Examples with NumberContext org.ojalgo.type.context.NumberContext used on opensource projects

Example 1 with NumberContext

use of org.ojalgo.type.context.NumberContext in project ojAlgo-finance by optimatika.

the class FinanceUtilsTest method doTestCleaning.

private static void doTestCleaning(final double[][] original) {
    final NumberContext tmpEvalCntx = NumberContext.getGeneral(6, 12);
    final PrimitiveDenseStore tmpOriginal = PrimitiveDenseStore.FACTORY.rows(original);
    final SingularValue<Double> tmpSVD = SingularValue.make(tmpOriginal);
    tmpSVD.decompose(tmpOriginal);
    final double tmpRefCond = tmpSVD.getCondition();
    final int tmpRefRank = tmpSVD.getRank();
    final double tmpRefNorm = tmpSVD.getFrobeniusNorm();
    final PrimitiveMatrix tmpCorrelations = FinanceUtils.toCorrelations(tmpOriginal, true);
    final PrimitiveMatrix tmpVolatilities = FinanceUtils.toVolatilities(tmpOriginal, true);
    final PrimitiveMatrix tmpCovariances = FinanceUtils.toCovariances(tmpVolatilities, tmpCorrelations);
    tmpSVD.decompose(PrimitiveDenseStore.FACTORY.copy(tmpCovariances));
    final double tmpNewCond = tmpSVD.getCondition();
    final int tmpNewRank = tmpSVD.getRank();
    final double tmpNewNorm = tmpSVD.getFrobeniusNorm();
    TestUtils.assertTrue("Improved the condition", tmpNewCond <= tmpRefCond);
    TestUtils.assertTrue("Improved the rank", tmpNewRank >= tmpRefRank);
    TestUtils.assertEquals("Full rank", original.length, tmpNewRank);
    TestUtils.assertEquals("Roughly the same frob norm", tmpRefNorm, tmpNewNorm, tmpEvalCntx);
    if (DEBUG) {
        BasicLogger.debug("Original", tmpOriginal);
        BasicLogger.debug("Cleaned", tmpCovariances);
        BasicLogger.debug("Difference", tmpOriginal.subtract(PrimitiveDenseStore.FACTORY.copy(tmpCovariances)), tmpEvalCntx);
    }
}

Example 2 with NumberContext

use of org.ojalgo.type.context.NumberContext in project ojAlgo-finance by optimatika.

the class PortfolioProblems method testP20160608.

/**
 * <a href="https://github.com/optimatika/ojAlgo/issues/23">GitHub Issue 23</a> The problem was that since
 * the model allows shorting the pure profit maximisation is unbounded (initial LP). The algorithm did not
 * handle the case where "target" could be >= the max possible when shorting not allowed (bounded LP).
 */
@Test
public void testP20160608() {
    final BasicMatrix.Factory<PrimitiveMatrix> matrixFactory = PrimitiveMatrix.FACTORY;
    final PrimitiveMatrix cov = matrixFactory.rows(new double[][] { { 0.01, 0.0018, 0.0011 }, { 0.0018, 0.0109, 0.0026 }, { 0.0011, 0.0026, 0.0199 } });
    final PrimitiveMatrix ret = matrixFactory.columns(new double[] { 0.0427, 0.0015, 0.0285 });
    final MarketEquilibrium marketEquilibrium = new MarketEquilibrium(cov);
    final MarkowitzModel markowitz = new MarkowitzModel(marketEquilibrium, ret);
    markowitz.setShortingAllowed(true);
    markowitz.setTargetReturn(BigDecimal.valueOf(0.0427));
    List<BigDecimal> tmpWeights = markowitz.getWeights();
    TestUtils.assertTrue(markowitz.optimiser().getState().isFeasible());
    final NumberContext tmpTestPrecision = StandardType.PERCENT.newPrecision(4);
    // Solution reachable without shorting, but since it is allowed the optimal solution is different
    // 0.82745
    TestUtils.assertEquals(0.82745, tmpWeights.get(0).doubleValue(), tmpTestPrecision);
    // -0.09075
    TestUtils.assertEquals(-0.09075, tmpWeights.get(1).doubleValue(), tmpTestPrecision);
    // 0.26329
    TestUtils.assertEquals(0.26329, tmpWeights.get(2).doubleValue(), tmpTestPrecision);
    TestUtils.assertEquals(0.0427, markowitz.getMeanReturn(), tmpTestPrecision);
    TestUtils.assertEquals(0.0084, markowitz.getReturnVariance(), tmpTestPrecision);
    // Also verify that it's posible to reach 10% return by shorting
    markowitz.setTargetReturn(BigDecimal.valueOf(0.1));
    TestUtils.assertEquals(0.1, markowitz.getMeanReturn(), tmpTestPrecision);
    TestUtils.assertTrue(markowitz.optimiser().getState().isFeasible());
    // Min risk portfolio, very high risk aversion means minimum risk.
    markowitz.setTargetReturn(null);
    markowitz.setRiskAversion(new BigDecimal(1000000));
    tmpWeights = markowitz.getWeights();
    TestUtils.assertTrue(markowitz.optimiser().getState().isFeasible());
    // 0.4411
    TestUtils.assertEquals(0.4411, tmpWeights.get(0).doubleValue(), tmpTestPrecision);
    // 0.3656
    TestUtils.assertEquals(0.3656, tmpWeights.get(1).doubleValue(), tmpTestPrecision);
    // 0.1933
    TestUtils.assertEquals(0.1933, tmpWeights.get(2).doubleValue(), tmpTestPrecision);
}

