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Swiss Army Knife Indicator

Ehlers DSP filter ehlers dsp multi-purpose smoothing

A versatile indicator that can be configured as EMA, SMA, Gaussian, Butterworth, High Pass, Band Pass, or Band Stop filter.

Visual Example

Swiss Army Knife Indicator — 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 Swiss Army Knife Indicator indicator is a technical analysis tool that a versatile indicator that can be configured as ema, sma, gaussian, butterworth, high pass, band pass, or band stop filter.

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.

Use as a single configurable filter that can emulate SMA, EMA, Gaussian, Butterworth, or bandpass responses by switching mode flags. Ideal for prototyping different filter designs without code changes.

Ehlers presents the Swiss Army Knife Indicator in Cycle Analytics for Traders as a unified filter framework. A set of boolean flags selects the operating mode, making it possible to compare multiple filter responses on the same data by simply toggling flags rather than reimplementing each filter.

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/swiss_army_knife.rs):

\[ Filt = c_0(b_0 x_t + b_1 x_{t-1} + b_2 x_{t-2}) + a_1 Filt_{t-1} + a_2 Filt_{t-2} - c_1 x_{t-N} \]

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

Parameters

Parameter Default Description
mode BandPass Filter mode (EMA, SMA, Gauss, Butter, Smooth, HP, 2PHP, BP, BS)
period 20 Filter period
delta 0.1 Bandwidth parameter for BP and BS modes

Usage Examples

Streaming (Rust)

use quantwave_core::indicators::SWISS_ARMY_KNIFE;
use quantwave_core::traits::Next;

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

Streaming (Python)

from quantwave import SWISS_ARMY_KNIFE

ind = SWISS_ARMY_KNIFE(BandPass)
for price in prices:
    value = ind.next(price)

Polars Batch (Python)

import polars as pl
import quantwave as qw

def apply_swiss_army_knife_indicator(series: pl.Series) -> pl.Series:
    ind = qw.SWISS_ARMY_KNIFE(BandPass)
    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_swiss_army_knife_indicator, return_dtype=pl.Float64).alias("swiss_army_knife_indicator")
    )
    .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/SwissArmyKnifeIndicator.pdf

Implementation: quantwave-core/src/indicators/swiss_army_knife.rs (SWISS_ARMY_KNIFE / SWISS_ARMY_KNIFE_METADATA). Parity: quantwave-core/tests/gold_standard/swiss_army_knife.json

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