Re: [ojAlgo-user] Markowitz optimisation

[Arthur M. <art...@be...>]

Hi Anders,

Here's an example that gives an exception.  Hopefully this code will retain=
 a semblance of formatting on emailing.

public class TestStats extends TestCase
{
public void testEfficientFrontier()
	{
		// create expected returns matrix
		PrimitiveMatrix expectedReturnsMatrix =3D new PrimitiveMatrix(new double[=
][] { { -0.007155942261937039 },
				{ -0.003665887902733331 }, { -0.004130184341000032 }, { -0.005639860515=
211043 },
				{ 0.0007211966666666817 }, { 0.0003258225000000077 }, { -0.005754291666=
666666 },
				{ -0.004264291666666667 }, { -0.0017500000000000003 } });
		// create covariance matrix
		PrimitiveMatrix covarianceMatrix =3D new PrimitiveMatrix(new double[][] {
				{  0.001561410465201063,     0.00006366128201274021,   -0.0001323096896=
759724,    0.0000909074052724909,   0.00003172000033558704,   0.00001955483=
223848944,   -0.00013771504482647386,  -0.00004858457275314645,  -0.0000129=
54723060403266 },
				{  0.00006366128201274021,   0.00016419786524761803,   -0.0000156628891=
1558343,  -0.00008688646089751923,  0.0000027349925543017186, 0.00000123561=
59598500247, -0.000024367796639005863, -0.000017576048221096555, -0.0000070=
052245518771815 },
				{ -0.0001323096896759724,   -0.00001566288911558343,    0.0001430155985=
985913,    0.00007675339168559199, -0.00007600590426518823,   0.00003297653=
8909267937,   0.00009520305608240259,   0.00007373075639042642,  -0.0000074=
77057858706954 },
				{  0.0000909074052724909,   -0.00008688646089751923,    0.0000767533916=
8559199,   0.000967519991100896,   -0.0000533460293834595,    0.00008665760=
416026126,    0.00014591175388747613,   0.0001232364989586903,    0.0001109=
7998789484925 },
				{  0.00003172000033558704,   0.0000027349925543017186, -0.0000760059042=
6518823,  -0.0000533460293834595,   0.000025267064307337795, -0.00003089584=
520279407,   -0.00005593123237578969,  -0.000017013960349712132,  0.0000013=
056146551724419 },
				{  0.00001955483223848944,   0.0000012356159598500247,  0.0000329765389=
09267937,  0.00008665760416026126, -0.00003089584520279407,   0.00016254994=
47274783,     0.00008242949058588471,   0.00010276895784859992,   0.0000005=
898510775862205 },
				{ -0.00013771504482647386,  -0.000024367796639005863,   0.0000952030560=
8240259,   0.00014591175388747613, -0.00005593123237578969,   0.00008242949=
058588471,    0.000560956958802083,     0.0002838794236862429,    0.0000914=
3821659482758 },
				{ -0.00004858457275314645,  -0.000017576048221096555,   0.0000737307563=
9042642,   0.0001232364989586903,  -0.000017013960349712132,  0.00010276895=
784859992,    0.0002838794236862429,    0.00021068964250359204,   0.0000446=
1044181034483 },
				{ -0.000012954723060403266, -0.0000070052245518771815, -0.0000074770578=
58706954,  0.00011097998789484925,  0.0000013056146551724419, 0.00000058985=
10775862205,  0.00009143821659482758,   0.00004461044181034483,   0.0000676=
1920797413792 } });

		MarketEquilibrium myMarket =3D new MarketEquilibrium(covarianceMatrix);

		// create asset variables - cost and weighting constraints
		Variable[] tmpVariables =3D new Variable[expectedReturnsMatrix.getRowDim(=
)];
		for (int i =3D 0; i < tmpVariables.length; i++)
		{
			tmpVariables[i] =3D new Variable("");
			tmpVariables[i].setCost(expectedReturnsMatrix.toBigDecimal(i, 0).negate(=
));
			// set the constraints on the asset weights
			// require at least a 2% allocation to each asset
			tmpVariables[i].setLowerLimit(new BigDecimal("0.02"));
			// require no more than 80% allocation to each asset
			tmpVariables[i].setUpperLimit(new BigDecimal("0.80"));
		}

		QuadraticModel quadModel =3D new QuadraticModel(tmpVariables);

		Expression tmpExpr =3D quadModel.addCorrelationExpression("Variance", cov=
arianceMatrix.toBigStore().toArray());
		BigDecimal tmpRiskAversion =3D myMarket.getRiskAversion();
		tmpExpr.setCost(tmpRiskAversion.multiply(BigMath.HALF));

		// set balance expression
		tmpExpr =3D quadModel.addSimpleWeightExpression("Balance");
		tmpExpr.setLowerLimit(BigMath.ONE);
		tmpExpr.setUpperLimit(BigMath.ONE);

		// exception here...
		BigMatrix.FACTORY.buildColumnVector(quadModel.getDefaultSolver().getSolut=
ion());
	}
}


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