Supported Indicators
Correlation
Introduction
The Correlation Indicator is a valuable tool in technical analysis, designed to quantify the degree of relationship between the price movements of a target security (e.g., a stock or ETF) and a reference market index. It measures how closely the target’s price changes are aligned with the fluctuations of the index over a specific period of time, providing insights into the target’s susceptibility to market movements. A positive correlation indicates that the target tends to move in the same direction as the market index, while a negative correlation suggests an inverse relationship. A correlation close to 0 implies a weak or no linear relationship. Commonly, the SPX index is employed as the benchmark for the overall market when calculating correlation, ensuring a consistent and reliable reference point. This helps traders and investors make informed decisions regarding the risk and behavior of the target security in relation to market trends. 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 C Indicator
To create an automatic indicator for Correlation, call the Cc helper method from the QCAlgorithm class. The Cc method creates a Correlation 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 CorrelationAlgorithm : QCAlgorithm
{
private Symbol _symbol,_reference;
private Correlation _c;
public override void Initialize()
{
_symbol = AddEquity("QQQ", Resolution.Daily).Symbol;
_reference = AddEquity("SPY", Resolution.Daily).Symbol;
_c = C(_symbol, _reference, 20, CorrelationType.Pearson);
}
public override void OnData(Slice data)
{
if (_c.IsReady)
{
// The current value of _c is represented by itself (_c)
// or _c.Current.Value
Plot("Correlation", "c", _c);
}
}
} class CorrelationAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("QQQ", Resolution.DAILY).symbol
self._reference = self.add_equity("SPY", Resolution.DAILY).symbol
self._c = self.c(self._symbol, self._reference, 20, CorrelationType.PEARSON)
def on_data(self, slice: Slice) -> None:
if self._c.is_ready:
# The current value of self._c is represented by self._c.current.value
self.plot("Correlation", "c", self._c.current.value)For more information about this method, see the QCAlgorithm classQCAlgorithm class.
You can manually create a Correlation 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 CorrelationAlgorithm : QCAlgorithm
{
private Symbol _symbol,_reference;
private Correlation _correlation;
public override void Initialize()
{
_symbol = AddEquity("QQQ", Resolution.Daily).Symbol;
_reference = AddEquity("SPY", Resolution.Daily).Symbol;
_correlation = new Correlation(_symbol, _reference, 20, CorrelationType.Pearson);
}
public override void OnData(Slice data)
{
if (data.Bars.TryGetValue(_symbol, out var bar))
_correlation.Update(bar);
if (data.Bars.TryGetValue(_reference, out bar))
_correlation.Update(bar);
if (_correlation.IsReady)
{
// The current value of _correlation is represented by itself (_correlation)
// or _correlation.Current.Value
Plot("Correlation", "correlation", _correlation);
}
}
} class CorrelationAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("QQQ", Resolution.DAILY).symbol
self._reference = self.add_equity("SPY", Resolution.DAILY).symbol
self._correlation = Correlation(self._symbol, self._reference, 20, CorrelationType.PEARSON)
def on_data(self, slice: Slice) -> None:
bar = slice.bars.get(self._symbol)
if bar:
self._correlation.update(bar)
bar = slice.bars.get(self._reference)
if bar:
self._correlation.update(bar)
if self._correlation.is_ready:
# The current value of self._correlation is represented by self._correlation.current.value
self.plot("Correlation", "correlation", self._correlation.current.value)For more information about this indicator, see its referencereference.
Indicator History
To get the historical data of the Correlation 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 CorrelationAlgorithm : QCAlgorithm
{
private Symbol _symbol,_reference;
private Correlation _c;
public override void Initialize()
{
_symbol = AddEquity("QQQ", Resolution.Daily).Symbol;
_reference = AddEquity("SPY", Resolution.Daily).Symbol;
_c = C(_symbol, _reference, 20, CorrelationType.Pearson);
var indicatorHistory = IndicatorHistory(_c, new[] { _symbol, _reference }, 100, Resolution.Minute);
var timeSpanIndicatorHistory = IndicatorHistory(_c, new[] { _symbol, _reference }, TimeSpan.FromDays(10), Resolution.Minute);
var timePeriodIndicatorHistory = IndicatorHistory(_c, new[] { _symbol, _reference }, new DateTime(2024, 7, 1), new DateTime(2024, 7, 5), Resolution.Minute);
}
} class CorrelationAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self._symbol = self.add_equity("QQQ", Resolution.DAILY).symbol
self._reference = self.add_equity("SPY", Resolution.DAILY).symbol
self._c = self.c(self._symbol, self._reference, 20, CorrelationType.PEARSON)
indicator_history = self.indicator_history(self._c, [ self._symbol, self._reference ], 100, Resolution.MINUTE)
timedelta_indicator_history = self.indicator_history(self._c, [ self._symbol, self._reference ], timedelta(days=10), Resolution.MINUTE)
time_period_indicator_history = self.indicator_history(self._c, [ self._symbol, self._reference ], datetime(2024, 7, 1), datetime(2024, 7, 5), Resolution.MINUTE)
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