Supported Indicators

Average Directional Index

Introduction

This indicator computes Average Directional Index which measures trend strength without regard to trend direction. Firstly, it calculates the Directional Movement and the True Range value, and then the values are accumulated and smoothed using a custom smoothing method proposed by Wilder. For an n period smoothing, 1/n of each period's value is added to the total period. From these accumulated values we are therefore able to derived the 'Positive Directional Index' (+DI) and 'Negative Directional Index' (-DI) which is used to calculate the Average Directional Index. Computation source: https://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:average_directional_index_adx

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

Using ADX Indicator

To create an automatic indicator for AverageDirectionalIndex, call the ADXadx helper method from the QCAlgorithm class. The ADXadx method creates a AverageDirectionalIndex 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 Initializeinitialize method.

public class AverageDirectionalIndexAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private AverageDirectionalIndex _adx;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _adx = ADX(_symbol, 20);
    }

    public override void OnData(Slice data)
    {

        if (_adx.IsReady)
        {
            // The current value of _adx is represented by itself (_adx)
            // or _adx.Current.Value
            Plot("AverageDirectionalIndex", "adx", _adx);
            // Plot all properties of abands
            Plot("AverageDirectionalIndex", "positivedirectionalindex", _adx.PositiveDirectionalIndex);
            Plot("AverageDirectionalIndex", "negativedirectionalindex", _adx.NegativeDirectionalIndex);
        }
    }
}
class AverageDirectionalIndexAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._adx = self.adx(self._symbol, 20)

    def on_data(self, slice: Slice) -> None:

        if self._adx.is_ready:
            # The current value of self._adx is represented by self._adx.current.value
            self.plot("AverageDirectionalIndex", "adx", self._adx.current.value)
            # Plot all attributes of self._adx
            self.plot("AverageDirectionalIndex", "positive_directional_index", self._adx.positive_directional_index.current.value)
            self.plot("AverageDirectionalIndex", "negative_directional_index", self._adx.negative_directional_index.current.value)

For more information about this method, see the QCAlgorithm classQCAlgorithm class.

You can manually create a AverageDirectionalIndex 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 Updateupdate method. The indicator will only be ready after you prime it with enough data.

public class AverageDirectionalIndexAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private AverageDirectionalIndex _averagedirectionalindex;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _averagedirectionalindex = new AverageDirectionalIndex(20);
    }

    public override void OnData(Slice data)
    {
        if (data.Bars.TryGetValue(_symbol, out var bar))
            _averagedirectionalindex.Update(bar);

        if (_averagedirectionalindex.IsReady)
        {
            // The current value of _averagedirectionalindex is represented by itself (_averagedirectionalindex)
            // or _averagedirectionalindex.Current.Value
            Plot("AverageDirectionalIndex", "averagedirectionalindex", _averagedirectionalindex);
            // Plot all properties of abands
            Plot("AverageDirectionalIndex", "positivedirectionalindex", _averagedirectionalindex.PositiveDirectionalIndex);
            Plot("AverageDirectionalIndex", "negativedirectionalindex", _averagedirectionalindex.NegativeDirectionalIndex);
        }
    }
}
class AverageDirectionalIndexAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._averagedirectionalindex = AverageDirectionalIndex(20)

    def on_data(self, slice: Slice) -> None:
        bar = slice.bars.get(self._symbol)
        if bar:
            self._averagedirectionalindex.update(bar)

        if self._averagedirectionalindex.is_ready:
            # The current value of self._averagedirectionalindex is represented by self._averagedirectionalindex.current.value
            self.plot("AverageDirectionalIndex", "averagedirectionalindex", self._averagedirectionalindex.current.value)
            # Plot all attributes of self._averagedirectionalindex
            self.plot("AverageDirectionalIndex", "positive_directional_index", self._averagedirectionalindex.positive_directional_index.current.value)
            self.plot("AverageDirectionalIndex", "negative_directional_index", self._averagedirectionalindex.negative_directional_index.current.value)

For more information about this indicator, see its referencereference.

Visualization

The following plot shows values for some of the AverageDirectionalIndex indicator properties:

AverageDirectionalIndex line plot.

Indicator History

To get the historical data of the AverageDirectionalIndex indicator, call the IndicatorHistoryself.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 IndicatorHistoryindicator_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. 

public class AverageDirectionalIndexAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private AverageDirectionalIndex _adx;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _adx = ADX(_symbol, 20);

        var indicatorHistory = IndicatorHistory(_adx, _symbol, 100, Resolution.Minute);
        var timeSpanIndicatorHistory = IndicatorHistory(_adx, _symbol, TimeSpan.FromDays(10), Resolution.Minute);
        var timePeriodIndicatorHistory = IndicatorHistory(_adx, _symbol, new DateTime(2024, 7, 1), new DateTime(2024, 7, 5), Resolution.Minute);

        // Access all attributes of indicatorHistory
        var positiveDirectionalIndex = indicatorHistory.Select(x => ((dynamic)x).PositiveDirectionalIndex).ToList();
        var negativeDirectionalIndex = indicatorHistory.Select(x => ((dynamic)x).NegativeDirectionalIndex).ToList();
    }
}
class AverageDirectionalIndexAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._adx = self.adx(self._symbol, 20)

        indicator_history = self.indicator_history(self._adx, self._symbol, 100, Resolution.MINUTE)
        timedelta_indicator_history = self.indicator_history(self._adx, self._symbol, timedelta(days=10), Resolution.MINUTE)
        time_period_indicator_history = self.indicator_history(self._adx, self._symbol, datetime(2024, 7, 1), datetime(2024, 7, 5), Resolution.MINUTE)
    
        # Access all attributes of indicator_history
        indicator_history_df = indicator_history.data_frame
        positive_directional_index = indicator_history_df["positivedirectionalindex"]
        negative_directional_index = indicator_history_df["negativedirectionalindex"]

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