Re: [ojAlgo-user] Markowitz Problem 2 :)
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Re: [ojAlgo-user] Markowitz Problem 2 :)
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From: Anders P. <an...@op...> - 2013-04-04 20:30:08
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The covariance matrix is not symmetric positive semidefinite.
Eigenvalues: [(0.4906530283552536 + 0.0i), (0.015721604173945955 + 0.0i), (0.010461976347998022 + 0.0i), (0.00722515181081578 + 0.0i), (0.0052806179437730125 + 0.0i), (0.004434033531049306 + 0.0i), (0.06071148162510361 + 0.0i), (0.05520353517789536 + 0.0i), (0.03098136247025044 + 0.0i), (0.024699548816013137 + 0.0i), (-0.007604829902151985 + 0.0i), (0.0010364796500534224 + 0.0i), (0.0 + 0.0i)]
If you want you can try calling: marketEquilibrium.clean();
/Anders
On 4 apr 2013, at 16:15, Matteo Baccan <mat...@gm...> wrote:
> Hi
>
> we have a second problem with MarkowitzModel.
> I have produced a little source that explain the problem.
>
> The problem is similar with the previous: 3 different TargetReturn 2 ok and 1 ko-
>
> This is the source that reproduce the problem
>
> ---------8<--------------8<--------------8<--------------8<--------------8<-----
> //package org.ojalgo.finance.portfolio;
>
> import java.math.BigDecimal;
> import java.util.List;
>
> import org.ojalgo.matrix.BasicMatrix;
> import org.ojalgo.matrix.BigMatrix;
> import org.ojalgo.matrix.store.BigDenseStore;
> import org.ojalgo.matrix.store.MatrixStore;
> import org.ojalgo.optimisation.Optimisation.State;
>
> import org.ojalgo.finance.portfolio.MarketEquilibrium;
> import org.ojalgo.finance.portfolio.MarkowitzModel;
>
> public class MarkowitzProblems2 {
>
> public static void main(final String[] args) {
>
> //BigDecimal nTarget = new BigDecimal("0.07"); // OK
> //0.0401
> //0.0
> //0.0
> //0.0
> //0.0239
> //0.0
> //0.0051
> //0.0
> //0.5305
> //0.1669
> //0.0
> //0.0335
> //0.2
>
> BigDecimal nTarget = new BigDecimal("0.08"); // ERROR
> // 0.0828
> // 0.0164
> // 0.0
> // 0.0
> // 0.0501
> // 0.0
> // -0.0396 -> Out of Weight Range
> // 0.0
> // 0.5876
> // 0.1908
> // -0.0049 -> Out of Weight Range
> // 0.0
> // 0.1169
>
> //BigDecimal nTarget = new BigDecimal("0.09"); // OK
> //0.0788
> //0.0045
> //0.0
> //0.0
> //0.0
> //0.0
> //0.0711
> //0.0
> //0.6272
> //0.1628
> //0.0057
> //0.0
> //0.05
>
> final double[][] cm=
> {{0.04206601, 0.044550845724, 0.048217369200, 0.054350966740, 0.022460320512, 0.055208551370, 0.034165558000, 0.029414658518, -0.000907567500, -0.003266560017, 0.011408652633, 0.007174996892, 0},
> {0.044550845724, 0.06796449, 0.063983606214, 0.072022499274, 0.032393205504, 0.085397746665, 0.046597518000, 0.040498055664, -0.001203130500, -0.003712871151, 0.016252486404, 0..008933472075, 0},
> {0.048217369200, 0.063983606214, 0.09084196, 0.096768635348, 0.043186328064, 0.083969449256, 0.054541344000, 0.049330020454, -0.001261359000, -0.004770776208, 0.023684614800, 0.016492134802, 0},
> {0.054350966740, 0.072022499274, 0.096768635348, 0.11874916, 0.039110390784, 0.091360338216, 0.058037532000, 0.051565647644, -0.001011401000, -0.004914519792, 0.024900113692, 0..014709412962, 0},
> {0.022460320512, 0.032393205504, 0.043186328064, 0.039110390784, 0.05308416, 0.064832995584, 0.040674816000, 0.041904582912, -0.001357056000, -0.003786856704, 0.018876923136, 0.017478379008, 0},
> {0.055208551370, 0.085397746665, 0.083969449256, 0.091360338216, 0.064832995584, 0.14661241, 0.060023404000, 0.054428675966, -0.000761971000, -0.004890659172, 0.020088021436, 0..009159105844, 0},
> {0.034165558000, 0.046597518000, 0.054541344000, 0.058037532000, 0.040674816000, 0.060023404000, 0.04000000, 0.030711460000, -0.001110000000, -0.003517058000, 0.013415070000, 0.007178534000, 0},
> {0.029414658518, 0.040498055664, 0.049330020454, 0.051565647644, 0.041904582912, 0.054428675966, 0.030711460000, 0.08300161, 0.000404780500, -0.001591573878, 0.020639653979, 0.010983694379, 0},
> {-0.000907567500, -0.001203130500, -0.001261359000, -0.001011401000, -0.001357056000, -0.000761971000, -0.001110000000, 0.000404780500, 0.00250000, 0.002084702500, 0.000854111500, 0.000385734000, 0},
> {-0.003266560017, -0.003712871151, -0.004770776208, -0.004914519792, -0.003786856704, -0.004890659172, -0.003517058000, -0.001591573878, 0.002084702500, 0.00426409, 0.000608437974, 0.001034468234, 0},