Example 3 with NumberContext

use of org.ojalgo.type.context.NumberContext in project ojAlgo by optimatika.

the class P20030512Case method setUp.

@BeforeEach
@Override
public void setUp() {
    DEFINITION = new NumberContext(7, 12);
    EVALUATION = new NumberContext(5, 6);
    myBigAA = P20030512Case.getProblematic();
    myBigAX = BasicMatrixTest.getIdentity(myBigAA.countColumns(), myBigAA.countColumns(), DEFINITION);
    myBigAB = myBigAA;
    myBigI = BasicMatrixTest.getIdentity(myBigAA.countRows(), myBigAA.countColumns(), DEFINITION);
    myBigSafe = BasicMatrixTest.getSafe(myBigAA.countRows(), myBigAA.countColumns(), DEFINITION);
    super.setUp();
}

Example 4 with NumberContext

use of org.ojalgo.type.context.NumberContext in project ojAlgo by optimatika.

the class P20030528Case method setUp.

@BeforeEach
@Override
public void setUp() {
    DEFINITION = new NumberContext(7, 1);
    EVALUATION = new NumberContext(7, 9);
    myBigAA = P20030528Case.getProblematic();
    myBigAX = BasicMatrixTest.getIdentity(myBigAA.countColumns(), myBigAA.countColumns(), DEFINITION);
    myBigAB = myBigAA;
    myBigI = BasicMatrixTest.getIdentity(myBigAA.countRows(), myBigAA.countColumns(), DEFINITION);
    myBigSafe = BasicMatrixTest.getSafe(myBigAA.countRows(), myBigAA.countColumns(), DEFINITION);
    super.setUp();
}

Example 5 with NumberContext

use of org.ojalgo.type.context.NumberContext in project ojAlgo by optimatika.

the class P20050125Case method setUp.

@BeforeEach
@Override
public void setUp() {
    DEFINITION = new NumberContext(7, 9);
    EVALUATION = new NumberContext(7, 6);
    myBigAA = P20050125Case.getProblematic();
    myBigAX = BasicMatrixTest.getIdentity(myBigAA.countColumns(), myBigAA.countColumns(), DEFINITION);
    myBigAB = myBigAA;
    myBigI = BasicMatrixTest.getIdentity(myBigAA.countRows(), myBigAA.countColumns(), DEFINITION);
    myBigSafe = BasicMatrixTest.getSafe(myBigAA.countRows(), myBigAA.countColumns(), DEFINITION);
    super.setUp();
}