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Supported Indicators

Super Trend

Introduction

Super trend indicator. Formula can be found here via the excel file: https://tradingtuitions.com/supertrend-indicator-excel-sheet-with-realtime-buy-sell-signals/

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

Using STR Indicator

To create an automatic indicators for SuperTrend, call the STR helper method from the QCAlgorithm class. The STR method creates a SuperTrend 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 SuperTrendAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._str = self.str(self._symbol, 20, 2, MovingAverageType.Wilders)

    def on_data(self, slice: Slice) -> None:
        if self._str.is_ready:
            # The current value of self._str is represented by self._str.current.value
            self.plot("SuperTrend", "str", self._str.current.value)
            # Plot all attributes of self._str
            self.plot("SuperTrend", "basic_upper_band", self._str.basic_upper_band)
            self.plot("SuperTrend", "basic_lower_band", self._str.basic_lower_band)
            self.plot("SuperTrend", "current_trailing_upper_band", self._str.current_trailing_upper_band)
            self.plot("SuperTrend", "current_trailing_lower_band", self._str.current_trailing_lower_band)

The following reference table describes the STR method:

str(symbol, period, multiplier, moving_average_type=2, resolution=None, selector=None)[source]

Creates a new SuperTrend indicator.

Parameters:
  • symbol (Symbol) — The symbol whose SuperTrend indicator we want.
  • period (int) — The smoothing period for average true range.
  • multiplier (float) — Multiplier to calculate basic upper and lower bands width.
  • moving_average_type (MovingAverageType, optional) — Smoother type for average true range, defaults to Wilders.
  • resolution (Resolution, optional) — The resolution.
  • selector (Callable[IBaseData, IBaseDataBar], optional) — Selects a value from the BaseData to send into the indicator, if null defaults to casting the input value to a TradeBar
Return type:

SuperTrend

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 SuperTrend 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 SuperTrendAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._str = SuperTrend(20, 2, MovingAverageType.Wilders)

    def on_data(self, slice: Slice) -> None:
        bar = slice.bars.get(self._symbol)
        if bar:
            self._str.update(bar)
        if self._str.is_ready:
            # The current value of self._str is represented by self._str.current.value
            self.plot("SuperTrend", "str", self._str.current.value)
            # Plot all attributes of self._str
            self.plot("SuperTrend", "basic_upper_band", self._str.basic_upper_band)
            self.plot("SuperTrend", "basic_lower_band", self._str.basic_lower_band)
            self.plot("SuperTrend", "current_trailing_upper_band", self._str.current_trailing_upper_band)
            self.plot("SuperTrend", "current_trailing_lower_band", self._str.current_trailing_lower_band)

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

Select Language: 
class SuperTrendAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._str = SuperTrend(20, 2, MovingAverageType.Wilders)
        self.register_indicator(self._symbol, self._str, Resolution.DAILY)

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

The following reference table describes the SuperTrend constructor:

SuperTrend

class QuantConnect.Indicators.SuperTrend[source]

Super trend indicator. Formula can be found here via the excel file: https://tradingtuitions.com/supertrend-indicator-excel-sheet-with-realtime-buy-sell-signals/

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 basic_lower_band

Basic Lower band

Returns:

Basic Lower band

Return type:

float

property basic_upper_band

Basic Upper Band

Returns:

Basic Upper Band

Return type:

float

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 current_trailing_lower_band

Current Trailing Lower Band

Returns:

Current Trailing Lower Band

Return type:

float

property current_trailing_upper_band

Current Trailing Upper Band

Returns:

Current Trailing Upper Band

Return type:

float

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

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 SuperTrend using the plotly library.

SuperTrend line plot.

Indicator History

To get the historical data of the SuperTrend 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 SuperTrendAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        str = self.str(self._symbol, 20, 2, MovingAverageType.Wilders)
        count_indicator_history = self.indicator_history(str, self._symbol, 100, Resolution.MINUTE)
        timedelta_indicator_history = self.indicator_history(str, self._symbol, timedelta(days=10), Resolution.MINUTE)
        time_period_indicator_history = self.indicator_history(str, 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(str, 100, Resolution.MINUTE, lambda bar: bar.high)
indicator_history_df = indicator_history.data_frame

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