Supported Indicators
Arnaud Legoux Moving Average
Introduction
Smooth and high sensitive moving Average. This moving average reduce lag of the information but still being smooth to reduce noises. Is a weighted moving average, which weights have a Normal shape; the parameters Sigma and Offset affect the kurtosis and skewness of the weights respectively. source
To view the implementation of this indicator, see the LEAN GitHub repository.
Using ALMA Indicator
To create an automatic indicators for ArnaudLegouxMovingAverage
, call the ALMA
helper method from the QCAlgorithm
class. The ALMA
method creates a ArnaudLegouxMovingAverage
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 ArnaudLegouxMovingAverageAlgorithm : QCAlgorithm { private Symbol _symbol; private ArnaudLegouxMovingAverage _alma; public override void Initialize() { _symbol = AddEquity("SPY", Resolution.Daily).Symbol; _alma = ALMA(_symbol, 10, 6, 0.85); } public override void OnData(Slice data) { if (_alma.IsReady) { // The current value of _alma is represented by itself (_alma) // or _alma.Current.Value Plot("ArnaudLegouxMovingAverage", "alma", _alma); } } }
class ArnaudLegouxMovingAverageAlgorithm(QCAlgorithm): def Initialize(self) -> None: self.symbol = self.AddEquity("SPY", Resolution.Daily).Symbol self.alma = self.ALMA(self.symbol, 10, 6, 0.85) def OnData(self, slice: Slice) -> None: if self.alma.IsReady: # The current value of self.alma is represented by self.alma.Current.Value self.Plot("ArnaudLegouxMovingAverage", "alma", self.alma.Current.Value)
The following reference table describes the ALMA
method:
ALMA()1/1
ArnaudLegouxMovingAverage QuantConnect.Algorithm.QCAlgorithm.ALMA (Symbol
symbol,Int32
period,*Int32
sigma,*Decimal
offset,*Nullable<Resolution>
resolution,*Func<IBaseData, Decimal>
selector )
Creates a new ArnaudLegouxMovingAverage indicator.
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 ArnaudLegouxMovingAverage
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 ArnaudLegouxMovingAverageAlgorithm : QCAlgorithm { private Symbol _symbol; private ArnaudLegouxMovingAverage _alma; public override void Initialize() { _symbol = AddEquity("SPY", Resolution.Daily).Symbol; _alma = new ArnaudLegouxMovingAverage(10, 6, 0.85); } public override void OnData(Slice data) { if (data.Bars.TryGeValue(_symbol, out var bar)) { _alma.Update(bar.EndTime, bar.Close); } if (_alma.IsReady) { // The current value of _alma is represented by itself (_alma) // or _alma.Current.Value Plot("ArnaudLegouxMovingAverage", "alma", _alma); } } }
class ArnaudLegouxMovingAverageAlgorithm(QCAlgorithm): def Initialize(self) -> None: self.symbol = self.AddEquity("SPY", Resolution.Daily).Symbol self.alma = ArnaudLegouxMovingAverage(10, 6, 0.85) def OnData(self, slice: Slice) -> None: bar = slice.Bars.get(self.symbol) if bar: self.alma.Update(bar.EndTime, bar.Close) if self.alma.IsReady: # The current value of self.alma is represented by self.alma.Current.Value self.Plot("ArnaudLegouxMovingAverage", "alma", self.alma.Current.Value)
To register a manual indicator for automatic updates with the security data, call the RegisterIndicator
method.
public class ArnaudLegouxMovingAverageAlgorithm : QCAlgorithm { private Symbol _symbol; private ArnaudLegouxMovingAverage _alma; public override void Initialize() { _symbol = AddEquity("SPY", Resolution.Daily).Symbol; _alma = new ArnaudLegouxMovingAverage(10, 6, 0.85); RegisterIndicator(_symbol, _alma, Resolution.Daily); } public override void OnData(Slice data) { if (_alma.IsReady) { // The current value of _alma is represented by itself (_alma) // or _alma.Current.Value Plot("ArnaudLegouxMovingAverage", "alma", _alma); } } }
class ArnaudLegouxMovingAverageAlgorithm(QCAlgorithm): def Initialize(self) -> None: self.symbol = self.AddEquity("SPY", Resolution.Daily).Symbol self.alma = ArnaudLegouxMovingAverage(10, 6, 0.85) self.RegisterIndicator(self.symbol, self.alma, Resolution.Daily) def OnData(self, slice: Slice) -> None: if self.alma.IsReady: # The current value of self.alma is represented by self.alma.Current.Value self.Plot("ArnaudLegouxMovingAverage", "alma", self.alma.Current.Value)
The following reference table describes the ArnaudLegouxMovingAverage
constructor:
ArnaudLegouxMovingAverage()1/4
ArnaudLegouxMovingAverage QuantConnect.Indicators.ArnaudLegouxMovingAverage (string
name,int
period )
Initializes a new instance of the ArnaudLegouxMovingAverage
class.
ArnaudLegouxMovingAverage()2/4
ArnaudLegouxMovingAverage QuantConnect.Indicators.ArnaudLegouxMovingAverage (string
name,int
period )
Initializes a new instance of the ArnaudLegouxMovingAverage
class.
ArnaudLegouxMovingAverage()3/4
ArnaudLegouxMovingAverage QuantConnect.Indicators.ArnaudLegouxMovingAverage (
int
period
)
Initializes a new instance of the ArnaudLegouxMovingAverage
class.
ArnaudLegouxMovingAverage()4/4
ArnaudLegouxMovingAverage QuantConnect.Indicators.ArnaudLegouxMovingAverage (
int
period
)
Initializes a new instance of the ArnaudLegouxMovingAverage
class.
Visualization
The following image shows plot values of selected properties of ArnaudLegouxMovingAverage
using the plotly library.
