Examples of evaluate()

Examples of com.opengamma.analytics.financial.interestrate.MultipleYieldCurveFinderIRSJacobian.evaluate()

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            new FXMatrix(currency));
        final NewtonVectorRootFinder rootFinder = new BroydenVectorRootFinder(absoluteTolerance, relativeTolerance, iterations, decomposition);
        final Function1D<DoubleMatrix1D, DoubleMatrix1D> curveCalculator = new MultipleYieldCurveFinderFunction(data, PAR_SPREAD_RATE_CALCULATOR);
        final Function1D<DoubleMatrix1D, DoubleMatrix2D> jacobianCalculator = new MultipleYieldCurveFinderIRSJacobian(data, PAR_SPREAD_RATE_SENSITIVITY_CALCULATOR);
        final double[] fittedYields = rootFinder.getRoot(curveCalculator, jacobianCalculator, new DoubleMatrix1D(initialRatesGuess.toDoubleArray())).getData();
        final DoubleMatrix2D jacobianMatrix = jacobianCalculator.evaluate(new DoubleMatrix1D(fittedYields));
        int i = 0;
        for (final String curveName : curveNames) {
          final Integer offset = nodesPerCurve.get(curveName);
          if (offset == null) {
            continue;
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Examples of com.opengamma.analytics.financial.interestrate.MultipleYieldCurveFinderJacobian.evaluate()

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      final MultipleYieldCurveFinderDataBundle data = new MultipleYieldCurveFinderDataBundle(derivatives, r, knownCurve, curveNodes, interpolators, useFiniteDifference, fxMatrix);
      final NewtonVectorRootFinder rootFinder = new BroydenVectorRootFinder(absoluteTolerance, relativeTolerance, iterations, decomposition);
      final Function1D<DoubleMatrix1D, DoubleMatrix1D> curveCalculator = new MultipleYieldCurveFinderFunction(data, PAR_RATE_CALCULATOR);
      final Function1D<DoubleMatrix1D, DoubleMatrix2D> jacobianCalculator = new MultipleYieldCurveFinderJacobian(data, PAR_RATE_SENSITIVITY_CALCULATOR);
      final double[] fittedYields = rootFinder.getRoot(curveCalculator, jacobianCalculator, new DoubleMatrix1D(r)).getData();
      final DoubleMatrix2D jacobianMatrix = jacobianCalculator.evaluate(new DoubleMatrix1D(fittedYields));
      final YieldCurve impliedDepositCurve = new YieldCurve(impliedDepositCurveName, InterpolatedDoublesCurve.from(t, fittedYields, interpolator));
      final ValueSpecification curveSpec = new ValueSpecification(YIELD_CURVE, target.toSpecification(), resultCurveProperties);
      final ValueSpecification jacobianSpec = new ValueSpecification(YIELD_CURVE_JACOBIAN, target.toSpecification(), resultJacobianProperties);
      return Sets.newHashSet(new ComputedValue(curveSpec, impliedDepositCurve), new ComputedValue(jacobianSpec, jacobianMatrix));
    }
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Examples of com.opengamma.analytics.financial.model.finitedifference.ExponentialMeshing.evaluate()

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    final PDEGrid1D[] grid;
    final double[] theta;

    if (_useBurnin) {
      final int tBurnNodes = (int) Math.max(2, timeNodes * _burninFrac);
      final double dt = tMesh.evaluate(1) - tMesh.evaluate(0);
      final double tBurn = tBurnNodes * dt * dt;
      final MeshingFunction tBurnMesh = new ExponentialMeshing(0, tBurn, tBurnNodes, 0.0);
      tMesh = new ExponentialMeshing(tBurn, t, timeNodes - tBurnNodes, lambda);
      grid = new PDEGrid1D[2];
      grid[0] = new PDEGrid1D(tBurnMesh, xMesh);
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Examples of com.opengamma.analytics.financial.model.finitedifference.HyperbolicMeshing.evaluate()

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      timeGrid[n] = timeMesh.evaluate(n);
    }

    final double[] spaceGrid = new double[xNodes];
    for (int i = 0; i < xNodes; i++) {
      spaceGrid[i] = spaceMesh.evaluate(i);
    }
    final PDEGrid1D grid = new PDEGrid1D(timeGrid, spaceGrid);

    final PDEResults1D[] res = solver.solve(DATA1, DATA2, grid, LOWER, UPPER, LOWER, UPPER, null);
    final PDEFullResults1D res1 = (PDEFullResults1D) res[0];
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Examples of com.opengamma.analytics.financial.model.finitedifference.MeshingFunction.evaluate()

