Supported Indicators
Triple Exponential Moving Average
Introduction
This indicator computes the Triple Exponential Moving Average (TEMA). The Triple Exponential Moving Average is calculated with the following formula: EMA1 = EMA(t,period) EMA2 = EMA(EMA(t,period),period) EMA3 = EMA(EMA(EMA(t,period),period),period) TEMA = 3 * EMA1 - 3 * EMA2 + EMA3
To view the implementation of this indicator, see the LEAN GitHub repository.
Using TEMA Indicator
To create an automatic indicator for TripleExponentialMovingAverage, call the TEMAtema helper method from the QCAlgorithm class. The TEMAtema method creates a TripleExponentialMovingAverage 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 TripleExponentialMovingAverageAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private TripleExponentialMovingAverage _tema;
public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
_tema = TEMA(_symbol, 20);
}
public override void OnData(Slice data)
{
if (_tema.IsReady)
{
// The current value of _tema is represented by itself (_tema)
// or _tema.Current.Value
Plot("TripleExponentialMovingAverage", "tema", _tema);
}
}
} class TripleExponentialMovingAverageAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
self._tema = self.tema(self._symbol, 20)
def on_data(self, slice: Slice) -> None:
if self._tema.is_ready:
# The current value of self._tema is represented by self._tema.current.value
self.plot("TripleExponentialMovingAverage", "tema", self._tema.current.value)For more information about this method, see the QCAlgorithm classQCAlgorithm class.
You can manually create a TripleExponentialMovingAverage 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. The indicator will only be ready after you prime it with enough data.
public class TripleExponentialMovingAverageAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private TripleExponentialMovingAverage _tripleexponentialmovingaverage;
public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
_tripleexponentialmovingaverage = new TripleExponentialMovingAverage(20);
}
public override void OnData(Slice data)
{
if (data.Bars.TryGetValue(_symbol, out var bar))
_tripleexponentialmovingaverage.Update(bar.EndTime, bar.Close);
if (_tripleexponentialmovingaverage.IsReady)
{
// The current value of _tripleexponentialmovingaverage is represented by itself (_tripleexponentialmovingaverage)
// or _tripleexponentialmovingaverage.Current.Value
Plot("TripleExponentialMovingAverage", "tripleexponentialmovingaverage", _tripleexponentialmovingaverage);
}
}
} class TripleExponentialMovingAverageAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
self._tripleexponentialmovingaverage = TripleExponentialMovingAverage(20)
def on_data(self, slice: Slice) -> None:
bar = slice.bars.get(self._symbol)
if bar:
self._tripleexponentialmovingaverage.update(bar.end_time, bar.close)
if self._tripleexponentialmovingaverage.is_ready:
# The current value of self._tripleexponentialmovingaverage is represented by self._tripleexponentialmovingaverage.current.value
self.plot("TripleExponentialMovingAverage", "tripleexponentialmovingaverage", self._tripleexponentialmovingaverage.current.value)For more information about this indicator, see its referencereference.
Indicator History
To get the historical data of the TripleExponentialMovingAverage 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 TripleExponentialMovingAverageAlgorithm : QCAlgorithm
{
private Symbol _symbol;
private TripleExponentialMovingAverage _tema;
public override void Initialize()
{
_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
_tema = TEMA(_symbol, 20);
var indicatorHistory = IndicatorHistory(_tema, _symbol, 100, Resolution.Minute);
var timeSpanIndicatorHistory = IndicatorHistory(_tema, _symbol, TimeSpan.FromDays(10), Resolution.Minute);
var timePeriodIndicatorHistory = IndicatorHistory(_tema, _symbol, new DateTime(2024, 7, 1), new DateTime(2024, 7, 5), Resolution.Minute);
}
} class TripleExponentialMovingAverageAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
self._tema = self.tema(self._symbol, 20)
indicator_history = self.indicator_history(self._tema, self._symbol, 100, Resolution.MINUTE)
timedelta_indicator_history = self.indicator_history(self._tema, self._symbol, timedelta(days=10), Resolution.MINUTE)
time_period_indicator_history = self.indicator_history(self._tema, self._symbol, datetime(2024, 7, 1), datetime(2024, 7, 5), Resolution.MINUTE)
