Re: [ojAlgo-user] Markowitz optimisation

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

Hi Anders,

I've been using the new version for a while and it has been working well on=
 many different constraints - thanks for all the work you've put in here.

Unfortunately I've got another issue with NullPointerExceptions.  I'd run t=
hrough the code myself but I don't understand the maths behind the constrai=
nts - hence my use of your library.

Could you have another look please

regards
Arthur





public void testojAlgo()
	{
		// create expected returns matrix
		PrimitiveMatrix expectedReturnsMatrix =3D new PrimitiveMatrix(new double[=
][] { {9.994620}, {10.011389}, {10.004353}, {9.998293}, {10.056851}, {9.997=
920}, {9.999011}, {10.050971}, {9.989124}, {9.989912}});
		// create covariance matrix
		PrimitiveMatrix covarianceMatrix =3D new PrimitiveMatrix(new double[][] {=
{0.014531344652473037,	4.444675045533674E-4,	0.007234717654072837,	-9.45531=
2097865225E-4,	0.0016345464996349748,	1.5256808879495097E-4,	0.002263258187=
49439,	0.003534367267672946,	-4.2669306842991344E-5,	6.902267133060073E-5},
			{4.444675045533674E-4,	0.008511422662647488,	0.0039821105759899845,	5.54=
3408872612397E-4,	-0.0015797828516888929,	1.3505400134130176E-4,	-1.5215492=
836142527E-4,	9.381119889780555E-4,	-4.5861204247023084E-4,	-2.422669450392=
1645E-5},
			{0.007234717654072837,	0.0039821105759899845,	0.031037646466036784,	-0.0=
022701157440735394,	-3.187028053841407E-4,	5.182461519304137E-4,	-3.6813402=
42039795E-4,	0.001526984686166616,	1.603885118040309E-4,	-1.359858314115312=
E-4},
			{-9.455312097865225E-4,	5.543408872612397E-4,	-0.0022701157440735394,	0.=
005637141895898889,	7.89377521930992E-4,	5.004781934410127E-4,	-9.792219671=
72284E-4,	-2.912861228906251E-4,	7.842012412867984E-4,	0.001086680880742953=
2},
			{0.0016345464996349748,	-0.0015797828516888929,	-3.187028053841407E-4,	7=
.89377521930992E-4,	0.03263062480163135,	6.041130577612135E-5,	6.8834890967=
10362E-4,	0.010830183513887228,	0.0016425608963272292,	0.002481787652249504=
},
			{1.5256808879495097E-4,	1.3505400134130176E-4,	5.182461519304137E-4,	5.0=
04781934410127E-4,	6.041130577612135E-5,	0.001733612375709255,	2.8742157640=
452992E-5,	-3.654534740999083E-4,	9.896178753749563E-5,	-1.703972415991329E=
-5},
			{0.00226325818749439,	-1.5215492836142527E-4,	-3.681340242039795E-4,	-9.=
79221967172284E-4,	6.883489096710362E-4,	2.8742157640452992E-5,	0.008167191=
690212253,	-0.0010075092076978207,	-4.293010139199468E-4,	-6.61564097833129=
2E-4},
			{0.003534367267672946,	9.381119889780555E-4,	0.001526984686166616,	-2.91=
2861228906251E-4,	0.010830183513887228,	-3.654534740999083E-4,	-0.001007509=
2076978207,	0.013796198054188104,	0.0013541164478127973,	-2.240108672066916=
7E-5},
			{-4.2669306842991344E-5,	-4.5861204247023084E-4,	1.603885118040309E-4,	7=
.842012412867984E-4,	0.0016425608963272292,	9.896178753749563E-5,	-4.293010=
139199468E-4,	0.0013541164478127973,	0.004743485149287524,	0.00114642932177=
08277},
			{6.902267133060073E-5,	-2.4226694503921645E-5,	-1.359858314115312E-4,	0.=
0010866808807429532,	0.002481787652249504,	-1.703972415991329E-5,	-6.615640=
978331292E-4,	-2.2401086720669167E-5,	0.0011464293217708277,	0.007398229661=
528494}});

		// 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 8% allocation to each asset
			tmpVariables[i].setLowerLimit(new BigDecimal("0.08"));
			// require no more than 12% allocation to each asset
			tmpVariables[i].setUpperLimit(new BigDecimal("0.12"));
		}

		QuadraticModel quadModel =3D new QuadraticModel(tmpVariables);

		Expression tmpExpr =3D quadModel.addCorrelationExpression("Variance", cov=
arianceMatrix.toBigStore().toArray());
		BigDecimal riskAversion =3D BigMath.PI.multiply(BigMath.E);
		tmpExpr.setCost(riskAversion.multiply(BigMath.HALF));

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

		// exception here...
		BasicMatrix bm =3D BigMatrix.FACTORY.buildColumnVector(quadModel.getDefau=
ltSolver().getSolution());
=09
		System.out.print(bm.toString());
	}


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