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Hilbert Transform - Trend vs. Cycle Mode (HT_TRENDMODE)

Ehlers DSP cycle trend hilbert regime-detection dsp

A binary indicator that determines if the market is currently in a trending state (1) or a cyclical state (0).

Visual Example

Hilbert Transform - Trend vs. Cycle Mode (HT_TRENDMODE) — 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 Hilbert Transform - Trend vs. Cycle Mode (HT_TRENDMODE) indicator is a technical analysis tool that a binary indicator that determines if the market is currently in a trending state (1) or a cyclical state (0).

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 master filter for strategy selection. Deploy trend-following tools when TRENDMODE is 1, and mean-reversion tools when TRENDMODE is 0.

Determining the current market regime is the 'holy grail' of technical analysis. The HT_TRENDMODE indicator uses the rate of change of the dominant cycle phase to distinguish between trending and ranging price action, allowing traders to avoid 'whipsaws' in non-conducive environments. — Rocket Science for Traders

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/cycle.rs):

\[ \text{TRENDMODE} = \begin{cases} 1 & \text{if trend detected} \\ 0 & \text{if cycle detected} \end{cases} \]

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

Parameters

Parameter Default Description
(none) — No tunable parameters for this detector.

Usage Examples

Streaming (Rust)

use quantwave_core::indicators::HT_TRENDMODE;
use quantwave_core::traits::Next;

let mut ind = HT_TRENDMODE::new(14);
for price in &prices {
    let value = ind.next(price);
}

Streaming (Python)

from quantwave import HT_TRENDMODE

ind = HT_TRENDMODE(14)
for price in prices:
    value = ind.next(price)

Polars Batch (Python)

import polars as pl

df = (
    pl.read_csv('ohlcv.csv')
    .lazy()
    .with_columns(
        pl.col("close").ta.ht_trendmode(14).alias("hilbert_transform_trend_vs_cycle_mode_ht_trendmode")
    )
    .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://www.tradingview.com/support/solutions/43000502014-hilbert-transform-trend-vs-cycle-mode-ht-trendmode/

Implementation: quantwave-core/src/indicators/cycle.rs (HT_TRENDMODE / HT_TRENDMODE_METADATA). Parity: quantwave-core/tests/gold_standard/ht_trendmode.json

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