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    final PDEGrid1D[] grid;
    final double[] theta;

    if (_useBurnin) {
      final int tBurnNodes = (int) Math.max(2, timeNodes * _burninFrac);
      final double dt = tMesh.evaluate(1) - tMesh.evaluate(0);
      final double tBurn = tBurnNodes * dt * dt;
      final MeshingFunction tBurnMesh = new ExponentialMeshing(0, tBurn, tBurnNodes, 0.0);
      tMesh = new ExponentialMeshing(tBurn, t, timeNodes - tBurnNodes, lambda);
      grid = new PDEGrid1D[2];
      grid[0] = new PDEGrid1D(tBurnMesh, xMesh);
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Examples of com.opengamma.analytics.financial.riskreward.JensenAlphaCalculator.evaluate()

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    final DoubleTimeSeries<?>[] series = TimeSeriesIntersector.intersect(assetReturnTS, riskFreeReturnTS, marketReturnTS);
    assetReturnTS = series[0];
    riskFreeReturnTS = series[1];
    marketReturnTS = series[2];
    final JensenAlphaCalculator calculator = getCalculator(constraints.getValues(ValuePropertyNames.EXCESS_RETURN_CALCULATOR));
    final double alpha = calculator.evaluate(assetReturnTS, riskFreeReturnTS, beta, marketReturnTS);
    final ValueProperties resultProperties = getResultProperties(desiredValues.iterator().next());
    return Sets.newHashSet(new ComputedValue(new ValueSpecification(ValueRequirementNames.JENSENS_ALPHA, targetSpec, resultProperties), alpha));
  }

  @Override
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Examples of com.opengamma.analytics.financial.riskreward.SharpeRatioCalculator.evaluate()

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    DoubleTimeSeries<?>[] series = TimeSeriesIntersector.intersect(assetReturnTS, benchmarkReturnTS);
    assetReturnTS = series[0];
    benchmarkReturnTS = series[1];
    final SharpeRatioCalculator calculator = getCalculator(constraints.getValues(ValuePropertyNames.EXCESS_RETURN_CALCULATOR),
        constraints.getValues(ValuePropertyNames.STD_DEV_CALCULATOR));
    final double ratio = calculator.evaluate(assetReturnTS, benchmarkReturnTS);
    final ValueProperties resultProperties = getResultProperties(desiredValues.iterator().next());
    return Sets.newHashSet(new ComputedValue(new ValueSpecification(ValueRequirementNames.SHARPE_RATIO, targetSpec, resultProperties), ratio));
  }

  @Override
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Examples of com.opengamma.analytics.financial.riskreward.TotalRiskAlphaCalculator.evaluate()

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    assetReturnTS = series[0];
    marketReturnTS = series[1];
    riskFreeReturnTS = series[2];
    final TotalRiskAlphaCalculator calculator = getCalculator(constraints.getValues(ValuePropertyNames.MEAN_CALCULATOR),
        constraints.getValues(ValuePropertyNames.STD_DEV_CALCULATOR));
    final double tra = calculator.evaluate(assetReturnTS, riskFreeReturnTS, marketReturnTS);
    final ValueProperties resultProperties = getResultProperties(desiredValues.iterator().next());
    return Sets.newHashSet(new ComputedValue(new ValueSpecification(ValueRequirementNames.TOTAL_RISK_ALPHA, targetSpec, resultProperties), tra));
  }

  @Override
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Examples of com.opengamma.analytics.financial.riskreward.TreynorRatioCalculator.evaluate()

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    DoubleTimeSeries<?> riskFreeReturnTS = riskFreeRateTSObject.getTimeSeries().divide(100 * DAYS_PER_YEAR);
    DoubleTimeSeries<?>[] series = TimeSeriesIntersector.intersect(riskFreeReturnTS, assetReturnTS);
    riskFreeReturnTS = series[0];
    assetReturnTS = series[1];
    final TreynorRatioCalculator calculator = getCalculator(constraints.getValues(ValuePropertyNames.EXCESS_RETURN_CALCULATOR));
    final double ratio = calculator.evaluate(assetReturnTS, riskFreeReturnTS, beta);
    final ValueProperties resultProperties = getResultProperties(desiredValues.iterator().next());
    return Sets.newHashSet(new ComputedValue(new ValueSpecification(ValueRequirementNames.TREYNOR_RATIO, targetSpec, resultProperties), ratio));
  }

  @Override
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Examples of com.opengamma.analytics.financial.timeseries.analysis.AutocorrelationFunctionCalculator.evaluate()

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  @Test
  public void test() {
    final AutocovarianceFunctionCalculator autocovariance = new AutocovarianceFunctionCalculator();
    final AutocorrelationFunctionCalculator autocorrelation = new AutocorrelationFunctionCalculator();
    final double[] rhoAR = autocorrelation.evaluate(AR);
    final double[] rhoMA = autocorrelation.evaluate(MA);
    final double[] rhoARMAP0 = autocorrelation.evaluate(MODEL.getSeries(PHI, P, null, 0, DATES));
    final double[] rhoARMA0Q = autocorrelation.evaluate(MODEL.getSeries(null, 0, THETA, Q, DATES));
    final double eps = Math.sqrt(STD) + 0.01;
    for (int i = 0; i < 200; i++) {
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