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ATR Trailing Stop

Classic volatility trend stop-loss atr classic

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

This trailing stop 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. Stop distances differ from a TradingView-equivalent ATR trailing stop. Review this before wiring it into live risk sizing.

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("atr_ts") to read the divergence programmatically.

A trailing stop based on Average True Range to keep trades in a trend.

Visual Example

ATR Trailing Stop — 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

A trailing stop based on Average True Range to keep trades in a trend.

Use as a dynamic trailing stop that widens in volatile markets and tightens in calm ones, automatically adjusting stop distance to current market conditions.

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

ATR Trailing Stop uses Average True Range to set a stop distance that scales with market volatility. During high-volatility regimes the stop moves further from price to avoid premature exit; during low-volatility regimes it tightens to lock in more profit. It is one of the most robust mechanical stop methods in systematic trading.

Typical applications:

  • Size stops and position risk from band width or ATR expansion
  • Detect squeeze conditions (narrow bands) before breakout systems
  • Warm-up: first 10 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/atr_ts.rs):

\[ Stop = P_{high} - (Multiplier \times ATR) \]

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

Parameters

Parameter Default Description
period 10 ATR period
multiplier 3.0 ATR Multiplier

Usage Examples

Streaming (Rust)

use quantwave_core::indicators::ATR_TS;
use quantwave_core::traits::Next;

let mut ind = ATR_TS::new(10);
for price in &prices {
    let value = ind.next(price);
}

Streaming (Python)

from quantwave import ATR_TS

ind = ATR_TS(10)
for price in prices:
    value = ind.next(price)

Polars Batch (Python)

import polars as pl
import quantwave as qw

def apply_atr_trailing_stop(series: pl.Series) -> pl.Series:
    ind = qw.ATR_TS(10)
    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_atr_trailing_stop, return_dtype=pl.Float64).alias("atr_trailing_stop")
    )
    .collect()
)

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

Edge Cases & Limitations

  • Warm-up: first 10 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.tradingview.com/support/solutions/43000589105-average-true-range-atr/

Implementation: quantwave-core/src/indicators/atr_ts.rs (ATR_TS / ATR_TS_METADATA). Parity: quantwave-core/tests/gold_standard/atr_ts.json

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