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Supported Indicators

Premier Stochastic Oscillator

Introduction

Premier Stochastic Oscillator (PSO) Indicator implementation. This indicator combines a stochastic oscillator with exponential moving averages to provide a normalized output between -1 and 1, which can be useful for identifying trends and potential reversal points in the market.

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

Using PremierStochasticOscillator Indicator

To create an automatic indicators for PremierStochasticOscillator, call the PremierStochasticOscillator helper method from the QCAlgorithm class. The PremierStochasticOscillator method creates a PremierStochasticOscillator 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 PremierStochasticOscillatorAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._premier_stochastic_oscillator = self.premier_stochastic_oscillator(self._symbol)

    def on_data(self, slice: Slice) -> None:
        if self._premier_stochastic_oscillator.is_ready:
            # The current value of self._premier_stochastic_oscillator is represented by self._premier_stochastic_oscillator.current.value
            self.plot("PremierStochasticOscillator", "premier_stochastic_oscillator", self._premier_stochastic_oscillator.current.value)

The following reference table describes the PremierStochasticOscillator method:

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 PremierStochasticOscillator 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 a TradeBar or QuoteBar. The indicator will only be ready after you prime it with enough data.

Select Language: 
class PremierStochasticOscillatorAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._premier_stochastic_oscillator = PremierStochasticOscillator()

    def on_data(self, slice: Slice) -> None:
        bar = slice.bars.get(self._symbol)
        if bar:
            self._premier_stochastic_oscillator.update(bar)
        if self._premier_stochastic_oscillator.is_ready:
            # The current value of self._premier_stochastic_oscillator is represented by self._premier_stochastic_oscillator.current.value
            self.plot("PremierStochasticOscillator", "premier_stochastic_oscillator", self._premier_stochastic_oscillator.current.value)

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

Select Language: 
class PremierStochasticOscillatorAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._premier_stochastic_oscillator = PremierStochasticOscillator()
        self.register_indicator(self._symbol, self._premier_stochastic_oscillator, Resolution.DAILY)

    def on_data(self, slice: Slice) -> None:
        if self._premier_stochastic_oscillator.is_ready:
            # The current value of self._premier_stochastic_oscillator is represented by self._premier_stochastic_oscillator.current.value
            self.plot("PremierStochasticOscillator", "premier_stochastic_oscillator", self._premier_stochastic_oscillator.current.value)

The following reference table describes the PremierStochasticOscillator constructor:

PremierStochasticOscillator

class QuantConnect.Indicators.PremierStochasticOscillator[source]

Premier Stochastic Oscillator (PSO) Indicator implementation. This indicator combines a stochastic oscillator with exponential moving averages to provide a normalized output between -1 and 1, which can be useful for identifying trends and potential reversal points in the market.

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 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 warm_up_period

The warm-up period necessary before the PSO indicator is considered ready.

Returns:

The warm-up period necessary before the PSO indicator is considered ready.

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 PremierStochasticOscillator using the plotly library.

PremierStochasticOscillator line plot.

Indicator History

To get the historical data of the PremierStochasticOscillator 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 PremierStochasticOscillatorAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        premier_stochastic_oscillator = self.premier_stochastic_oscillator(self._symbol)
        count_indicator_history = self.indicator_history(premier_stochastic_oscillator, self._symbol, 100, Resolution.MINUTE)
        timedelta_indicator_history = self.indicator_history(premier_stochastic_oscillator, self._symbol, timedelta(days=10), Resolution.MINUTE)
        time_period_indicator_history = self.indicator_history(premier_stochastic_oscillator, 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(premier_stochastic_oscillator, 100, Resolution.MINUTE, lambda bar: bar.high)
indicator_history_df = indicator_history.data_frame

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