# Supported Indicators

## Relative Strength Index

### Introduction

This indicator represents the Relative Strength Index (RSI) developed by K. Welles Wilder. You can optionally specified a different moving average type to be used in the computation

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

### Using RSI Indicator

To create an automatic indicators for RelativeStrengthIndex, call the RSI helper method from the QCAlgorithm class. The RSI method creates a RelativeStrengthIndex 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 RelativeStrengthIndexAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private RelativeStrengthIndex _rsi;

public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
_rsi = RSI(_symbol, 14);
}

public override void OnData(Slice data)
{
{
// The current value of _rsi is represented by itself (_rsi)
// or _rsi.Current.Value
Plot("RelativeStrengthIndex", "rsi", _rsi);
// Plot all properties of rsi
Plot("RelativeStrengthIndex", "averageloss", _rsi.AverageLoss);
Plot("RelativeStrengthIndex", "averagegain", _rsi.AverageGain);
}
}
}
class RelativeStrengthIndexAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
self._rsi = self.rsi(self._symbol, 14)

def on_data(self, slice: Slice) -> None:
# The current value of self._rsi is represented by self._rsi.current.value
self.plot("RelativeStrengthIndex", "rsi", self._rsi.current.value)
# Plot all attributes of self._rsi
self.plot("RelativeStrengthIndex", "average_loss", self._rsi.average_loss.current.value)
self.plot("RelativeStrengthIndex", "average_gain", self._rsi.average_gain.current.value)


The following reference table describes the RSI method:

rsi(symbol, period, moving_average_type=2, resolution=None, selector=None)[source]

Creates a new RelativeStrengthIndex indicator. This will produce an oscillator that ranges from 0 to 100 based on the ratio of average gains to average losses over the specified period.

Parameters:
• symbol (Symbol) — The symbol whose RSI we want
• period (int) — The period over which to compute the RSI
• moving_average_type (MovingAverageType, optional) — The type of moving average to use in computing the average gainloss values
• resolution (Resolution, optional) — The resolution
• selector (Callable[IBaseData, float], optional) — x.Value)
Returns:

The RelativeStrengthIndex indicator for the requested symbol over the specified period

Return type:

RelativeStrengthIndex

RSI(symbol, period, movingAverageType=2, resolution=None, selector=None)[source]

Creates a new RelativeStrengthIndex indicator. This will produce an oscillator that ranges from 0 to 100 based on the ratio of average gains to average losses over the specified period.

Parameters:
• symbol (Symbol) — The symbol whose RSI we want
• period (Int32) — The period over which to compute the RSI
• movingAverageType (MovingAverageType, optional) — The type of moving average to use in computing the average gainloss values
• resolution (Resolution, optional) — The resolution
• selector (Func<IBaseData, Decimal>, optional) — x.Value)
Returns:

The RelativeStrengthIndex indicator for the requested symbol over the specified period

Return type:

RelativeStrengthIndex

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.

The following table describes the MovingAverageType enumeration members:

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

public class RelativeStrengthIndexAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private RelativeStrengthIndex _rsi;

public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Hour).Symbol;
_rsi = RSI(_symbol, 14, resolution: Resolution.Daily);
}
}
class RelativeStrengthIndexAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("SPY", Resolution.HOUR).Symbol
self._rsi = self.rsi(self._symbol, 14, resolution=Resolution.DAILY)


You can manually create a RelativeStrengthIndex 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 RelativeStrengthIndexAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private RelativeStrengthIndex _rsi;

public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
_rsi = new RelativeStrengthIndex(14);
}

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

{
// The current value of _rsi is represented by itself (_rsi)
// or _rsi.Current.Value
Plot("RelativeStrengthIndex", "rsi", _rsi);
// Plot all properties of rsi
Plot("RelativeStrengthIndex", "averageloss", _rsi.AverageLoss);
Plot("RelativeStrengthIndex", "averagegain", _rsi.AverageGain);
}
}
}
class RelativeStrengthIndexAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
self._rsi = RelativeStrengthIndex(14)

def on_data(self, slice: Slice) -> None:
bar = slice.bars.get(self._symbol)
if bar:
self._rsi.update(bar.EndTime, bar.Close)
# The current value of self._rsi is represented by self._rsi.current.value
self.plot("RelativeStrengthIndex", "rsi", self._rsi.current.value)
# Plot all attributes of self._rsi
self.plot("RelativeStrengthIndex", "average_loss", self._rsi.average_loss.current.value)
self.plot("RelativeStrengthIndex", "average_gain", self._rsi.average_gain.current.value)


