Indicators

Technical indicators take in a stream of data points, Bar objects, or TradeBar objects and produce a continuous value. Candlestick patterns take in a stream of Bar or TradeBar objects and produce a value that's either 0, 1, or -1 to signify the presence of the pattern.

You can configure technical indicators and candlestick patterns to receive manual or automatic updates. With manual indicators, you update the indicator with whatever data you want and whenever you want. With automatic indicators, the algorithm automatically uses the security data to update the indicator value.

LEAN's indicators are implemented "on-line". This means as data pipes through, it updates the internal state of the indicator. Other platforms perform indicator math on an array of values in bulk which can be very inefficient when working on large volumes of data. You need to warm up your indicators and prime them with data to get them ready.

You can classify an indicator as either a data point, bar, or TradeBar indicator. Their classification depends on the type of data they receive.

Data Point Indicators

Data point indicators use IndicatorDataPoint objects to compute their value. Some examples of data point indicators include the following:

• SimpleMovingAverage
• ExponentialMovingAverage
• Momentum

Bar Indicators

Bar indicators use QuoteBar or TradeBar objects to compute their value. Since Forex and CFD securities don't have TradeBar data, they use bar indicators. Candlestick patterns are examples of bar indicators. Some other examples of bar indicators include the following:

• WilliamsPercentR
• Stochastics
• AverageTrueRange

TradeBar Indicators

TradeBar indicators use TradeBar objects to compute their value. Some TradeBar indicators use the volume property of the TradeBar to compute their value. Some examples of TradeBar indicators include the following:

• Beta
• AdvanceDeclineVolumeRatio
• VolumeWeightedAveragePriceIndicator

The class name to create a manual indicator is the indicator name spelled in pascal case. For example, to create a manual simple moving average indicator, use the SimpleMovingAverage class.

The method to create an automatic indicator is usually named after the acronym of the indicator name. For example, to create an automatic simple moving average indicator, use the SMAsma method.

To view the class name and shortcut method of each indicator, see the Supported Indicators.

There are two ways to create indicators. You can create indicators with the indicator constructor or use a helper method in the QCAlgorithm class. If you use the helper method, the indicator automatically updates as your algorithm receives new data.

private BollingerBands _manualBB;
private BollingerBands _autoBB;
private Symbol _symbol;
public override void Initialize()
{
    // Create a manual indicator with the indicator constructor
    _manualBB = new BollingerBands(20, 2);
    // Create an automatic indicator with the helper method
    _symbol = AddCrypto("BTCUSD").Symbol;
    _autoBB = BB(_symbol, 20, 2, Resolution.Daily);
}

def initialize(self) -> None:
    # Create a manual indicator with the indicator constructor
    self.manual_bb = BollingerBands(20, 2)
    # Create an automatic indicator with the helper method
    self._symbol = self.add_crypto("BTCUSD").Symbol
    self.auto_bb = self.bb(self._symbol, 20, 2, Resolution.DAILY)

Indicators have a built-in RollingWindow that stores their historical values. The default window size is 2. To change the window size, set the Window.Size member.

// Increase the window size to 10 for the Bollinger Band
_manualBB.Window.Size = 10;
_autoBB.Window.Size = 10;

// Increase the Size to 20 for the middle band
_manualBB.MiddleBand.Window.Size = 20;
_autoBB.MiddleBand.Window.Size = 20;

# Increase the Size to 10 for Bollinger Band
self.manual_bb.window.size = 10
self.auto_bb.window.size = 10

# Increase the Size to 20 for the middle band
self.manual_bb.middle_band.window.size = 20
self.auto_bb.middle_band.window.size = 20

When you decrease the size, it removes the oldest values that no longer fit in the RollingWindow. When you explicitly increase the Sizesize member, it doesn't automatically add any new elements to the RollingWindow. However, if you set the value of an index in the RollingWindow and the index doesn't currently exist, it fills the empty indices with nullNone. For example, the following code increases the Sizesize to 10, sets the 10th element to the indicator current value, and sets the 6th-9th elements to nullNone:

_manualBB.Window[9] = _manualBB.Current;
_autoBB.Window[9] = _autoBB.Current;

self.manual_bb.window[9] = self.manual_bb.current
self.auto_bb.window[9] = self.auto_bb.current

Indicators aren't always ready when you first create them. The length of time it takes to trust the indicator values depends on the indicator period. To know if an indicator is ready to use, use the IsReadyis_ready property.

if not self.auto_bb.is_ready:
    return

if (!_autoBB.IsReady) return;

To get the number of samples the indicator has processed, use the Samplessamples property.

samples = self.auto_bb.samples

var samples = _autoBB.Samples;

The RollingWindow objects that store the historical values may not be full when the indicator is ready to use. To check if the Window is full, use its IsReadyis_ready flag.

if not self.auto_bb.window.is_ready:
    return

if (!_autoBB.Window.IsReady) return;

When an indicator receives a new data point and updates its state, it triggers an update event. To be notified of update events, attach an event handler to the indicator object. The event handler receives 2 arguments: the indicator object and the latest IndicatorDataPoint it produced.

# After you create the indicator, attach an event handler
self.auto_bb.updated += self.update_event_handler

# Define the event handler within the same class
def update_event_handler(self, indicator: object, indicator_data_point: IndicatorDataPoint) -> None:
    if indicator.is_ready:
        self.plot("Indicator", "Value", indicator_data_point.value)

// After you create the indicator, attach an event handler
_autoBB.Updated += updateEventHandler;

// Define the event handler within the same class
private void updateEventHandler(object indicator, IndicatorDataPoint indicatorDataPoint)
{
    if (indicator.IsReady)
    {
        Plot("Indicator", "Value", indicatorDataPoint.Value);
    }
}

To access the indicator value, use the Current.Valuecurrent.value property. Some indicators have one output and some indicators have multiple outputs. The SimpleMovingAverage indicator only has one output, the average price over the last n periods, so the Current.Valuecurrent.value property returns this value. The BollingerBand indicator has multiple outputs because it has a simple moving average, an upper band, and a lower band. For indicators that have multiple outputs, refer to the Supported Indicators to see how to access the output values.

sma = self.sma.current.value

current_price = self.auto_bb.current.value
bb_upper_band = self.auto_bb.upper_band.current.value
bb_lower_band = self.auto_bb.lower_band.current.value

var sma = _sma.Current.Value;

var currentPrice = _autoBB.Current.Value;
var bbUpperBand = _autoBB.UpperBand.Current.Value;
var bbLowerBand = _autoBB.LowerBand.Current.Value;