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Roc

ROC

Bases: IndicatorBase

Rate of Change (ROC) indicator.

Computes the percentage change between the current value and the value \(n\) periods ago: ROC = ((current - previous) / previous) * 100

The rolling window is maintained independently for each symbol. Until the window is fully populated, the indicator yields numpy.nan.

name property

Canonical indicator name.

Returns:

Type Description
str

Stable identifier for the ROC indicator.
Source code in src/onesecondtrader/indicators/oscillators/roc.py 
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def name(self) -> str:
    """
    Canonical indicator name.

    Returns:
        Stable identifier for the ROC indicator.
    """
    return f"ROC({self.period})"

__init__(period=14, max_history=100, bar_field=models.BarField.CLOSE, plot_at=99, plot_as=models.PlotStyle.LINE, plot_color=models.PlotColor.BLACK)

Parameters:

Name Type Description Default
period int

Number of periods to look back for the rate of change calculation.

 14
max_history int

Maximum number of computed indicator values retained per symbol.

 100
bar_field BarField

Bar field used as the input series.

 CLOSE
plot_at int

Opaque plotting identifier forwarded to the charting backend.

 99
plot_as PlotStyle

Visual style used to render the indicator.

 LINE
plot_color PlotColor

Color used to render the indicator.

 BLACK
Source code in src/onesecondtrader/indicators/oscillators/roc.py 
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def __init__(
    self,
    period: int = 14,
    max_history: int = 100,
    bar_field: models.BarField = models.BarField.CLOSE,
    plot_at: int = 99,
    plot_as: models.PlotStyle = models.PlotStyle.LINE,
    plot_color: models.PlotColor = models.PlotColor.BLACK,
) -> None:
    """
    Parameters:
        period:
            Number of periods to look back for the rate of change calculation.
        max_history:
            Maximum number of computed indicator values retained per symbol.
        bar_field:
            Bar field used as the input series.
        plot_at:
            Opaque plotting identifier forwarded to the charting backend.
        plot_as:
            Visual style used to render the indicator.
        plot_color:
            Color used to render the indicator.
    """
    super().__init__(
        max_history=max_history,
        plot_at=plot_at,
        plot_as=plot_as,
        plot_color=plot_color,
    )

    self.period: int = max(1, int(period))
    self.bar_field: models.BarField = bar_field
    self._window: dict[str, collections.deque[float]] = {}

_compute_indicator(incoming_bar)

Compute the rate of change for a single received bar.

Parameters:

Name Type Description Default
incoming_bar BarReceived

Market bar used as input for the computation.

 required

Returns:

Type Description
float

Rate of change value as a percentage, or numpy.nan if the rolling window is not yet fully populated.
Source code in src/onesecondtrader/indicators/oscillators/roc.py 
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def _compute_indicator(self, incoming_bar: events.market.BarReceived) -> float:
    """
    Compute the rate of change for a single received bar.

    Parameters:
        incoming_bar:
            Market bar used as input for the computation.

    Returns:
        Rate of change value as a percentage, or `numpy.nan` if the rolling window is not yet fully populated.
    """
    symbol = incoming_bar.symbol
    if symbol not in self._window:
        self._window[symbol] = collections.deque(maxlen=self.period + 1)

    window = self._window[symbol]
    value = self._extract_field(incoming_bar)
    window.append(value)

    if len(window) < self.period + 1:
        return np.nan

    previous = window[0]
    if previous == 0:
        return np.nan

    return ((value - previous) / previous) * 100

_extract_field(incoming_bar)

Extract the configured bar field from an incoming bar.

Parameters:

Name Type Description Default
incoming_bar BarReceived

Market bar providing the input data.

 required

Returns:

Type Description
float

Extracted field value, or numpy.nan if unavailable.
Source code in src/onesecondtrader/indicators/oscillators/roc.py 
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def _extract_field(self, incoming_bar: events.market.BarReceived) -> float:
    """
    Extract the configured bar field from an incoming bar.

    Parameters:
        incoming_bar:
            Market bar providing the input data.

    Returns:
        Extracted field value, or `numpy.nan` if unavailable.
    """
    match self.bar_field:
        case models.BarField.OPEN:
            return incoming_bar.open
        case models.BarField.HIGH:
            return incoming_bar.high
        case models.BarField.LOW:
            return incoming_bar.low
        case models.BarField.CLOSE:
            return incoming_bar.close
        case models.BarField.VOLUME:
            return (
                float(incoming_bar.volume)
                if incoming_bar.volume is not None
                else np.nan
            )
        case _:
            return incoming_bar.close