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Supported Indicators

Absolute Price Oscillator

Introduction

This indicator computes the Absolute Price Oscillator (APO) The Absolute Price Oscillator is calculated using the following formula: APO[i] = FastMA[i] - SlowMA[i]

To view the implementation of this indicator, see the LEAN GitHub repository.

Using APO Indicator

To create an automatic indicators for AbsolutePriceOscillator, call the APO helper method from the QCAlgorithm class. The APO method creates a AbsolutePriceOscillator object, hooks it up for automatic updates, and returns it so you can used it in your algorithm. In most cases, you should call the helper method in the initialize method.

Select Language: 
class AbsolutePriceOscillatorAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._apo = self.apo(self._symbol, 10, 2, MovingAverageType.Simple)

    def on_data(self, slice: Slice) -> None:
        if self._apo.is_ready:
            # The current value of self._apo is represented by self._apo.current.value
            self.plot("AbsolutePriceOscillator", "apo", self._apo.current.value)
            # Plot all attributes of self._apo
            self.plot("AbsolutePriceOscillator", "fast", self._apo.fast.current.value)
            self.plot("AbsolutePriceOscillator", "slow", self._apo.slow.current.value)
            self.plot("AbsolutePriceOscillator", "signal", self._apo.signal.current.value)
            self.plot("AbsolutePriceOscillator", "histogram", self._apo.histogram.current.value)

The following reference table describes the APO method:

apo(symbol, fast_period, slow_period, moving_average_type, resolution=None, selector=None)[source]

Creates a new AbsolutePriceOscillator indicator.

Parameters:
  • symbol (Symbol) — The symbol whose APO we want
  • fast_period (int) — The fast moving average period
  • slow_period (int) — The slow moving average period
  • moving_average_type (MovingAverageType) — The type of moving average to use
  • resolution (Resolution, optional) — The resolution
  • selector (Callable[IBaseData, float], optional) — x.Value)
Returns:

The AbsolutePriceOscillator indicator for the requested symbol over the specified period

Return type:

AbsolutePriceOscillator

If you don't provide a resolution, it defaults to the security resolution. If you provide a resolution, it must be greater than or equal to the resolution of the security. For instance, if you subscribe to hourly data for a security, you should update its indicator with data that spans 1 hour or longer.

For more information about the selector argument, see Alternative Price Fields.

For more information about plotting indicators, see Plotting Indicators.

You can manually create a AbsolutePriceOscillator indicator, so it doesn't automatically update. Manual indicators let you update their values with any data you choose.

Updating your indicator manually enables you to control when the indicator is updated and what data you use to update it. To manually update the indicator, call the update method with time/number pair or an IndicatorDataPoint. The indicator will only be ready after you prime it with enough data.

Select Language: 
class AbsolutePriceOscillatorAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._apo = AbsolutePriceOscillator(10, 20, MovingAverageType.Simple)

    def on_data(self, slice: Slice) -> None:
        bar = slice.bars.get(self._symbol)
        if bar:
            self._apo.update(bar.EndTime, bar.Close)
        if self._apo.is_ready:
            # The current value of self._apo is represented by self._apo.current.value
            self.plot("AbsolutePriceOscillator", "apo", self._apo.current.value)
            # Plot all attributes of self._apo
            self.plot("AbsolutePriceOscillator", "fast", self._apo.fast.current.value)
            self.plot("AbsolutePriceOscillator", "slow", self._apo.slow.current.value)
            self.plot("AbsolutePriceOscillator", "signal", self._apo.signal.current.value)
            self.plot("AbsolutePriceOscillator", "histogram", self._apo.histogram.current.value)

To register a manual indicator for automatic updates with the security data, call the register_indicator method.

Select Language: 
class AbsolutePriceOscillatorAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._apo = AbsolutePriceOscillator(10, 20, MovingAverageType.Simple)
        self.register_indicator(self._symbol, self._apo, Resolution.DAILY)

    def on_data(self, slice: Slice) -> None:
        if self._apo.is_ready:
            # The current value of self._apo is represented by self._apo.current.value
            self.plot("AbsolutePriceOscillator", "apo", self._apo.current.value)
            # Plot all attributes of self._apo
            self.plot("AbsolutePriceOscillator", "fast", self._apo.fast.current.value)
            self.plot("AbsolutePriceOscillator", "slow", self._apo.slow.current.value)
            self.plot("AbsolutePriceOscillator", "signal", self._apo.signal.current.value)
            self.plot("AbsolutePriceOscillator", "histogram", self._apo.histogram.current.value)

The following reference table describes the AbsolutePriceOscillator constructor:

AbsolutePriceOscillator

class QuantConnect.Indicators.AbsolutePriceOscillator[source]

This indicator computes the Absolute Price Oscillator (APO) The Absolute Price Oscillator is calculated using the following formula: APO[i] = FastMA[i] - SlowMA[i]

get_enumerator()

Returns an enumerator that iterates through the history window.

