Supported Indicators

Least Squares Moving Average With Reference

Introduction

The Least Squares Moving Average (LSMA) of a target in relation with a reference fits a least squares regression line of the target close prices on the reference close prices over the given period, instead of on the time index used by LeastSquaresMovingAverage. It then returns the value the regression line takes for the most recent reference price, which is the price the target is expected to have given where the reference is trading. It is common practice to use the SPX index as the reference, so that the indicator describes the target price in terms of the overall market level. The indicator only updates when both assets have a price for a time step. When a bar is missing for one of the assets, the indicator value fills forward to improve the accuracy of the indicator.

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

Using LSMA Indicator

To create an automatic indicator for LeastSquaresMovingAverageWithReference, call the LSMAlsma helper method from the QCAlgorithm class. The LSMAlsma method creates a LeastSquaresMovingAverageWithReference object, hooks it up for automatic updates, and returns it so you can use it in your algorithm. In most cases, you should call the helper method in the Initializeinitialize method.

public class LeastSquaresMovingAverageWithReferenceAlgorithm : QCAlgorithm
{
    private Symbol _symbol,_reference;
    private LeastSquaresMovingAverageWithReference _lsma;

    public override void Initialize()
    {
        _symbol = AddEquity("QQQ", Resolution.Daily).Symbol;
        _reference = AddEquity("SPY", Resolution.Daily).Symbol;
        _lsma = LSMA(_symbol, _reference, 20);
    }

    public override void OnData(Slice data)
    {

        if (_lsma.IsReady)
        {
            // The current value of _lsma is represented by itself (_lsma)
            // or _lsma.Current.Value
            Plot("LeastSquaresMovingAverageWithReference", "lsma", _lsma);
            // Plot all properties of _lsma
            Plot("LeastSquaresMovingAverageWithReference", "intercept", _lsma.Intercept);
            Plot("LeastSquaresMovingAverageWithReference", "slope", _lsma.Slope);
        }
    }
}
class LeastSquaresMovingAverageWithReferenceAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("QQQ", Resolution.DAILY).symbol
        self._reference = self.add_equity("SPY", Resolution.DAILY).symbol
        self._lsma = self.lsma(self._symbol, self._reference, 20)

    def on_data(self, slice: Slice) -> None:

        if self._lsma.is_ready:
            # The current value of self._lsma is represented by self._lsma.current.value
            self.plot("LeastSquaresMovingAverageWithReference", "lsma", self._lsma.current.value)
            # Plot all attributes of self._lsma
            self.plot("LeastSquaresMovingAverageWithReference", "intercept", self._lsma.intercept.current.value)
            self.plot("LeastSquaresMovingAverageWithReference", "slope", self._lsma.slope.current.value)

For more information about this method, see the QCAlgorithm classQCAlgorithm class.

You can manually create a LeastSquaresMovingAverageWithReference 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 LeastSquaresMovingAverageWithReferenceAlgorithm : QCAlgorithm
{
    private Symbol _symbol,_reference;
    private LeastSquaresMovingAverageWithReference _leastsquaresmovingaveragewithreference;

    public override void Initialize()
    {
        _symbol = AddEquity("QQQ", Resolution.Daily).Symbol;
        _reference = AddEquity("SPY", Resolution.Daily).Symbol;
        _leastsquaresmovingaveragewithreference = new LeastSquaresMovingAverageWithReference(_symbol, _reference, 20);
    }

    public override void OnData(Slice data)
    {
        if (data.Bars.TryGetValue(_symbol, out var bar))
            _leastsquaresmovingaveragewithreference.Update(bar);
        if (data.Bars.TryGetValue(_reference, out bar))
            _leastsquaresmovingaveragewithreference.Update(bar);

