Examples of com.opengamma.analytics.financial.pnl.SensitivityAndReturnDataBundle

      if (underlyingType != UnderlyingType.SPOT_PRICE) {
        throw new OpenGammaRuntimeException("Have hard-coded to only use delta; should not have anything with " + underlyingType + " as the underlying type");
      }
      tsReturns.put(underlyingType, returnCalculator.evaluate(sampledTS));
    }
    dataBundleArray[0] = new SensitivityAndReturnDataBundle(sensitivity, value, tsReturns);
    final DoubleTimeSeries<?> result = PNL_CALCULATOR.evaluate(dataBundleArray);
    // Please see http://jira.opengamma.com/browse/PLAT-2330 for information about the PROPERTY_PNL_CONTRIBUTIONS constant
    final ValueProperties properties = createValueProperties()
        .with(ValuePropertyNames.CURRENCY, currency)
        .with(ValuePropertyNames.SAMPLING_PERIOD, samplingPeriodName.iterator().next())

    CALC.evaluate(new SensitivityAndReturnDataBundle[] {null});
  }


  @Test(expectedExceptions = IllegalArgumentException.class)
  public void testThirdOrderSensitivity() {
    final SensitivityAndReturnDataBundle data = new SensitivityAndReturnDataBundle(new ValueGreekSensitivity(new ValueGreek(Greek.SPEED), "A"), 10,
        Collections.<UnderlyingType, DoubleTimeSeries<?>> singletonMap(UnderlyingType.SPOT_PRICE, ImmutableInstantDoubleTimeSeries.of(new long[] {1},
            new double[] {1})));
    CALC.evaluate(data);
  }

Related Classes of com.opengamma.analytics.financial.pnl.SensitivityAndReturnDataBundle

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