Supported Indicators

Kaufman Adaptive Moving Average

Introduction

This indicator computes the Kaufman Adaptive Moving Average (KAMA). The Kaufman Adaptive Moving Average is calculated as explained here: http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:kaufman_s_adaptive_moving_average

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

Using KAMA Indicator

To create an automatic indicators for KaufmanAdaptiveMovingAverage, call the KAMA helper method from the QCAlgorithm class. The KAMA method creates a KaufmanAdaptiveMovingAverage 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 KaufmanAdaptiveMovingAverageAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private KaufmanAdaptiveMovingAverage _kama;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _kama = KAMA(_symbol, 20, 10, 20);
    }

    public override void OnData(Slice data)
    {
        if (_kama.IsReady)
        {
            // The current value of _kama is represented by itself (_kama)
            // or _kama.Current.Value
            Plot("KaufmanAdaptiveMovingAverage", "kama", _kama);
            
        }
    }
}
class KaufmanAdaptiveMovingAverageAlgorithm(QCAlgorithm):
    def Initialize(self) -> None:
        self._symbol = self.AddEquity("SPY", Resolution.Daily).Symbol
        self.kama = self.KAMA(self.symbol, 20, 10, 20)

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

The following reference table describes the KAMA method:

KAMA()1/2

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

Creates a new KaufmanAdaptiveMovingAverage indicator.

KAMA()2/2

            KaufmanAdaptiveMovingAverage QuantConnect.Algorithm.QCAlgorithm.KAMA (
    Symbol                           symbol,
    Int32                            period,
    Int32                            fastEmaPeriod,
    Int32                            slowEmaPeriod,
    *Nullable<Resolution>      resolution,
    *Func<IBaseData, Decimal>  selector
   )
        

Creates a new KaufmanAdaptiveMovingAverage 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 KaufmanAdaptiveMovingAverage 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 with time/number pair or an IndicatorDataPoint. The indicator will only be ready after you prime it with enough data.

public class KaufmanAdaptiveMovingAverageAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private KaufmanAdaptiveMovingAverage _kama;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _kama = new KaufmanAdaptiveMovingAverage(20, 10, 20);
    }

    public override void OnData(Slice data)
    {
        if (data.Bars.TryGetValue(_symbol, out var bar))
        {      
            _kama.Update(bar.EndTime, bar.Close);
        }
   
        if (_kama.IsReady)
        {
            // The current value of _kama is represented by itself (_kama)
            // or _kama.Current.Value
            Plot("KaufmanAdaptiveMovingAverage", "kama", _kama);
            
        }
    }
}
class KaufmanAdaptiveMovingAverageAlgorithm(QCAlgorithm):
    def Initialize(self) -> None:
        self._symbol = self.AddEquity("SPY", Resolution.Daily).Symbol
        self.kama = KaufmanAdaptiveMovingAverage(20, 10, 20)

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

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

public class KaufmanAdaptiveMovingAverageAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private KaufmanAdaptiveMovingAverage _kama;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _kama = new KaufmanAdaptiveMovingAverage(20, 10, 20);
        RegisterIndicator(_symbol, _kama, Resolution.Daily);
    }

    public override void OnData(Slice data)
    {
        if (_kama.IsReady)
        {
            // The current value of _kama is represented by itself (_kama)
            // or _kama.Current.Value
            Plot("KaufmanAdaptiveMovingAverage", "kama", _kama);
            
        }
    }
}
class KaufmanAdaptiveMovingAverageAlgorithm(QCAlgorithm):
    def Initialize(self) -> None:
        self._symbol = self.AddEquity("SPY", Resolution.Daily).Symbol
        self.kama = KaufmanAdaptiveMovingAverage(20, 10, 20)
        self.RegisterIndicator(self.symbol, self.kama, Resolution.Daily)

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

The following reference table describes the KaufmanAdaptiveMovingAverage constructor:

KaufmanAdaptiveMovingAverage()1/2

            KaufmanAdaptiveMovingAverage QuantConnect.Indicators.KaufmanAdaptiveMovingAverage (
    string  name,
    int     period,
    *int    fastEmaPeriod,
    *int    slowEmaPeriod
   )
        

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

KaufmanAdaptiveMovingAverage()2/2

            KaufmanAdaptiveMovingAverage QuantConnect.Indicators.KaufmanAdaptiveMovingAverage (
    int   period,
    *int  fastEmaPeriod,
    *int  slowEmaPeriod
   )
        

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

Visualization

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

KaufmanAdaptiveMovingAverage line plot.

You can also see our Videos. You can also get in touch with us via Discord.

Did you find this page helpful?

Contribute to the documentation: