# Supported Indicators

## Bollinger Bands

### Introduction

This indicator creates a moving average (middle band) with an upper band and lower band fixed at k standard deviations above and below the moving average.

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

### Using BB Indicator

To create an automatic indicators for BollingerBands, call the BB helper method from the QCAlgorithm class. The BB method creates a BollingerBands 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 BollingerBandsAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private BollingerBands _bb;

public override void Initialize()
{
_bb = BB(_symbol, 30, 2);
}

public override void OnData(Slice data)
{
{
// The current value of _bb is represented by itself (_bb)
// or _bb.Current.Value
Plot("BollingerBands", "bb", _bb);
// Plot all properties of bb
Plot("BollingerBands", "standarddeviation", _bb.StandardDeviation);
Plot("BollingerBands", "middleband", _bb.MiddleBand);
Plot("BollingerBands", "upperband", _bb.UpperBand);
Plot("BollingerBands", "lowerband", _bb.LowerBand);
Plot("BollingerBands", "bandwidth", _bb.BandWidth);
Plot("BollingerBands", "percentb", _bb.PercentB);
Plot("BollingerBands", "price", _bb.Price);
}
}
}
class BollingerBandsAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._bb = self.bb(self._symbol, 30, 2)

def on_data(self, slice: Slice) -> None:
# The current value of self._bb is represented by self._bb.current.value
self.plot("BollingerBands", "bb", self._bb.current.value)
# Plot all attributes of self._bb
self.plot("BollingerBands", "standard_deviation", self._bb.standard_deviation.current.value)
self.plot("BollingerBands", "middle_band", self._bb.middle_band.current.value)
self.plot("BollingerBands", "upper_band", self._bb.upper_band.current.value)
self.plot("BollingerBands", "lower_band", self._bb.lower_band.current.value)
self.plot("BollingerBands", "band_width", self._bb.band_width.current.value)
self.plot("BollingerBands", "percent_b", self._bb.percent_b.current.value)
self.plot("BollingerBands", "price", self._bb.price.current.value)


The following reference table describes the BB method:

bb(symbol, period, k, moving_average_type=0, resolution=None, selector=None)[source]

Creates a new BollingerBands indicator which will compute the MiddleBand, UpperBand, LowerBand, and StandardDeviation

Parameters:
• symbol (Symbol) — The symbol whose BollingerBands we seek
• period (int) — The period of the standard deviation and moving average (middle band)
• k (float) — The number of standard deviations specifying the distance between the middle band and upper or lower bands
• moving_average_type (MovingAverageType, optional) — The type of moving average to be used
• resolution (Resolution, optional) — The resolution
• selector (Callable[IBaseData, float], optional) — x.Value)
Returns:

A BollingerBands configured with the specified period

Return type:

BollingerBands

BB(symbol, period, k, movingAverageType=0, resolution=None, selector=None)[source]

Creates a new BollingerBands indicator which will compute the MiddleBand, UpperBand, LowerBand, and StandardDeviation

Parameters:
• symbol (Symbol) — The symbol whose BollingerBands we seek
• period (Int32) — The period of the standard deviation and moving average (middle band)
• k (decimal) — The number of standard deviations specifying the distance between the middle band and upper or lower bands
• movingAverageType (MovingAverageType, optional) — The type of moving average to be used
• resolution (Resolution, optional) — The resolution
• selector (Func<IBaseData, Decimal>, optional) — x.Value)
Returns:

A BollingerBands configured with the specified period

Return type:

BollingerBands

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.

