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HighPass

Ehlers DSP filter ehlers dsp high-pass cycle

A second-order High Pass filter that rejects low-frequency components.

Visual Example

HighPass — annotated preview mapping to core implementation

Synthetic ideal per library logic. Generated 2026-06-25 IST via docs/generate_all_previews.py (reproducible; maps to core Next<T> implementation).

Description

The HighPass indicator is a technical analysis tool that a second-order high pass filter that rejects low-frequency components.

This indicator is primarily used for identifying key market conditions. It provides a robust signal that can be easily integrated into both simple strategies and more complex machine learning feature pipelines. Compared to its alternatives, it offers a distinct balance of responsiveness and stability.

Traders often combine this with other metrics to confirm signals and avoid false positives during sideways market regimes. It remains a standard tool for systematic trading models.

Apply to price to isolate the cyclical component by attenuating the low-frequency trend. Use as the first stage before an oscillator or spectrum analyser.

Ehlers derives the one-pole high-pass filter in Cycle Analytics for Traders analogously to EMA derivation, but applied to price differences rather than levels. It removes the DC component and low-frequency trend, leaving the cyclical content for downstream analysis.

QuantWave implements this indicator via the universal Next<T> trait, guaranteeing bit-identical results between Rust streaming, Python streaming, and Polars batch (.ta() / map_batches) surfaces.

Formula / Specification

Implementation (quantwave-core/src/indicators/high_pass.rs):

[ a_1 = \exp\left(-\frac{1.414\pi}{Period}\right) ] [ c_2 = 2a_1 \cos\left(\frac{1.414\pi}{Period}\right) ] [ c_3 = -a_1^2 ] [ c_1 = (1 + c_2 - c_3) / 4 ] [ HP = c_1 (Price - 2 Price_{t-1} + Price_{t-2}) + c_2 HP_{t-1} + c_3 HP_{t-2} ]

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

Parameters

Parameter Default Description
period 20 Critical period (wavelength)

Usage Examples

Streaming (Rust)

use quantwave_core::indicators::HIGH_PASS;
use quantwave_core::traits::Next;

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

Streaming (Python)

from quantwave import HIGH_PASS

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

Polars Batch (Python)

import polars as pl
import quantwave as qw

def apply_highpass(series: pl.Series) -> pl.Series:
    ind = qw.HIGH_PASS(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_highpass, return_dtype=pl.Float64).alias("highpass")
    )
    .collect()
)

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

Edge Cases & Limitations

  • Recursive DSP filters require a warm-up period; first N bars may be unstable or raw-pass-through.
  • Designed for cyclic/mean-reverting regimes; trending markets can produce lag or drift.
  • Parameter period (or equivalent) controls cutoff — too small adds noise, too large adds lag.
  • Prefer chaining with other Ehlers tools (Roofing Filter, SuperSmoother) on noisy inputs.
  • Validated via proptests against gold-standard vectors where available.
  • No look-ahead bias; suitable for live streaming and batch feature pipelines.

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://github.com/lavs9/quantwave/blob/main/references/Ehlers%20Papers/implemented/UltimateSmoother.pdf

Implementation: quantwave-core/src/indicators/high_pass.rs (HIGH_PASS / HIGH_PASS_METADATA). Parity: quantwave-core/tests/gold_standard/high_pass.json

Provenance: Standards bulk upgrade 2026-06-25 IST — see docs/DOCUMENTATION_STANDARDS.md.