Re: [ojAlgo-user] Markowitz optimisation
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Re: [ojAlgo-user] Markowitz optimisation
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From: Arthur M. <art...@be...> - 2008-01-24 12:11:08
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Hi Anders,
I've run some more tests and I get a different NullPointerException on diff=
erent data.
If I set the variable upper bounds to "1.00" then it works but if I set the=
m to "0.35" as in this example then I get an error. Could you have a look =
please. The underlying code seems to set the upper bounds to "0.30" when p=
assing in "1.00" but leaves as is with "0.35" which I think is the max poss=
ible upper bounds.
regards
Arthur
public void testojAlgo3()
{
// create expected returns matrix
PrimitiveMatrix expectedReturnsMatrix =3D new PrimitiveMatrix(new double[=
][] { {10.012158}, {9.996046}, {10.000744}, {9.990585}, {9.998392}, {9.9966=
14}, {10.010531}, {10.001401}, {9.997447}, {9.993817}, {9.998537}, {9.99574=
1}, {9.987224}, {9.992392}});
// create covariance matrix
PrimitiveMatrix covarianceMatrix =3D new PrimitiveMatrix(new double[][] {=
{0.0013191354374342357, 7.786471466322114E-5, -3.810886655309235E-5, -2.281=
02405899103E-4, -1.2589115740653127E-4, -1.3247692268411991E-5, 1.422624656=
557158E-4, -2.7176361887359125E-5, 8.675127894495302E-5, -8.116577287090551=
E-5, -8.468380774247271E-6, 4.930080166695193E-5, -2.774138231533918E-4, -3=
.148322898570031E-5},
{7.786471466322114E-5, 0.001028250547816086, 8.986425197170406E-4, -1.0=
341435238579975E-5, 6.472902968147139E-4, 2.9014435841747375E-4, 1.06404144=
44602855E-4, 5.638694128451113E-4, 6.024515366195699E-4, -1.094867665517237=
E-4, 6.177221606260711E-6, -5.682215091954099E-5, 2.7178074500896235E-4, 0.=
0010146062950574643},
{-3.810886655309235E-5, 8.986425197170406E-4, 0.0012477403456464075, -1=
.8104847201530489E-4, 9.299199981666304E-4, 3.486383951982303E-4, 1.0246402=
606579107E-4, 7.009722990366382E-4, 6.545695073447614E-4, -1.16809691715001=
55E-4, 7.123493385355658E-5, 1.559414390174896E-5, 1.972605480880284E-4, 9.=
368808845809186E-4},
{-2.28102405899103E-4, -1.0341435238579975E-5, -1.8104847201530489E-4, =
6.250793590180099E-4, -5.4721911720097E-6, 1.3081826023829458E-4, -5.644046=
856412501E-5, -1.1282043806099452E-5, -6.729835202722053E-5, 1.392968154273=
7307E-4, 3.698155248637573E-6, 5.0269944317023966E-5, 5.344931460074395E-4,=
-1.1654882792112444E-4},
{-1.2589115740653127E-4, 6.472902968147139E-4, 9.299199981666304E-4, -5=
.4721911720097E-6, 0.001181357476541527, 3.0334522038028824E-4, 2.698384049=
7611894E-4, 6.983493701701867E-4, 5.68816790613126E-4, -7.899505299987754E-=
5, 1.05074262063586E-5, 1.137295188785598E-4, 1.9732025136606058E-4, 6.6313=
30613471645E-4},
{-1.3247692268411991E-5, 2.9014435841747375E-4, 3.486383951982303E-4, 1=
.3081826023829458E-4, 3.0334522038028824E-4, 3.372068413122505E-4, 1.106746=
8759384309E-4, 2.6589126866881173E-4, 2.1364931019670806E-4, -4.20123947252=
