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.
- 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
The FRAMA for the given parameters
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.
- 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
The FRAMA for the given parameters
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
The Fractal Adaptive Moving Average (FRAMA) by John Ehlers
get_enumerator()Returns an enumerator that iterates through the history window.
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}
str
update(time, value)Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise
- time (datetime)
- value (float)
bool
update(input)Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise
- input (IBaseData)
bool
consolidatorsThe data consolidators associated with this indicator if any
The data consolidators associated with this indicator if any
ISet[IDataConsolidator]
currentGets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.
Gets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.
IndicatorDataPoint
is_readyReturns whether the indicator will return valid results
Returns whether the indicator will return valid results
bool
itemIndexes 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.
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.
IndicatorDataPoint
nameGets a name for this indicator
Gets a name for this indicator
str
previousGets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.
Gets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.
IndicatorDataPoint
samplesGets the number of samples processed by this indicator
Gets the number of samples processed by this indicator
int
warm_up_periodRequired period, in data points, for the indicator to be ready and fully initialized.
Required period, in data points, for the indicator to be ready and fully initialized.
int
windowA rolling window keeping a history of the indicator values of a given period
A rolling window keeping a history of the indicator values of a given period
RollingWindow[IndicatorDataPoint]
FractalAdaptiveMovingAverage
The Fractal Adaptive Moving Average (FRAMA) by John Ehlers
GetEnumerator()Returns an enumerator that iterates through the history window.
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}
String
Update(time, value)Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise
- time (DateTime)
- value (decimal)
Boolean
Update(input)Updates the state of this indicator with the given value and returns true if this indicator is ready, false otherwise
- input (IBaseData)
Boolean
ConsolidatorsThe data consolidators associated with this indicator if any
The data consolidators associated with this indicator if any
ISet<IDataConsolidator>
CurrentGets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.
Gets the current state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.
IndicatorDataPoint
IsReadyReturns whether the indicator will return valid results
Returns whether the indicator will return valid results
bool
NameGets a name for this indicator
Gets a name for this indicator
string
PreviousGets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.
Gets the previous state of this indicator. If the state has not been updated then the time on the value will equal DateTime.MinValue.
IndicatorDataPoint
SamplesGets the number of samples processed by this indicator
Gets the number of samples processed by this indicator
int
WarmUpPeriodRequired period, in data points, for the indicator to be ready and fully initialized.
Required period, in data points, for the indicator to be ready and fully initialized.
Int32
WindowA rolling window keeping a history of the indicator values of a given period
A rolling window keeping a history of the indicator values of a given period
RollingWindow<IndicatorDataPoint>
[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.
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.
IndicatorDataPoint
Visualization
The following image shows plot values of selected properties of FractalAdaptiveMovingAverage using the plotly library.
Indicator History
To get the historical data of the FractalAdaptiveMovingAverage indicator, call the IndicatorHistoryself.indicator_history method.
This method resets your indicator, makes a history request, and updates the indicator with the historical data.
Just like with regular history requests, the IndicatorHistoryindicator_history method supports time periods based on a trailing number of bars, a trailing period of time, or a defined period of time.
If you don't provide a resolution argument, it defaults to match the resolution of the security subscription.
public class FractalAdaptiveMovingAverageAlgorithm : QCAlgorithm
{
private Symbol _symbol;
public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
var frama = FRAMA(_symbol, 20, 198);
var countIndicatorHistory = IndicatorHistory(frama, _symbol, 100, Resolution.Minute);
var timeSpanIndicatorHistory = IndicatorHistory(frama, _symbol, TimeSpan.FromDays(10), Resolution.Minute);
var timePeriodIndicatorHistory = IndicatorHistory(frama, _symbol, new DateTime(2024, 7, 1), new DateTime(2024, 7, 5), Resolution.Minute);
}
} class FractalAdaptiveMovingAverageAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
frama = self.frama(self._symbol, 20, 198)
count_indicator_history = self.indicator_history(frama, self._symbol, 100, Resolution.MINUTE)
timedelta_indicator_history = self.indicator_history(frama, self._symbol, timedelta(days=10), Resolution.MINUTE)
time_period_indicator_history = self.indicator_history(frama, self._symbol, datetime(2024, 7, 1), datetime(2024, 7, 5), Resolution.MINUTE)
To make the IndicatorHistoryindicator_history method update the indicator with an alternative price field instead of the close (or mid-price) of each bar, pass a selector argument.
var indicatorHistory = IndicatorHistory(frama, 100, Resolution.Minute, (bar) => ((TradeBar)bar).High);
indicator_history = self.indicator_history(frama, 100, Resolution.MINUTE, lambda bar: bar.high) indicator_history_df = indicator_history.data_frame
If you already have a list of Slice objects, you can pass them to the IndicatorHistoryindicator_history method to avoid the internal history request.
var history = History(_symbol, 100, Resolution.Minute); var historyIndicatorHistory = IndicatorHistory(frama, history);
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