The following table describes the MovingAverageType enumeration members:

To avoid parameter ambiguity, use the resolution argument to set the Resolution.

public class BollingerBandsAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private BollingerBands _bb;

public override void Initialize()
{
_bb = BB(_symbol, 30, 2, resolution: Resolution.Daily);
}
}
class BollingerBandsAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._bb = self.bb(self._symbol, 30, 2, resolution=Resolution.DAILY)


You can manually create a BollingerBands 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 BollingerBandsAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private BollingerBands _bb;

public override void Initialize()
{
_bb = new BollingerBands(30, 2);
}

public override void OnData(Slice data)
{
if (data.Bars.TryGetValue(_symbol, out var bar))
{
_bb.Update(bar.EndTime, bar.Close);
}

{
// The current value of _bb is represented by itself (_bb)
// or _bb.Current.Value
Plot("BollingerBands", "bb", _bb);
// Plot all properties of bb
Plot("BollingerBands", "standarddeviation", _bb.StandardDeviation);
Plot("BollingerBands", "middleband", _bb.MiddleBand);
Plot("BollingerBands", "upperband", _bb.UpperBand);
Plot("BollingerBands", "lowerband", _bb.LowerBand);
Plot("BollingerBands", "bandwidth", _bb.BandWidth);
Plot("BollingerBands", "percentb", _bb.PercentB);
Plot("BollingerBands", "price", _bb.Price);
}
}
}
class BollingerBandsAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._bb = BollingerBands(30, 2)

def on_data(self, slice: Slice) -> None:
bar = slice.bars.get(self._symbol)
if bar:
self._bb.update(bar.EndTime, bar.Close)
# The current value of self._bb is represented by self._bb.current.value
self.plot("BollingerBands", "bb", self._bb.current.value)
# Plot all attributes of self._bb
self.plot("BollingerBands", "standard_deviation", self._bb.standard_deviation.current.value)
self.plot("BollingerBands", "middle_band", self._bb.middle_band.current.value)
self.plot("BollingerBands", "upper_band", self._bb.upper_band.current.value)
self.plot("BollingerBands", "lower_band", self._bb.lower_band.current.value)
self.plot("BollingerBands", "band_width", self._bb.band_width.current.value)
self.plot("BollingerBands", "percent_b", self._bb.percent_b.current.value)
self.plot("BollingerBands", "price", self._bb.price.current.value)


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

public class BollingerBandsAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private BollingerBands _bb;

public override void Initialize()
{
_bb = new BollingerBands(30, 2);
RegisterIndicator(_symbol, _bb, Resolution.Daily);
}

public override void OnData(Slice data)
{
{
// The current value of _bb is represented by itself (_bb)
// or _bb.Current.Value
Plot("BollingerBands", "bb", _bb);
// Plot all properties of bb
Plot("BollingerBands", "standarddeviation", _bb.StandardDeviation);
Plot("BollingerBands", "middleband", _bb.MiddleBand);
Plot("BollingerBands", "upperband", _bb.UpperBand);
Plot("BollingerBands", "lowerband", _bb.LowerBand);
Plot("BollingerBands", "bandwidth", _bb.BandWidth);
Plot("BollingerBands", "percentb", _bb.PercentB);
Plot("BollingerBands", "price", _bb.Price);
}
}
}
class BollingerBandsAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._bb = BollingerBands(30, 2)
self.register_indicator(self._symbol, self._bb, Resolution.DAILY)

def on_data(self, slice: Slice) -> None:
# The current value of self._bb is represented by self._bb.current.value
self.plot("BollingerBands", "bb", self._bb.current.value)
# Plot all attributes of self._bb
self.plot("BollingerBands", "standard_deviation", self._bb.standard_deviation.current.value)
self.plot("BollingerBands", "middle_band", self._bb.middle_band.current.value)
self.plot("BollingerBands", "upper_band", self._bb.upper_band.current.value)
self.plot("BollingerBands", "lower_band", self._bb.lower_band.current.value)
self.plot("BollingerBands", "band_width", self._bb.band_width.current.value)
self.plot("BollingerBands", "percent_b", self._bb.percent_b.current.value)
self.plot("BollingerBands", "price", self._bb.price.current.value)


The following reference table describes the BollingerBands constructor:

#### BollingerBands

class QuantConnect.Indicators.BollingerBands[source]

This indicator creates a moving average (middle band) with an upper band and lower band fixed at k standard deviations above and below the moving average.

get_enumerator()

Returns an enumerator that iterates through the history window.

Return type:

IEnumerator[IndicatorDataPoint]

reset()

Resets this indicator and all sub-indicators (StandardDeviation, LowerBand, MiddleBand, UpperBand, BandWidth, %B)

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 band_width

Gets the Bollinger BandWidth indicator BandWidth = ((Upper Band - Lower Band) / Middle Band) * 100

Returns:

Gets the Bollinger BandWidth indicator BandWidth = ((Upper Band - Lower Band) / Middle Band) * 100

Return type:

IndicatorBase[IndicatorDataPoint]

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

Gets a flag indicating when this indicator is ready and fully initialized

Returns:

Gets a flag indicating when this indicator is ready and fully initialized

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 lower_band

Gets the lower Bollinger band (middleBand - k * stdDev)

Returns:

Gets the lower Bollinger band (middleBand - k * stdDev)

Return type:

IndicatorBase[IndicatorDataPoint]

property middle_band

Gets the middle Bollinger band (moving average)

Returns:

Gets the middle Bollinger band (moving average)

Return type:

IndicatorBase[IndicatorDataPoint]

property moving_average_type

Gets the type of moving average

Returns:

Gets the type of moving average

Return type:

MovingAverageType

property name

Gets a name for this indicator

Returns:

Gets a name for this indicator

Return type:

str

property percent_b

Gets the Bollinger %B %B = (Price - Lower Band)/(Upper Band - Lower Band)

Returns:

Gets the Bollinger %B %B = (Price - Lower Band)/(Upper Band - Lower Band)

Return type:

IndicatorBase[IndicatorDataPoint]

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 price

Gets the Price level

Returns:

Gets the Price level

Return type:

IndicatorBase[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 standard_deviation

Gets the standard deviation

Returns:

Gets the standard deviation

Return type:

IndicatorBase[IndicatorDataPoint]

property upper_band

Gets the upper Bollinger band (middleBand + k * stdDev)

Returns:

Gets the upper Bollinger band (middleBand + k * stdDev)

Return type:

IndicatorBase[IndicatorDataPoint]

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]

#### BollingerBands

class QuantConnect.Indicators.BollingerBands[source]

This indicator creates a moving average (middle band) with an upper band and lower band fixed at k standard deviations above and below the moving average.

GetEnumerator()

Returns an enumerator that iterates through the history window.

Return type:

IEnumerator[IndicatorDataPoint]

Reset()

Resets this indicator and all sub-indicators (StandardDeviation, LowerBand, MiddleBand, UpperBand, BandWidth, %B)

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 BandWidth

Gets the Bollinger BandWidth indicator BandWidth = ((Upper Band - Lower Band) / Middle Band) * 100

Returns:

Gets the Bollinger BandWidth indicator BandWidth = ((Upper Band - Lower Band) / Middle Band) * 100

Return type:

IndicatorBase<IndicatorDataPoint>

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

Gets a flag indicating when this indicator is ready and fully initialized

Returns:

Gets a flag indicating when this indicator is ready and fully initialized

Return type:

bool

property LowerBand

Gets the lower Bollinger band (middleBand - k * stdDev)

Returns:

Gets the lower Bollinger band (middleBand - k * stdDev)

Return type:

IndicatorBase<IndicatorDataPoint>

property MiddleBand

Gets the middle Bollinger band (moving average)

Returns:

Gets the middle Bollinger band (moving average)

Return type:

IndicatorBase<IndicatorDataPoint>

property MovingAverageType

Gets the type of moving average

Returns:

Gets the type of moving average

Return type:

MovingAverageType

property Name

Gets a name for this indicator

Returns:

Gets a name for this indicator

Return type:

string

property PercentB

Gets the Bollinger %B %B = (Price - Lower Band)/(Upper Band - Lower Band)

Returns:

Gets the Bollinger %B %B = (Price - Lower Band)/(Upper Band - Lower Band)

