protected override void OnStateChange()
{
if (State == State.SetDefaults)
{
Description = @"Correlation of Two Instruments";
Name = "Correlation";
Calculate = Calculate.OnBarClose;
IsOverlay = false;
DisplayInDataBox = true;
DrawOnPricePanel = true;
DrawHorizontalGridLines = true;
DrawVerticalGridLines = true;
PaintPriceMarkers = true;
ScaleJustification = NinjaTrader.Gui.Chart.ScaleJustification.Right;
//Disable this property if your indicator requires custom values that cumulate with each new market data event.
//See Help Guide for additional information.
IsSuspendedWhileInactive = true;
//Symbol2 = string.Empty;
Period = 100;
PeriodPctChange = 1;
AddPlot(Brushes.CornflowerBlue, "Name");
}
else if (State == State.Configure)
{
AddDataSeries("CL 01-18", BarsPeriodType.Day, 1);
//AddDataSeries("CL 01-18", new BarsPeriod { BarsPeriodType = BarsPeriodType.Minute, Value = 1440 }, "Default 24 x 7");
}
else if (State == State.DataLoaded)
{
Instrument2BIPClose = new SyncedDataSeries(this, Instrument1BIP, Instrument2BIP, Closes[Instrument2BIP]);
}
}
private double SyncedRankCorrelation(PriceSeries inputSeries1, SyncedDataSeries inputSeries2, int corrPeriod)
// SyncedRankCorrelation: Calculate the Spearman Rank Correlation of 2 Data Series, using only the bars which are synchronized
//
// Inputs:
// inputSeries1: 1st DataSeries, typically Closes[x]
// inputSeries2: SyncedDataSeries, synced to InputSeries1; some bars (flagged by BoolSeries "Synced") hold valid (synchronized) values
// corrPeriod: Period for Correlation calculation; there must be >= CorrPeriod synced bars in the input series, or it will throw an exception
//
{
int index1 = 0;
double[] dataArray1 = new double[corrPeriod];
double[] dataArray2 = new double[corrPeriod];
for (int counter = corrPeriod - 1; counter >= 0; counter--)
{
while (!inputSeries2.Synced[index1]) //Find next synced Bar
{
index1++;
}
dataArray1[counter] = inputSeries1[index1];
dataArray2[counter] = inputSeries2[index1];
index1++;
}
return(KDRankCorrelation(dataArray1, dataArray2, corrPeriod));
}
private double SyncedPctChangeCorrelation(PriceSeries inputSeries1, SyncedDataSeries inputSeries2, int corrPeriod, int changeLookback)
{
int index = 0;
double[] pctChangeArray1 = new double[corrPeriod];
double[] pctChangeArray2 = new double[corrPeriod];
while (!inputSeries2.Synced[index]) //Find most recent synced Bar
{
index++;
}
double val1 = inputSeries1[index];
double val2 = inputSeries2[index];
index++;
for (int counter = corrPeriod - 1; counter >= 0; counter--)
{
int changeIndex;
while (!inputSeries2.Synced[index]) //Find previous synced Bar
{
index++;
}
double chg2 = inputSeries2.SyncedGet(changeLookback - 1, index, out changeIndex); // this will scan back more synced bars if changeLookback > 0
double chg1 = inputSeries1[changeIndex];
pctChangeArray1[counter] = (val1 - chg1) / chg1;
pctChangeArray2[counter] = (val2 - chg2) / chg2;
val1 = inputSeries1[index];
val2 = inputSeries2[index];
index++;
}
// return(KDRankCorrelation(pctChangeArray1,pctChangeArray2,corrPeriod)); // maybe rank correlation of PctChange would be better?
return(KDCorrelation(pctChangeArray1, pctChangeArray2, corrPeriod));
}
private double SyncedCorrelation(PriceSeries inputSeries1, SyncedDataSeries inputSeries2, int corrPeriod)
// SyncedCorrelation: Calculates the Pearson Product Moment Correlation of 2 Data Series, using only the bars which are synchronized
// Note: Correlations may differ from Excel if NinjaTrader is set to dividend-adjust historical prices
//
// Inputs:
// inputSeries1: 1st DataSeries, typically Closes[x]
// inputSeries2: SyncedDataSeries, synced to InputSeries1; some bars (flagged by BoolSeries "Synced") hold valid (synchronized) values
// corrPeriod: Period for Correlation calculation; there must be >= CorrPeriod synced bars in the input series, or it will throw an exception
//
{
double sum1 = 0;
double sum2 = 0;
double sum3 = 0;
int index1 = 0;
double mean1, mean2, variance1, variance2, denominator;
mean1 = SyncedSMA(inputSeries1, inputSeries2.Synced, corrPeriod);
mean2 = SyncedSMA(inputSeries2, inputSeries2.Synced, corrPeriod);
for (int counter = 0; counter < corrPeriod; counter++)
{
while (!inputSeries2.Synced[index1]) //Find next synced Bar
{
index1++;
}
variance1 = inputSeries1[index1] - mean1;
variance2 = inputSeries2[index1] - mean2;
sum1 += variance1 * variance2;
sum2 += variance1 * variance1;
sum3 += variance2 * variance2;
index1++;
}
denominator = Math.Sqrt(sum2 * sum3);
if (denominator == 0)
{
return(0); // avoid divide-by-zero error; not really the correct result (actual correlation is undefined)
}
else
{
return(sum1 / denominator);
}
}
private double SyncedResidualCorrelation(PriceSeries inputSeries1, SyncedDataSeries inputSeries2, int corrPeriod)
// Correlation of residuals (residual = error = difference between actual values and linear regression line)
{
int index1 = 0;
double[] residualArray1 = new double[corrPeriod];
double[] residualArray2 = new double[corrPeriod];
double[] dataArray1 = new double[corrPeriod];
double[] dataArray2 = new double[corrPeriod];
for (int counter = corrPeriod - 1; counter >= 0; counter--)
{
while (!inputSeries2.Synced[index1]) //Find next synced Bar
{
index1++;
}
dataArray1[counter] = inputSeries1[index1];
dataArray2[counter] = inputSeries2[index1];
index1++;
}
KDResidual(dataArray1, corrPeriod, residualArray1);
KDResidual(dataArray2, corrPeriod, residualArray2);
// return(KDRankCorrelation(residualArray1,residualArray2,corrPeriod)); // maybe rank correlation of residuals would be better?
return(KDCorrelation(residualArray1, residualArray2, corrPeriod));
}
