Supported Indicators

Fractal Adaptive Moving Average

Introduction

The Fractal Adaptive Moving Average (FRAMA) by John Ehlers

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

Using FRAMA Indicator

To create an automatic indicators for FractalAdaptiveMovingAverage, call the FRAMA helper method from the QCAlgorithm class. The FRAMA method creates a FractalAdaptiveMovingAverage 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 FractalAdaptiveMovingAverageAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private FractalAdaptiveMovingAverage _frama;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _frama = FRAMA(_symbol, 20, 198);
    }

    public override void OnData(Slice data)
    {
        if (_frama.IsReady)
        {
            // The current value of _frama is represented by itself (_frama)
            // or _frama.Current.Value
            Plot("FractalAdaptiveMovingAverage", "frama", _frama);
            
        }
    }
}
class FractalAdaptiveMovingAverageAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self.frama = self.FRAMA(self.symbol, 20, 198)

    def on_data(self, slice: Slice) -> None:
        if self.frama.is_ready:
            # The current value of self.frama is represented by self.frama.current.value
            self.plot("FractalAdaptiveMovingAverage", "frama", self.frama.current.value)
            

The following reference table describes the FRAMA method:

frama(symbol, period, long_period=198, resolution=None, selector=None)[source]

Creates an FractalAdaptiveMovingAverage (FRAMA) indicator for the symbol. The indicator will be automatically updated on the given resolution.

Parameters:
  • symbol (Symbol) — The symbol whose FRAMA we want
  • period (int) — The period of the FRAMA
  • long_period (int, optional) — The long period of the FRAMA
  • resolution (Resolution, optional) — The resolution
  • selector (Callable[IBaseData, IBaseDataBar], optional) — Selects a value from the BaseData to send into the indicator, if null defaults to casting the input value to a TradeBar
Returns:

The FRAMA for the given parameters

Return type:

FractalAdaptiveMovingAverage

FRAMA(symbol, period, longPeriod=198, resolution=None, selector=None)[source]

Creates an FractalAdaptiveMovingAverage (FRAMA) indicator for the symbol. The indicator will be automatically updated on the given resolution.

Parameters:
  • symbol (Symbol) — The symbol whose FRAMA we want
  • period (Int32) — The period of the FRAMA
  • longPeriod (Int32, optional) — The long period of the FRAMA
  • resolution (Resolution, optional) — The resolution
  • selector (Func<IBaseData, IBaseDataBar>, optional) — Selects a value from the BaseData to send into the indicator, if null defaults to casting the input value to a TradeBar
Returns:

The FRAMA for the given parameters

Return type:

FractalAdaptiveMovingAverage

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 FractalAdaptiveMovingAverage 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 a TradeBar or QuoteBar. The indicator will only be ready after you prime it with enough data.

public class FractalAdaptiveMovingAverageAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private FractalAdaptiveMovingAverage _frama;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _frama = new FractalAdaptiveMovingAverage(20, 198);
    }

    public override void OnData(Slice data)
    {
        if (data.Bars.TryGetValue(_symbol, out var bar))
        {      
            _frama.Update(bar);
        }
   
        if (_frama.IsReady)
        {
            // The current value of _frama is represented by itself (_frama)
            // or _frama.Current.Value
            Plot("FractalAdaptiveMovingAverage", "frama", _frama);
            
        }
    }
}
class FractalAdaptiveMovingAverageAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self.frama = FractalAdaptiveMovingAverage(20, 198)

    def on_data(self, slice: Slice) -> None:
        bar = slice.bars.get(self._symbol)
        if bar:
            self.frama.update(bar)
        if self.frama.is_ready:
            # The current value of self.frama is represented by self.frama.current.value
            self.plot("FractalAdaptiveMovingAverage", "frama", self.frama.current.value)
            

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

public class FractalAdaptiveMovingAverageAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private FractalAdaptiveMovingAverage _frama;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _frama = new FractalAdaptiveMovingAverage(20, 198);
        RegisterIndicator(_symbol, _frama, Resolution.Daily);
    }

    public override void OnData(Slice data)
    {
        if (_frama.IsReady)
        {
            // The current value of _frama is represented by itself (_frama)
            // or _frama.Current.Value
            Plot("FractalAdaptiveMovingAverage", "frama", _frama);
            
        }
    }
}
class FractalAdaptiveMovingAverageAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
        self.frama = FractalAdaptiveMovingAverage(20, 198)
        self.register_indicator(self._symbol, self.frama, Resolution.DAILY)

    def on_data(self, slice: Slice) -> None:
        if self.frama.is_ready:
            # The current value of self.frama is represented by self.frama.current.value
            self.plot("FractalAdaptiveMovingAverage", "frama", self.frama.current.value)
            

The following reference table describes the FractalAdaptiveMovingAverage constructor:

FractalAdaptiveMovingAverage

class QuantConnect.Indicators.FractalAdaptiveMovingAverage[source]

The Fractal Adaptive Moving Average (FRAMA) by John Ehlers

get_enumerator()

Returns an enumerator that iterates through the history window.