Return type:

IndicatorBase<IndicatorDataPoint>

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 Price

Gets the Price level

Returns:

Gets the Price level

Return type:

IndicatorBase<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 StandardDeviation

Gets the standard deviation

Returns:

Gets the standard deviation

Return type:

IndicatorBase<IndicatorDataPoint>

property UpperBand

Gets the upper Bollinger band (middleBand + k * stdDev)

Returns:

Gets the upper Bollinger band (middleBand + k * stdDev)

Return type:

IndicatorBase<IndicatorDataPoint>

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 BollingerBands using the plotly library.

### Indicator History

To get the historical data of the BollingerBands 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 BollingerBandsAlgorithm : QCAlgorithm
{
private Symbol _symbol;

public override void Initialize()
{
var bb = BB(_symbol, 30, 2);
var countIndicatorHistory = IndicatorHistory(bb, _symbol, 100, Resolution.Minute);
var timeSpanIndicatorHistory = IndicatorHistory(bb, _symbol, TimeSpan.FromDays(10), Resolution.Minute);
var timePeriodIndicatorHistory = IndicatorHistory(bb, _symbol, new DateTime(2024, 7, 1), new DateTime(2024, 7, 5), Resolution.Minute);
}
}
class BollingerBandsAlgorithm(QCAlgorithm):
def initialize(self) -> None:
bb = self.bb(self._symbol, 30, 2)
count_indicator_history = self.indicator_history(bb, self._symbol, 100, Resolution.MINUTE)
timedelta_indicator_history = self.indicator_history(bb, self._symbol, timedelta(days=10), Resolution.MINUTE)
time_period_indicator_history = self.indicator_history(bb, 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(bb, 100, Resolution.Minute, (bar) => ((TradeBar)bar).High);
indicator_history = self.indicator_history(bb, 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(bb, history);

To access the properties of the indicator history, invoke the property of each IndicatorDataPoint object.index the DataFrame with the property name.

var standarddeviation = indicatorHistory.Select(x => ((dynamic)x).StandardDeviation).ToList();
var middleband = indicatorHistory.Select(x => ((dynamic)x).MiddleBand).ToList();
var upperband = indicatorHistory.Select(x => ((dynamic)x).UpperBand).ToList();
var lowerband = indicatorHistory.Select(x => ((dynamic)x).LowerBand).ToList();
var bandwidth = indicatorHistory.Select(x => ((dynamic)x).BandWidth).ToList();
var percentb = indicatorHistory.Select(x => ((dynamic)x).PercentB).ToList();
var price = indicatorHistory.Select(x => ((dynamic)x).Price).ToList();

// Alternative way
// var standarddeviation = indicatorHistory.Select(x => x["standarddeviation"]).ToList();
// var middleband = indicatorHistory.Select(x => x["middleband"]).ToList();
// var upperband = indicatorHistory.Select(x => x["upperband"]).ToList();
// var lowerband = indicatorHistory.Select(x => x["lowerband"]).ToList();
// var bandwidth = indicatorHistory.Select(x => x["bandwidth"]).ToList();
// var percentb = indicatorHistory.Select(x => x["percentb"]).ToList();
// var price = indicatorHistory.Select(x => x["price"]).ToList();

standard_deviation = indicator_history_df["standard_deviation"]
middle_band = indicator_history_df["middle_band"]
upper_band = indicator_history_df["upper_band"]
lower_band = indicator_history_df["lower_band"]
band_width = indicator_history_df["band_width"]
percent_b = indicator_history_df["percent_b"]
price = indicator_history_df["price"]

# Alternative way
# standard_deviation = indicator_history_df.standard_deviation
# middle_band = indicator_history_df.middle_band
# upper_band = indicator_history_df.upper_band
# lower_band = indicator_history_df.lower_band
# band_width = indicator_history_df.band_width
# percent_b = indicator_history_df.percent_b
# price = indicator_history_df.price


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