0589E-5, 2.32769639721745E-5, 5.847559594073046E-6, 1.9925897592339058E-4, =
1.9671375386540353E-4},
{1.422624656557158E-4, 1.0640414444602855E-4, 1.0246402606579107E-4, -5=
.644046856412501E-5, 2.6983840497611894E-4, 1.1067468759384309E-4, 0.001484=
755064835215, 1.2295961703024863E-4, 1.0843198781689372E-4, -2.129232829431=
3923E-5, -4.152686600769749E-6, 1.163599038579726E-4, -3.14739599261259E-4,=
2.4519847977412686E-4},
{-2.7176361887359125E-5, 5.638694128451113E-4, 7.009722990366382E-4, -1=
.1282043806099452E-5, 6.983493701701867E-4, 2.6589126866881173E-4, 1.229596=
1703024863E-4, 5.563328439145604E-4, 4.4816730200338125E-4, -3.472983281400=
7256E-5, -6.028818604193519E-7, 3.192976987126335E-5, 1.7402262469809026E-4=
, 5.182632389125651E-4},
{8.675127894495302E-5, 6.024515366195699E-4, 6.545695073447614E-4, -6.7=
29835202722053E-5, 5.68816790613126E-4, 2.1364931019670806E-4, 1.0843198781=
689372E-4, 4.4816730200338125E-4, 6.277134808325468E-4, -4.988229718603287E=
-5, -5.5018781802344255E-6, -1.3231260300518203E-5, 8.214207901880769E-5, 5=
.841470978796527E-4},
{-8.116577287090551E-5, -1.094867665517237E-4, -1.1680969171500155E-4, =
1.3929681542737307E-4, -7.899505299987754E-5, -4.201239472520589E-5, -2.129=
2328294313923E-5, -3.4729832814007256E-5, -4.988229718603287E-5, 3.51526926=
12068785E-4, -9.358092257358399E-6, 4.962216896551324E-6, 1.291957229930161=
E-4, -1.5046975508620905E-4},
{-8.468380774247271E-6, 6.177221606260711E-6, 7.123493385355658E-5, 3.6=
98155248637573E-6, 1.05074262063586E-5, 2.32769639721745E-5, -4.15268660076=
9749E-6, -6.028818604193519E-7, -5.5018781802344255E-6, -9.358092257358399E=
-6, 4.8495980378967104E-5, 1.1704645004909169E-5, 1.814918597253607E-5, 1.2=
448218299234062E-5},
{4.930080166695193E-5, -5.682215091954099E-5, 1.559414390174896E-5, 5.0=
269944317023966E-5, 1.137295188785598E-4, 5.847559594073046E-6, 1.163599038=
579726E-4, 3.192976987126335E-5, -1.3231260300518203E-5, 4.962216896551324E=
-6, 1.1704645004909169E-5, 1.802684481609152E-4, 1.0475986793792914E-5, -4.=
113641419540392E-5},
{-2.774138231533918E-4, 2.7178074500896235E-4, 1.972605480880284E-4, 5.=
344931460074395E-4, 1.9732025136606058E-4, 1.9925897592339058E-4, -3.147395=
99261259E-4, 1.7402262469809026E-4, 8.214207901880769E-5, 1.291957229930161=
E-4, 1.814918597253607E-5, 1.0475986793792914E-5, 7.843917688960864E-4, 1.2=
31995848356005E-4},
{-3.148322898570031E-5, 0.0010146062950574643, 9.368808845809186E-4, -1=
.1654882792112444E-4, 6.631330613471645E-4, 1.9671375386540353E-4, 2.451984=
7977412686E-4, 5.182632389125651E-4, 5.841470978796527E-4, -1.5046975508620=
905E-4, 1.2448218299234062E-5, -4.113641419540392E-5, 1.231995848356005E-4,=
0.0011885193322126312}});
// 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("0.05"));
// require no more than 80% allocation to each asset
tmpVariables[i].setUpperLimit(new BigDecimal("0.35"));
// tmpVariables[i].setUpperLimit(new BigDecimal("1.00"));
}
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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