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
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("SPY", 10, 6, 0.85);
}
public override void OnData(Slice data)
{
if (_alma.IsReady)
{
Plot("ArnaudLegouxMovingAverage", "alma", _alma);
}
}
} class ArnaudLegouxMovingAverageAlgorithm(QCAlgorithm):
def Initialize(self) -> None:
self.symbol = self.AddEquity("SPY", Resolution.Daily).Symbol
self.alma = self.ALMA("SPY", 10, 6, 0.85)
def OnData(self, slice: Slice) -> None:
if self.alma.IsReady:
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)
{
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 = data.Bars.get(self.symbol)
if bar:
self.alma.Update(bar.EndTime, bar.Close)
if self.alma.IsReady:
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)
{
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:
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.
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