Supported Indicators
Average Range
Introduction
This indicator represents the Average Range (AR) indicator, which calculates the average price range
To view the implementation of this indicator, see the LEAN GitHub repository.
Using AverageRange Indicator
To create an automatic indicators for AverageRange
, call the AverageRange
helper method from the QCAlgorithm
class. The AverageRange
method creates a AverageRange
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
initialize
method.
public class AverageRangeAlgorithm : QCAlgorithm { private Symbol _symbol; private AverageRange _averagerange; public override void Initialize() { _symbol = AddEquity("SPY", Resolution.Daily).Symbol; _averagerange = AverageRange(_symbol); } public override void OnData(Slice data) { if (_averagerange.IsReady) { // The current value of _averagerange is represented by itself (_averagerange) // or _averagerange.Current.Value Plot("AverageRange", "averagerange", _averagerange); } } }
class AverageRangeAlgorithm(QCAlgorithm): def initialize(self) -> None: self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol self._averagerange = self.averagerange(self._symbol) def on_data(self, slice: Slice) -> None: if self._averagerange.is_ready: # The current value of self._averagerange is represented by self._averagerange.current.value self.plot("AverageRange", "averagerange", self._averagerange.current.value)
The following reference table describes the AverageRange
method:
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 AverageRange
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
update
method with a TradeBar
or QuoteBar
. The indicator will only be ready after you prime it with enough data.
public class AverageRangeAlgorithm : QCAlgorithm { private Symbol _symbol; private AverageRange _averagerange; public override void Initialize() { _symbol = AddEquity("SPY", Resolution.Daily).Symbol; _averagerange = new AverageRange(); } public override void OnData(Slice data) { if (data.Bars.TryGetValue(_symbol, out var bar)) { _averagerange.Update(bar); } if (_averagerange.IsReady) { // The current value of _averagerange is represented by itself (_averagerange) // or _averagerange.Current.Value Plot("AverageRange", "averagerange", _averagerange); } } }
class AverageRangeAlgorithm(QCAlgorithm): def initialize(self) -> None: self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol self._averagerange = AverageRange() def on_data(self, slice: Slice) -> None: bar = slice.bars.get(self._symbol) if bar: self._averagerange.update(bar) if self._averagerange.is_ready: # The current value of self._averagerange is represented by self._averagerange.current.value self.plot("AverageRange", "averagerange", self._averagerange.current.value)
To register a manual indicator for automatic updates with the security data, call the RegisterIndicator
register_indicator
method.
public class AverageRangeAlgorithm : QCAlgorithm { private Symbol _symbol; private AverageRange _averagerange; public override void Initialize() { _symbol = AddEquity("SPY", Resolution.Daily).Symbol; _averagerange = new AverageRange(); RegisterIndicator(_symbol, _averagerange, Resolution.Daily); } public override void OnData(Slice data) { if (_averagerange.IsReady) { // The current value of _averagerange is represented by itself (_averagerange) // or _averagerange.Current.Value Plot("AverageRange", "averagerange", _averagerange); } } }
class AverageRangeAlgorithm(QCAlgorithm): def initialize(self) -> None: self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol self._averagerange = AverageRange() self.register_indicator(self._symbol, self._averagerange, Resolution.DAILY) def on_data(self, slice: Slice) -> None: if self._averagerange.is_ready: # The current value of self._averagerange is represented by self._averagerange.current.value self.plot("AverageRange", "averagerange", self._averagerange.current.value)
The following reference table describes the AverageRange
constructor:
AverageRange
Represents the Average Range (AR) indicator, which calculates the average price range
get_enumerator()
Returns an enumerator that iterates through the history window.
IEnumerator[IndicatorDataPoint]
reset()
Resets the indicator and clears the internal state, including the SMA.
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
consolidators
The data consolidators associated with this indicator if any
The data consolidators associated with this indicator if any
ISet[IDataConsolidator]
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.
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_ready
Indicates whether the indicator has enough data to start producing valid results.
Indicates whether the indicator has enough data to start producing valid results.
bool
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.
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
name
Gets a name for this indicator
Gets a name for this indicator
str
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.
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
samples
Gets the number of samples processed by this indicator
Gets the number of samples processed by this indicator
int
warm_up_period
The number of periods needed to fully initialize the AR indicator.
The number of periods needed to fully initialize the AR indicator.
int
window
A 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]
AverageRange
Represents the Average Range (AR) indicator, which calculates the average price range
GetEnumerator()
Returns an enumerator that iterates through the history window.
IEnumerator[IndicatorDataPoint]
Reset()
Resets the indicator and clears the internal state, including the SMA.
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
Consolidators
The data consolidators associated with this indicator if any
The data consolidators associated with this indicator if any
ISet<IDataConsolidator>
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.
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
IsReady
Indicates whether the indicator has enough data to start producing valid results.
Indicates whether the indicator has enough data to start producing valid results.
bool
Name
Gets a name for this indicator
Gets a name for this indicator
string
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.
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
Samples
Gets the number of samples processed by this indicator
Gets the number of samples processed by this indicator
int
WarmUpPeriod
The number of periods needed to fully initialize the AR indicator.
The number of periods needed to fully initialize the AR indicator.
Int32
Window
A 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 AverageRange
using the plotly library.
Indicator History
To get the historical data of the AverageRange
indicator, call the IndicatorHistory
self.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 IndicatorHistory
indicator_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 AverageRangeAlgorithm : QCAlgorithm { private Symbol _symbol; public override void Initialize() { _symbol = AddEquity("SPY", Resolution.Daily).Symbol; var averagerange = AverageRange(_symbol); var countIndicatorHistory = IndicatorHistory(averagerange, _symbol, 100, Resolution.Minute); var timeSpanIndicatorHistory = IndicatorHistory(averagerange, _symbol, TimeSpan.FromDays(10), Resolution.Minute); var timePeriodIndicatorHistory = IndicatorHistory(averagerange, _symbol, new DateTime(2024, 7, 1), new DateTime(2024, 7, 5), Resolution.Minute); } }
class AverageRangeAlgorithm(QCAlgorithm): def initialize(self) -> None: self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol averagerange = self.averagerange(self._symbol) count_indicator_history = self.indicator_history(averagerange, self._symbol, 100, Resolution.MINUTE) timedelta_indicator_history = self.indicator_history(averagerange, self._symbol, timedelta(days=10), Resolution.MINUTE) time_period_indicator_history = self.indicator_history(averagerange, self._symbol, datetime(2024, 7, 1), datetime(2024, 7, 5), Resolution.MINUTE)
To make the IndicatorHistory
indicator_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(averagerange, 100, Resolution.Minute, (bar) => ((TradeBar)bar).High);
indicator_history = self.indicator_history(averagerange, 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 IndicatorHistory
indicator_history
method to avoid the internal history request.
var history = History(_symbol, 100, Resolution.Minute); var historyIndicatorHistory = IndicatorHistory(averagerange, history);