        if (_leastsquaresmovingaveragewithreference.IsReady)
        {
            // The current value of _leastsquaresmovingaveragewithreference is represented by itself (_leastsquaresmovingaveragewithreference)
            // or _leastsquaresmovingaveragewithreference.Current.Value
            Plot("LeastSquaresMovingAverageWithReference", "leastsquaresmovingaveragewithreference", _leastsquaresmovingaveragewithreference);
            // Plot all properties of _leastsquaresmovingaveragewithreference
            Plot("LeastSquaresMovingAverageWithReference", "intercept", _leastsquaresmovingaveragewithreference.Intercept);
            Plot("LeastSquaresMovingAverageWithReference", "slope", _leastsquaresmovingaveragewithreference.Slope);
        }
    }
}
class LeastSquaresMovingAverageWithReferenceAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("QQQ", Resolution.DAILY).symbol
        self._reference = self.add_equity("SPY", Resolution.DAILY).symbol
        self._leastsquaresmovingaveragewithreference = LeastSquaresMovingAverageWithReference(self._symbol, self._reference, 20)

    def on_data(self, slice: Slice) -> None:
        bar = slice.bars.get(self._symbol)
        if bar:
            self._leastsquaresmovingaveragewithreference.update(bar)
        bar = slice.bars.get(self._reference)
        if bar:
            self._leastsquaresmovingaveragewithreference.update(bar)

        if self._leastsquaresmovingaveragewithreference.is_ready:
            # The current value of self._leastsquaresmovingaveragewithreference is represented by self._leastsquaresmovingaveragewithreference.current.value
            self.plot("LeastSquaresMovingAverageWithReference", "leastsquaresmovingaveragewithreference", self._leastsquaresmovingaveragewithreference.current.value)
            # Plot all attributes of self._leastsquaresmovingaveragewithreference
            self.plot("LeastSquaresMovingAverageWithReference", "intercept", self._leastsquaresmovingaveragewithreference.intercept.current.value)
            self.plot("LeastSquaresMovingAverageWithReference", "slope", self._leastsquaresmovingaveragewithreference.slope.current.value)

For more information about this indicator, see its referencereference.

Visualization

The following plot shows values for some of the LeastSquaresMovingAverageWithReference indicator properties:

LeastSquaresMovingAverageWithReference line plot.

Indicator History

To get the historical data of the LeastSquaresMovingAverageWithReference 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 LeastSquaresMovingAverageWithReferenceAlgorithm : QCAlgorithm
{
    private Symbol _symbol,_reference;
    private LeastSquaresMovingAverageWithReference _lsma;

    public override void Initialize()
    {
        _symbol = AddEquity("QQQ", Resolution.Daily).Symbol;
        _reference = AddEquity("SPY", Resolution.Daily).Symbol;
        _lsma = LSMA(_symbol, _reference, 20);

        var indicatorHistory = IndicatorHistory(_lsma, new[] { _symbol, _reference }, 100, Resolution.Minute);
        var timeSpanIndicatorHistory = IndicatorHistory(_lsma, new[] { _symbol, _reference }, TimeSpan.FromDays(10), Resolution.Minute);
        var timePeriodIndicatorHistory = IndicatorHistory(_lsma, new[] { _symbol, _reference }, new DateTime(2024, 7, 1), new DateTime(2024, 7, 5), Resolution.Minute);

        // Access all attributes of indicatorHistory
        var intercept = indicatorHistory.Select(x => ((dynamic)x).Intercept).ToList();
        var slope = indicatorHistory.Select(x => ((dynamic)x).Slope).ToList();
    }
}
class LeastSquaresMovingAverageWithReferenceAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self._symbol = self.add_equity("QQQ", Resolution.DAILY).symbol
        self._reference = self.add_equity("SPY", Resolution.DAILY).symbol
        self._lsma = self.lsma(self._symbol, self._reference, 20)

        indicator_history = self.indicator_history(self._lsma, [ self._symbol, self._reference ], 100, Resolution.MINUTE)
        timedelta_indicator_history = self.indicator_history(self._lsma, [ self._symbol, self._reference ], timedelta(days=10), Resolution.MINUTE)
        time_period_indicator_history = self.indicator_history(self._lsma, [ self._symbol, self._reference ], datetime(2024, 7, 1), datetime(2024, 7, 5), Resolution.MINUTE)
    
        # Access all attributes of indicator_history
        indicator_history_df = indicator_history.data_frame
        intercept = indicator_history_df["intercept"]
        slope = indicator_history_df["slope"]

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