Supported Indicators

Log Return

Introduction

This indicator represents the LogReturn indicator (LOGR) - log returns are useful for identifying price convergence/divergence in a given period - logr = log (current price / last price in period)

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

Using LOGR Indicator

To create an automatic indicators for LogReturn, call the LOGR helper method from the QCAlgorithm class. The LOGR method creates a LogReturn 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 LogReturnAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private LogReturn _logr;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _logr = LOGR(_symbol, 20);
    }

    public override void OnData(Slice data)
    {
        if (_logr.IsReady)
        {
            // The current value of _logr is represented by itself (_logr)
            // or _logr.Current.Value
            Plot("LogReturn", "logr", _logr);
            
        }
    }
}
class LogReturnAlgorithm(QCAlgorithm):
    def Initialize(self) -> None:
        self._symbol = self.AddEquity("SPY", Resolution.Daily).Symbol
        self.logr = self.LOGR(self.symbol, 20)

    def on_data(self, slice: Slice) -> None:
        if self.logr.IsReady:
            # The current value of self.logr is represented by self.logr.Current.Value
            self.plot("LogReturn", "logr", self.logr.Current.Value)

The following reference table describes the LOGR method:

LOGR()1/1

            LogReturn QuantConnect.Algorithm.QCAlgorithm.LOGR (
    Symbol                           symbol,
    Int32                            period,
    *Nullable<Resolution>      resolution,
    *Func<IBaseData, Decimal>  selector
   )

Creates a new LogReturn indicator.

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.

For more information about plotting indicators, see Plotting Indicators.

You can manually create a LogReturn 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 LogReturnAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private LogReturn _logr;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _logr = new LogReturn(20);
    }

    public override void OnData(Slice data)
    {
        if (data.Bars.TryGetValue(_symbol, out var bar))
        {      
            _logr.Update(bar.EndTime, bar.Close);
        }
   
        if (_logr.IsReady)
        {
            // The current value of _logr is represented by itself (_logr)
            // or _logr.Current.Value
            Plot("LogReturn", "logr", _logr);
            
        }
    }
}
class LogReturnAlgorithm(QCAlgorithm):
    def Initialize(self) -> None:
        self._symbol = self.AddEquity("SPY", Resolution.Daily).Symbol
        self.logr = LogReturn(20)

    def on_data(self, slice: Slice) -> None:
        bar = slice.Bars.get(self.symbol)
        if bar:
            self.logr.Update(bar.EndTime, bar.Close)
        if self.logr.IsReady:
            # The current value of self.logr is represented by self.logr.Current.Value
            self.plot("LogReturn", "logr", self.logr.Current.Value)

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

public class LogReturnAlgorithm : QCAlgorithm
{
    private Symbol _symbol;
    private LogReturn _logr;

    public override void Initialize()
    {
        _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
        _logr = new LogReturn(20);
        RegisterIndicator(_symbol, _logr, Resolution.Daily);
    }

    public override void OnData(Slice data)
    {
        if (_logr.IsReady)
        {
            // The current value of _logr is represented by itself (_logr)
            // or _logr.Current.Value
            Plot("LogReturn", "logr", _logr);
            
        }
    }
}
class LogReturnAlgorithm(QCAlgorithm):
    def Initialize(self) -> None:
        self._symbol = self.AddEquity("SPY", Resolution.Daily).Symbol
        self.logr = LogReturn(20)
        self.RegisterIndicator(self.symbol, self.logr, Resolution.Daily)

    def on_data(self, slice: Slice) -> None:
        if self.logr.IsReady:
            # The current value of self.logr is represented by self.logr.Current.Value
            self.plot("LogReturn", "logr", self.logr.Current.Value)

The following reference table describes the LogReturn constructor:

LogReturn()1/2

            LogReturn QuantConnect.Indicators.LogReturn (
    string  name,
    int     period
   )

Initializes a new instance of the LogReturn class with the specified name and period.

LogReturn()2/2

            LogReturn QuantConnect.Indicators.LogReturn (
    int  period
   )

Initializes a new instance of the LogReturn class with the default name and period.

Visualization

The following image shows plot values of selected properties of LogReturn using the plotly library.

LogReturn line plot.

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