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

public class RelativeStrengthIndexAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private RelativeStrengthIndex _rsi;

public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
_rsi = new RelativeStrengthIndex(14);
RegisterIndicator(_symbol, _rsi, Resolution.Daily);
}

public override void OnData(Slice data)
{
{
// The current value of _rsi is represented by itself (_rsi)
// or _rsi.Current.Value
Plot("RelativeStrengthIndex", "rsi", _rsi);
// Plot all properties of rsi
Plot("RelativeStrengthIndex", "averageloss", _rsi.AverageLoss);
Plot("RelativeStrengthIndex", "averagegain", _rsi.AverageGain);
}
}
}
class RelativeStrengthIndexAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
self._rsi = RelativeStrengthIndex(14)
self.register_indicator(self._symbol, self._rsi, Resolution.DAILY)

def on_data(self, slice: Slice) -> None:
# The current value of self._rsi is represented by self._rsi.current.value
self.plot("RelativeStrengthIndex", "rsi", self._rsi.current.value)
# Plot all attributes of self._rsi
self.plot("RelativeStrengthIndex", "average_loss", self._rsi.average_loss.current.value)
self.plot("RelativeStrengthIndex", "average_gain", self._rsi.average_gain.current.value)


The following reference table describes the RelativeStrengthIndex constructor:

#### RelativeStrengthIndex

class QuantConnect.Indicators.RelativeStrengthIndex[source]

Represents the Relative Strength Index (RSI) developed by K. Welles Wilder. You can optionally specified a different moving average type to be used in the computation

get_enumerator()

Returns an enumerator that iterates through the history window.

Return type:

IEnumerator[IndicatorDataPoint]

reset()

Resets this indicator 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 average_gain

Gets the indicator for average gain

Returns:

Gets the indicator for average gain

Return type:

IndicatorBase[IndicatorDataPoint]

property average_loss

Gets the EMA for the down days

Returns:

Gets the EMA for the down days

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 moving_average_type

Gets the type of indicator used to compute AverageGain and AverageLoss

Returns:

Gets the type of indicator used to compute AverageGain and AverageLoss

Return type:

MovingAverageType

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]

#### RelativeStrengthIndex

class QuantConnect.Indicators.RelativeStrengthIndex[source]

Represents the Relative Strength Index (RSI) developed by K. Welles Wilder. You can optionally specified a different moving average type to be used in the computation

GetEnumerator()

Returns an enumerator that iterates through the history window.

Return type:

IEnumerator[IndicatorDataPoint]

Reset()

Resets this indicator 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 AverageGain

Gets the indicator for average gain

Returns:

Gets the indicator for average gain

Return type:

IndicatorBase<IndicatorDataPoint>

property AverageLoss

Gets the EMA for the down days

Returns:

Gets the EMA for the down days

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 MovingAverageType

Gets the type of indicator used to compute AverageGain and AverageLoss

Returns:

Gets the type of indicator used to compute AverageGain and AverageLoss

Return type:

MovingAverageType

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 RelativeStrengthIndex using the plotly library.

### Indicator History

To get the historical data of the RelativeStrengthIndex 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 RelativeStrengthIndexAlgorithm : QCAlgorithm
{
private Symbol _symbol;

public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
var rsi = RSI(_symbol, 14);
var countIndicatorHistory = IndicatorHistory(rsi, _symbol, 100, Resolution.Minute);
var timeSpanIndicatorHistory = IndicatorHistory(rsi, _symbol, TimeSpan.FromDays(10), Resolution.Minute);
var timePeriodIndicatorHistory = IndicatorHistory(rsi, _symbol, new DateTime(2024, 7, 1), new DateTime(2024, 7, 5), Resolution.Minute);
}
}
class RelativeStrengthIndexAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
rsi = self.rsi(self._symbol, 14)
count_indicator_history = self.indicator_history(rsi, self._symbol, 100, Resolution.MINUTE)
timedelta_indicator_history = self.indicator_history(rsi, self._symbol, timedelta(days=10), Resolution.MINUTE)
time_period_indicator_history = self.indicator_history(rsi, 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(rsi, 100, Resolution.Minute, (bar) => ((TradeBar)bar).High);
indicator_history = self.indicator_history(rsi, 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(rsi, history);

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

var averageloss = indicatorHistory.Select(x => ((dynamic)x).AverageLoss).ToList();
var averagegain = indicatorHistory.Select(x => ((dynamic)x).AverageGain).ToList();

// Alternative way
// var averageloss = indicatorHistory.Select(x => x["averageloss"]).ToList();
// var averagegain = indicatorHistory.Select(x => x["averagegain"]).ToList();

average_loss = indicator_history_df["average_loss"]
average_gain = indicator_history_df["average_gain"]

# Alternative way
# average_loss = indicator_history_df.average_loss
# average_gain = indicator_history_df.average_gain


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