public static NArray CorrelationMatrixToWeights(NArray correlationMatrix)
{
var nearestCorrelationMatrix = NearestCorrelationMatrix(correlationMatrix);
var cholesky = NMath.CholeskyDecomposition(nearestCorrelationMatrix);
// the weights are simply the Cholesky decomposition
return(cholesky);
}
private NArray CalculateSyntheticReturns(NArray correlationMatrix, int returnsCount)
{
var location = StorageLocation.Host;
var cholesky = NMath.CholeskyDecomposition(correlationMatrix);
var variates = new NArray(location, returnsCount, correlationMatrix.RowCount);
using (var stream = new RandomNumberStream(location))
{
var normal = new Normal(stream, 0, 1);
variates.FillRandom(normal);
}
return(variates * cholesky.Transpose());
}
public static void AddMultivariateModelWeightsProvider(Context context,
IList <string> identifiers, NArray correlationMatrix)
{
correlationMatrix = CorrelationHelper.NearestCorrelationMatrix(correlationMatrix);
var weightsCount = correlationMatrix.RowCount;
var weightsMatrix = NMath.CholeskyDecomposition(correlationMatrix).Transpose();
var weights = context.Data.AddCalibrationParametersProvider
(new WeightsProvider(weightsCount));
for (int i = 0; i < weightsMatrix.ColumnCount; ++i)
{
weights.AddValue(identifiers[i], weightsMatrix.Column(i));
}
}
private List <string> CreateTestWeightsProvider(Context context,
WeightsType weightsType, int returnsCount = 1000)
{
var correlationMatrix = context.Factory.CreateNArray(new double[, ] {
{ 1.0, 0.84, -0.42 },
{ 0.84, 1.0, 0.14 },
{ -0.42, 0.14, 1.0 }
});
correlationMatrix = CorrelationHelper.NearestCorrelationMatrix(correlationMatrix);
int weightsCount;
NArray weightsMatrix;
if (weightsType == WeightsType.Returns)
{
weightsCount = returnsCount;
weightsMatrix = CalculateSyntheticReturns(correlationMatrix, weightsCount);
}
else
{
weightsCount = correlationMatrix.RowCount;
weightsMatrix = NMath.CholeskyDecomposition(correlationMatrix);
}
var weights = context.Data.AddCalibrationParametersProvider
(new WeightsProvider(weightsCount));
var identifiers = Enumerable.Range(1, weightsMatrix.ColumnCount)
.Select(i => string.Format("TestFactor{0}", i)).ToList();
for (int i = 0; i < weightsMatrix.ColumnCount; ++i)
{
weights.AddValue(identifiers[i], weightsMatrix.Column(i));
}
return(identifiers);
}