Return type:

IEnumerator[IndicatorDataPoint]

reset()

Resets this indicator to its initial state

to_detailed_string()

Provides a more detailed string of this indicator in the form of {Name} - {Value}

Return type:

str

update(time, value)

Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise

Parameters:
  • time (datetime)
  • value (float)
Return type:

bool

update(input)

Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise

Parameters:
  • input (IBaseData)
Return type:

bool

property consolidators

The data consolidators associated with this indicator if any

Returns:

The data consolidators associated with this indicator if any

Return type:

ISet[IDataConsolidator]

property current

Gets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Returns:

Gets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Return type:

IndicatorDataPoint

property fast

Gets the fast average indicator

Returns:

Gets the fast average indicator

Return type:

IndicatorBase[IndicatorDataPoint]

property histogram

Developed by Thomas Aspray in 1986, the MACD-Histogram measures the distance between MACD and its signal line, is an oscillator that fluctuates above and below the zero line. Bullish or bearish divergences in the MACD-Histogram can alert chartists to an imminent signal line crossover in MACD.

Returns:

Developed by Thomas Aspray in 1986, the MACD-Histogram measures the distance between MACD and its signal line, is an oscillator that fluctuates above and below the zero line. Bullish or bearish divergences in the MACD-Histogram can alert chartists to an imminent signal line crossover in MACD.

Return type:

IndicatorBase[IndicatorDataPoint]

property is_ready

Gets a flag indicating when this indicator is ready and fully initialized

Returns:

Gets a flag indicating when this indicator is ready and fully initialized

Return type:

bool

property item

Indexes the history windows, where index 0 is the most recent indicator value. If index is greater or equal than the current count, it returns null. If the index is greater or equal than the window size, it returns null and resizes the windows to i + 1.

Returns:

Indexes the history windows, where index 0 is the most recent indicator value. If index is greater or equal than the current count, it returns null. If the index is greater or equal than the window size, it returns null and resizes the windows to i + 1.

Return type:

IndicatorDataPoint

property name

Gets a name for this indicator

Returns:

Gets a name for this indicator

Return type:

str

property previous

Gets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Returns:

Gets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Return type:

IndicatorDataPoint

property samples

Gets the number of samples processed by this indicator

Returns:

Gets the number of samples processed by this indicator

Return type:

int

property signal

Gets the signal of the MACD

Returns:

Gets the signal of the MACD

Return type:

IndicatorBase[IndicatorDataPoint]

property slow

Gets the slow average indicator

Returns:

Gets the slow average indicator

Return type:

IndicatorBase[IndicatorDataPoint]

property warm_up_period

Required period, in data points, for the indicator to be ready and fully initialized.

Returns:

Required period, in data points, for the indicator to be ready and fully initialized.

Return type:

int

property window

A rolling window keeping a history of the indicator values of a given period

Returns:

A rolling window keeping a history of the indicator values of a given period

Return type:

RollingWindow[IndicatorDataPoint]

Visualization

The following image shows plot values of selected properties of AbsolutePriceOscillator using the plotly library.

AbsolutePriceOscillator line plot.

Indicator History

To get the historical data of the AbsolutePriceOscillator indicator, call the self.indicator_history method. This method resets your indicator, makes a history request, and updates the indicator with the historical data. Just like with regular history requests, the indicator_history method supports time periods based on a trailing number of bars, a trailing period of time, or a defined period of time. If you don't provide a resolution argument, it defaults to match the resolution of the security subscription.

Select Language: 
class AbsolutePriceOscillatorAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        apo = self.apo(self._symbol, 10, 2, MovingAverageType.Simple)
        count_indicator_history = self.indicator_history(apo, self._symbol, 100, Resolution.MINUTE)
        timedelta_indicator_history = self.indicator_history(apo, self._symbol, timedelta(days=10), Resolution.MINUTE)
        time_period_indicator_history = self.indicator_history(apo, self._symbol, datetime(2024, 7, 1), datetime(2024, 7, 5), Resolution.MINUTE)

To make the indicator_history method update the indicator with an alternative price field instead of the close (or mid-price) of each bar, pass a selector argument.

Select Language: 
indicator_history = self.indicator_history(apo, 100, Resolution.MINUTE, lambda bar: bar.high)
indicator_history_df = indicator_history.data_frame

To access the properties of the indicator history, index the DataFrame with the property name.

Select Language: 
fast = indicator_history_df["fast"]
slow = indicator_history_df["slow"]
signal = indicator_history_df["signal"]
histogram = indicator_history_df["histogram"]

# Alternative way
# fast = indicator_history_df.fast
# slow = indicator_history_df.slow
# signal = indicator_history_df.signal
# histogram = indicator_history_df.histogram

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