Cycle

Cycle Indicators — Hilbert Transform-based cycle analysis.

All functions use a 63-bar lookback period (first 63 values are NaN).

Functions

HT_TRENDLINE — Hilbert Transform - Instantaneous Trendline HT_DCPERIOD — Hilbert Transform - Dominant Cycle Period HT_DCPHASE — Hilbert Transform - Dominant Cycle Phase HT_PHASOR — Hilbert Transform - Phasor Components (returns inphase, quadrature) HT_SINE — Hilbert Transform - SineWave (returns sine, leadsine) HT_TRENDMODE — Hilbert Transform - Trend vs Cycle Mode (1=trend, 0=cycle)

ferro_ta.cycle.HT_DCPERIOD(close)[source]

Hilbert Transform - Dominant Cycle Period.

Estimates the current dominant cycle period in bars using the Hilbert Transform. Values are smoothed and clamped to [6, 50].

Parameters:: close (array-like) – Sequence of closing prices.
Returns:: Dominant cycle period values; first 63 entries are NaN.
Return type:: numpy.ndarray

ferro_ta.cycle.HT_DCPHASE(close)[source]

Hilbert Transform - Dominant Cycle Phase.

Returns the instantaneous phase (in degrees) of the dominant cycle.

Parameters:: close (array-like) – Sequence of closing prices.
Returns:: Phase values in degrees; first 63 entries are NaN.
Return type:: numpy.ndarray

ferro_ta.cycle.HT_PHASOR(close)[source]

Hilbert Transform - Phasor Components.

Returns the In-Phase (I) and Quadrature (Q) components of the Hilbert Transform. These represent the real and imaginary parts of the analytic signal derived from the price series.

Parameters:: close (array-like) – Sequence of closing prices.
Returns:: (inphase, quadrature) — two arrays; first 63 entries are NaN.
Return type:: tuple[numpy.ndarray, numpy.ndarray]

ferro_ta.cycle.HT_SINE(close)[source]

Hilbert Transform - SineWave.

Returns the sine and lead-sine (45-degree lead) of the dominant cycle phase. Used to detect cycle turning points.

Parameters:: close (array-like) – Sequence of closing prices.
Returns:: (sine, leadsine) — two arrays; first 63 entries are NaN.
Return type:: tuple[numpy.ndarray, numpy.ndarray]

ferro_ta.cycle.HT_TRENDLINE(close)[source]

Hilbert Transform - Instantaneous Trendline.

Computes the underlying trend of the price series using the Hilbert Transform. The trendline is the dominant-cycle-period average of the smoothed price.

Parameters:: close (array-like) – Sequence of closing prices.
Returns:: Trendline values; first 63 entries are NaN.
Return type:: numpy.ndarray

ferro_ta.cycle.HT_TRENDMODE(close)[source]

Hilbert Transform - Trend vs Cycle Mode.

Returns 1 when the market is in a trending mode (dominant cycle period below 20 bars) and 0 when in a cycling mode.

Parameters:: close (array-like) – Sequence of closing prices.
Returns:: Array of 1 (trending) or 0 (cycling).
Return type:: numpy.ndarray[int32]