Supported Indicators

Variance

Introduction

This indicator computes the n-period population variance.

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

Using VAR Indicator

To create an automatic indicators for Variance, call the VAR helper method from the QCAlgorithm class. The VAR method creates a Variance 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.

public class VarianceAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private Variance _var;

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

    public override void OnData(Slice data)
    {
        if (_var.IsReady)
        {
            // The current value of _var is represented by itself (_var)
            // or _var.Current.Value
            Plot("Variance", "var", _var);
            
        }
    }
}
class VarianceAlgorithm(QCAlgorithm):
    def Initialize(self) -> None:
        self.symbol = self.AddEquity("SPY", Resolution.Daily).Symbol
        self.var = self.VAR(self.symbol, 20)

    def OnData(self, slice: Slice) -> None:
        if self.var.IsReady:
            # The current value of self.var is represented by self.var.Current.Value
            self.Plot("Variance", "var", self.var.Current.Value)
            

The following reference table describes the VAR method:

VAR()1/1

            Variance QuantConnect.Algorithm.QCAlgorithm.VAR (
    Symbol                           symbol,
    Int32                            period,
    *Nullable<Resolution>      resolution,
    *Func<IBaseData, Decimal>  selector
   )
        

Creates a new Variance indicator. This will return the population variance of samples over the specified period.

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 Variance 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.

public class VarianceAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private Variance _var;

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

    public override void OnData(Slice data)
    {
        if (data.Bars.TryGetValue(_symbol, out var bar))
        {      
            _var.Update(bar.EndTime, bar.Close);
        }
    
        if (_var.IsReady)
        {
            // The current value of _var is represented by itself (_var)
            // or _var.Current.Value
            Plot("Variance", "var", _var);
            
        }
    }
}
class VarianceAlgorithm(QCAlgorithm):
    def Initialize(self) -> None:
        self.symbol = self.AddEquity("SPY", Resolution.Daily).Symbol
        self.var = Variance(20)

    def OnData(self, slice: Slice) -> None:
        bar = slice.Bars.get(self.symbol)
        if bar:
            self.var.Update(bar.EndTime, bar.Close)
                
        if self.var.IsReady:
            # The current value of self.var is represented by self.var.Current.Value
            self.Plot("Variance", "var", self.var.Current.Value)
            

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

public class VarianceAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private Variance _var;

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

    public override void OnData(Slice data)
    {
        if (_var.IsReady)
        {
            // The current value of _var is represented by itself (_var)
            // or _var.Current.Value
            Plot("Variance", "var", _var);
            
        }
    }
}
class VarianceAlgorithm(QCAlgorithm):
    def Initialize(self) -> None:
        self.symbol = self.AddEquity("SPY", Resolution.Daily).Symbol
        self.var = Variance(20)
        self.RegisterIndicator(self.symbol, self.var, Resolution.Daily)

    def OnData(self, slice: Slice) -> None:
        if self.var.IsReady:
            # The current value of self.var is represented by self.var.Current.Value
            self.Plot("Variance", "var", self.var.Current.Value)
            

The following reference table describes the Variance constructor:

Variance()1/2

            Variance QuantConnect.Indicators.Variance (
    int  period
   )
        

Initializes a new instance of the Variance class using the specified period.

Variance()2/2

            Variance QuantConnect.Indicators.Variance (
    string  name,
    int     period
   )
        

Initializes a new instance of the Variance class using the specified name and period.

Visualization

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

Variance line plot.

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