Return type:

IEnumerator[IndicatorDataPoint]

reset()

Resets the average to its initial state

to_detailed_string()

Provides a more detailed string of this indicator in the form of {Name} - {Value}

Return type:

str

update(time, value)

Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise

Parameters:
  • time (datetime)
  • value (float)
Return type:

bool

update(input)

Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise

Parameters:
  • input (IBaseData)
Return type:

bool

property consolidators

The data consolidators associated with this indicator if any

Returns:

The data consolidators associated with this indicator if any

Return type:

ISet[IDataConsolidator]

property current

Gets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Returns:

Gets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Return type:

IndicatorDataPoint

property is_ready

Returns whether the indicator will return valid results

Returns:

Returns whether the indicator will return valid results

Return type:

bool

property item

Indexes the history windows, where index 0 is the most recent indicator value. If index is greater or equal than the current count, it returns null. If the index is greater or equal than the window size, it returns null and resizes the windows to i + 1.

Returns:

Indexes the history windows, where index 0 is the most recent indicator value. If index is greater or equal than the current count, it returns null. If the index is greater or equal than the window size, it returns null and resizes the windows to i + 1.

Return type:

IndicatorDataPoint

property name

Gets a name for this indicator

Returns:

Gets a name for this indicator

Return type:

str

property previous

Gets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Returns:

Gets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Return type:

IndicatorDataPoint

property samples

Gets the number of samples processed by this indicator

Returns:

Gets the number of samples processed by this indicator

Return type:

int

property warm_up_period

Required period, in data points, for the indicator to be ready and fully initialized.

Returns:

Required period, in data points, for the indicator to be ready and fully initialized.

Return type:

int

property window

A rolling window keeping a history of the indicator values of a given period

Returns:

A rolling window keeping a history of the indicator values of a given period

Return type:

RollingWindow[IndicatorDataPoint]

FractalAdaptiveMovingAverage

class QuantConnect.Indicators.FractalAdaptiveMovingAverage[source]

The Fractal Adaptive Moving Average (FRAMA) by John Ehlers

GetEnumerator()

Returns an enumerator that iterates through the history window.

Return type:

IEnumerator[IndicatorDataPoint]

Reset()

Resets the average to its initial state

ToDetailedString()

Provides a more detailed string of this indicator in the form of {Name} - {Value}

Return type:

String

Update(time, value)

Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise

Parameters:
  • time (DateTime)
  • value (decimal)
Return type:

Boolean

Update(input)

Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise

Parameters:
  • input (IBaseData)
Return type:

Boolean

property Consolidators

The data consolidators associated with this indicator if any

Returns:

The data consolidators associated with this indicator if any

Return type:

ISet<IDataConsolidator>

property Current

Gets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Returns:

Gets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Return type:

IndicatorDataPoint

property IsReady

Returns whether the indicator will return valid results

Returns:

Returns whether the indicator will return valid results

Return type:

bool

property Name

Gets a name for this indicator

Returns:

Gets a name for this indicator

Return type:

string

property Previous

Gets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Returns:

Gets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.

Return type:

IndicatorDataPoint

property Samples

Gets the number of samples processed by this indicator

Returns:

Gets the number of samples processed by this indicator

Return type:

int

property WarmUpPeriod

Required period, in data points, for the indicator to be ready and fully initialized.

Returns:

Required period, in data points, for the indicator to be ready and fully initialized.

Return type:

Int32

property Window

A rolling window keeping a history of the indicator values of a given period

Returns:

A rolling window keeping a history of the indicator values of a given period

Return type:

RollingWindow<IndicatorDataPoint>

property [System.Int32]

Indexes the history windows, where index 0 is the most recent indicator value. If index is greater or equal than the current count, it returns null. If the index is greater or equal than the window size, it returns null and resizes the windows to i + 1.

Returns:

Indexes the history windows, where index 0 is the most recent indicator value. If index is greater or equal than the current count, it returns null. If the index is greater or equal than the window size, it returns null and resizes the windows to i + 1.

Return type:

IndicatorDataPoint

Visualization

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

FractalAdaptiveMovingAverage line plot.

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