Supported Indicators
Variance
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("SPY", 20); } public override void OnData(Slice data) { if (_var.IsReady) { Plot("Variance", "var", _var); } } }
class VarianceAlgorithm(QCAlgorithm): def Initialize(self) -> None: self.symbol = self.AddEquity("SPY", Resolution.Daily).Symbol self.var = self.VAR("SPY", 20) def OnData(self, slice: Slice) -> None: if self.var.IsReady: 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.TryGeValue(_symbol, out var bar)) { _var.Update(bar.EndTime, bar.Close); } if (_var.IsReady) { 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 = data.Bars.get(self.symbol) if bar: self.var.Update(bar.EndTime, bar.Close) if self.var.IsReady: 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) { 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: 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 Varianc
class using the specified period.
Variance()2/2
Variance QuantConnect.Indicators.Variance (string
name,int
period )
Initializes a new instance of the Varianc
class using the specified name and period.
Visualization
The following image shows plot values of selected properties of Variance
using the plotly library.
