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CorrelationCycle

Ehlers DSP cycle dominant-cycle ehlers dsp spectral

Determines cycle phase angle by correlating price with orthogonal sinusoids.

Visual Example

CorrelationCycle — 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 CorrelationCycle indicator is a technical analysis tool that determines cycle phase angle by correlating price with orthogonal sinusoids.

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 to measure the dominant cycle period via autocorrelation in an amplitude-independent way. Prefer over DFT methods when price amplitude varies significantly across the measurement window.

Ehlers introduces Correlation Cycle measurement in Cycle Analytics for Traders (2013) as an improvement on DFT. By normalizing autocorrelation coefficients to unity variance, the resulting periodogram is independent of price amplitude variations, producing more consistent cycle period estimates.

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/correlation_cycle.rs):

[ R = \text{Corr}(Price, \cos(2\pi n/P)), I = \text{Corr}(Price, -\sin(2\pi n/P)) ] [ \text{Angle} = 90 + \arctan(R/I) \text{ (with quadrant resolution)} ]

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

Parameters

Parameter Default Description
period 20 Correlation wavelength

Usage Examples

Streaming (Rust)

use quantwave_core::indicators::CORRELATION_CYCLE;
use quantwave_core::traits::Next;

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

Streaming (Python)

from quantwave import CORRELATION_CYCLE

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

Polars Batch (Python)

import polars as pl
import quantwave as qw

def apply_correlationcycle(series: pl.Series) -> pl.Series:
    ind = qw.CORRELATION_CYCLE(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_correlationcycle, return_dtype=pl.Float64).alias("correlationcycle")
    )
    .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/CORRELATION%20AS%20A%20CYCLE%20INDICATOR.pdf

Implementation: quantwave-core/src/indicators/correlation_cycle.rs (CORRELATION_CYCLE / CORRELATION_CYCLE_METADATA). Parity: quantwave-core/tests/gold_standard/correlation_cycle.json

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