Supported Indicators

Variable Index Dynamic Average

Introduction

This indicator computes the n-period adaptive weighted moving average indicator. VIDYAi = Pricei x F x ABS(CMOi) + VIDYAi-1 x (1 - F x ABS(CMOi)) where: VIDYAi - is the value of the current period. Pricei - is the source price of the period being calculated. F = 2/(Period_EMA+1) - is a smoothing factor. ABS(CMOi) - is the absolute current value of CMO. VIDYAi-1 - is the value of the period immediately preceding the period being calculated.

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

Using VIDYA Indicator

To create an automatic indicator for VariableIndexDynamicAverage, call the VIDYAvidya helper method from the QCAlgorithm class. The VIDYAvidya method creates a VariableIndexDynamicAverage 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 VariableIndexDynamicAverageAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private VariableIndexDynamicAverage _vidya;

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

    public override void OnData(Slice data)
    {

        if (_vidya.IsReady)
        {
            // The current value of _vidya is represented by itself (_vidya)
            // or _vidya.Current.Value
            Plot("VariableIndexDynamicAverage", "vidya", _vidya);
        }
    }
}
class VariableIndexDynamicAverageAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._vidya = self.vidya(self._symbol, 20)

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

        if self._vidya.is_ready:
            # The current value of self._vidya is represented by self._vidya.current.value
            self.plot("VariableIndexDynamicAverage", "vidya", self._vidya.current.value)

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

You can manually create a VariableIndexDynamicAverage 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 VariableIndexDynamicAverageAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private VariableIndexDynamicAverage _variableindexdynamicaverage;

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

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

        if (_variableindexdynamicaverage.IsReady)
        {
            // The current value of _variableindexdynamicaverage is represented by itself (_variableindexdynamicaverage)
            // or _variableindexdynamicaverage.Current.Value
            Plot("VariableIndexDynamicAverage", "variableindexdynamicaverage", _variableindexdynamicaverage);
        }
    }
}
class VariableIndexDynamicAverageAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._variableindexdynamicaverage = VariableIndexDynamicAverage(20)

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

        if self._variableindexdynamicaverage.is_ready:
            # The current value of self._variableindexdynamicaverage is represented by self._variableindexdynamicaverage.current.value
            self.plot("VariableIndexDynamicAverage", "variableindexdynamicaverage", self._variableindexdynamicaverage.current.value)

For more information about this indicator, see its referencereference.

Visualization

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

VariableIndexDynamicAverage line plot.

Indicator History

To get the historical data of the VariableIndexDynamicAverage 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 VariableIndexDynamicAverageAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private VariableIndexDynamicAverage _vidya;

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

        var indicatorHistory = IndicatorHistory(_vidya, _symbol, 100, Resolution.Minute);
        var timeSpanIndicatorHistory = IndicatorHistory(_vidya, _symbol, TimeSpan.FromDays(10), Resolution.Minute);
        var timePeriodIndicatorHistory = IndicatorHistory(_vidya, _symbol, new DateTime(2024, 7, 1), new DateTime(2024, 7, 5), Resolution.Minute);
    }
}
class VariableIndexDynamicAverageAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self._vidya = self.vidya(self._symbol, 20)

        indicator_history = self.indicator_history(self._vidya, self._symbol, 100, Resolution.MINUTE)
        timedelta_indicator_history = self.indicator_history(self._vidya, self._symbol, timedelta(days=10), Resolution.MINUTE)
        time_period_indicator_history = self.indicator_history(self._vidya, self._symbol, datetime(2024, 7, 1), datetime(2024, 7, 5), Resolution.MINUTE)

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