period
kc_mult 1.5 Keltner Channel Multiplier

Usage Examples

Streaming (Rust)

use quantwave_core::indicators::TTM_SQUEEZE;
use quantwave_core::traits::Next;

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

Streaming (Python)

from quantwave import TTM_SQUEEZE

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

Polars Batch (Python)

import polars as pl
import quantwave as qw

def apply_ttm_squeeze(series: pl.Series) -> pl.Series:
    ind = qw.TTM_SQUEEZE(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_ttm_squeeze, return_dtype=pl.Float64).alias("ttm_squeeze")
    )
    .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 Leading bars return NaN until warmup_bars is satisfied.
period > len When period exceeds series length, output is all NaN.
NaN inputs NaN in input propagates to output (NaN out).
Invalid params Non-positive period or missing required params raise ValueError.
Empty data Empty input returns an empty result series.

Sources & References

Primary Source: https://www.investopedia.com/articles/active-trading/110714/intro-ttm-squeeze-indicator.asp

Implementation: quantwave-core/src/indicators/ttm_squeeze.rs (TTM_SQUEEZE / TTM_SQUEEZE_METADATA). Parity: quantwave-core/tests/gold_standard/ttm_squeeze.json

Provenance: Standards bulk upgrade 2026-07-01 IST — see docs/DOCUMENTATION_STANDARDS.md.