> {0.011408652633, 0.016252486404, 0.023684614800, 0.024900113692, 0.018876923136, 0.020088021436, 0.013415070000, 0.020639653979, 0.000854111500, 0.000608437974, 0.03500641, 0.003756060565, 0},
> {0.007174996892, 0.008933472075, 0.016492134802, 0.014709412962, 0.017478379008, 0.009159105844, 0.007178534000, 0.010983694379, 0.000385734000, 0.001034468234, 0.003756060565, 0.01471369, 0},
> {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}
> ;
>
> final int assetNum = cm.length;
>
> final int row = cm.length;
> if (row > 0) {
> final int col = cm[0].length;
> final MatrixStore<BigDecimal> a = BigDenseStore.FACTORY.makeZero(row, col);
> BasicMatrix covariances = BigMatrix.FACTORY.copy(a);
>
> for (int i = 0; i < row; i++) {
> for (int j = 0; j < col; j++) {
> covariances = covariances.replace(i, j, cm[i][j]);
> }
> }
>
> final double nRisk = 1000.0;
> final BigDecimal riskAversion = new BigDecimal(nRisk);
> final MarketEquilibrium marketEquilibrium = new MarketEquilibrium(covariances, riskAversion);
>
> final MatrixStore<BigDecimal> ret_matrix = BigDenseStore.FACTORY.makeZero(assetNum, 1);
> BasicMatrix expectedExcessReturns1 = BigMatrix.FACTORY.copy(ret_matrix);
>
> expectedExcessReturns1 = expectedExcessReturns1.replace(0, 0, 0.1389);
> expectedExcessReturns1 = expectedExcessReturns1.replace(1, 0, 0.1545);
> expectedExcessReturns1 = expectedExcessReturns1.replace(2, 0, 0.0736);
> expectedExcessReturns1 = expectedExcessReturns1.replace(3, 0, 0.0648);
> expectedExcessReturns1 = expectedExcessReturns1.replace(4, 0, 0.0915);
> expectedExcessReturns1 = expectedExcessReturns1.replace(5, 0, 0.1802);
> expectedExcessReturns1 = expectedExcessReturns1.replace(6, 0, 0.1331);
> expectedExcessReturns1 = expectedExcessReturns1.replace(7, 0, 0.0816);
> expectedExcessReturns1 = expectedExcessReturns1.replace(8, 0, 0.0874);
> expectedExcessReturns1 = expectedExcessReturns1.replace(9, 0, 0.0829);
> expectedExcessReturns1 = expectedExcessReturns1.replace(10, 0, 0.1038);
> expectedExcessReturns1 = expectedExcessReturns1.replace(11, 0, 0.0759);
> expectedExcessReturns1 = expectedExcessReturns1.replace(12, 0, 0.0000);
>
> final MarkowitzModel markowitzModel = new MarkowitzModel(marketEquilibrium, expectedExcessReturns1);
>
> markowitzModel.setLowerLimit(0, new BigDecimal(0.0000));
> markowitzModel.setUpperLimit(0, new BigDecimal(1.0000));
> markowitzModel.setLowerLimit(1, new BigDecimal(0.0000));
> markowitzModel.setUpperLimit(1, new BigDecimal(1.0000));
> markowitzModel.setLowerLimit(2, new BigDecimal(0.0000));
> markowitzModel.setUpperLimit(2, new BigDecimal(1.0000));
> markowitzModel.setLowerLimit(3, new BigDecimal(0.0000));
> markowitzModel.setUpperLimit(3, new BigDecimal(1.0000));
> markowitzModel.setLowerLimit(4, new BigDecimal(0.0000));
> markowitzModel.setUpperLimit(4, new BigDecimal(1.0000));
> markowitzModel.setLowerLimit(5, new BigDecimal(0.0000));
> markowitzModel.setUpperLimit(5, new BigDecimal(1.0000));
> markowitzModel.setLowerLimit(6, new BigDecimal(0.0000));
> markowitzModel.setUpperLimit(6, new BigDecimal(1.0000));
> markowitzModel.setLowerLimit(7, new BigDecimal(0.0000));
> markowitzModel.setUpperLimit(7, new BigDecimal(1.0000));
> markowitzModel.setLowerLimit(8, new BigDecimal(0.0000));
> markowitzModel.setUpperLimit(8, new BigDecimal(1.0000));
> markowitzModel.setLowerLimit(9, new BigDecimal(0.0000));
> markowitzModel.setUpperLimit(9, new BigDecimal(1.0000));
> markowitzModel.setLowerLimit(10, new BigDecimal(0.0000));
> markowitzModel.setUpperLimit(10, new BigDecimal(1.0000));
> markowitzModel.setLowerLimit(11, new BigDecimal(0.0000));
> markowitzModel.setUpperLimit(11, new BigDecimal(1.0000));
> markowitzModel.setLowerLimit(12, new BigDecimal(0.0500));
> markowitzModel.setUpperLimit(12, new BigDecimal(0.2000));
>
> final boolean bShort = false;
> markowitzModel.setShortingAllowed(bShort);
> markowitzModel.setTargetReturn(nTarget);
>
> final List<BigDecimal> re = markowitzModel.getWeights();
>
> final State tmpOptState = markowitzModel.getOptimisationState();
>
> for (int nn = 0; nn < re.size(); nn++) {
> System.out.println(re.get(nn));
> }
> }
> }
>
> }
> ---------8<--------------8<--------------8<--------------8<--------------8<-----
>
>
>
> All the best
> Matteo Baccan
>
>
>
> --
> Matteo Baccan
> http://www.baccan.it
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