public void ChartWeights()
{
Vector expected = new DenseVector (new double [] { 0.079, 0.079, 0.09, 0.071 });
Matrix correlations = new DenseMatrix(new double[,] { { 1.0, 0F, 0F, 0F }, { 0.24, 1.0, 0F, 0F }, { 0.25, 0.47, 1.0, 0F }, { 0.22, 0.14, 0.25, 1.0 } });
Vector stdDeviations = new DenseVector(new double[] { 0.195, 0.182, 0.183, 0.165 });
RiskMinimizationFormulation.RiskMinimization model = new RiskMinimizationFormulation.RiskMinimization(expected, correlations, stdDeviations);
var range = ListModule.OfSeq(Enumerable.Range(50, 120).Where(e => e % 5 == 0).Select(e => (double)e / 1000D));
model.ChartOptimalWeights(range, new string [] {"Australia", "Austria", "Belgium", "Canada"});
}
public void ChartStd()
{
Vector expected = new DenseVector(new double[] { 0.079, 0.079, 0.09, 0.071 });
Matrix correlations = new DenseMatrix(new double[,] { { 1.0, 0F, 0F, 0F }, { 0.24, 1.0, 0F, 0F }, { 0.25, 0.47, 1.0, 0F }, { 0.22, 0.14, 0.25, 1.0 } });
Vector stdDeviations = new DenseVector(new double[] { 0.195, 0.182, 0.183, 0.165 });
RiskMinimizationFormulation.RiskMinimization model = new RiskMinimizationFormulation.RiskMinimization(expected, correlations, stdDeviations);
var range = ListModule.OfSeq(Enumerable.Range(50, 120).Where(e => e % 5 == 0).Select(e => (double)e / 1000D));
model.ChartStandardDeviation(range);
}
