Package com.opengamma.analytics.financial.timeseries.analysis

Examples of com.opengamma.analytics.financial.timeseries.analysis.DoubleTimeSeriesStatisticsCalculator

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    final double[] rho = new AutocorrelationFunctionCalculator().evaluate(MA);
    final double rho1 = PHI[1] / (1 - PHI[2]);
    assertEquals(rho[0], 1, 1e-16);
    assertEquals(rho[1], rho1, eps);
    assertEquals(rho[2], rho1 * PHI[1] + PHI[2], eps);
    final Double mean = new DoubleTimeSeriesStatisticsCalculator(new MeanCalculator()).evaluate(MA);
    assertEquals(mean, PHI[0] / (1 - PHI[1] - PHI[2]), eps);
  }
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        assertTrue(rho[i] > LIMIT);
      } else {
        assertTrue(rho[i] < LIMIT);
      }
    }
    final Double mean = new DoubleTimeSeriesStatisticsCalculator(new MeanCalculator()).evaluate(MA);
    assertEquals(mean, THETA[0], eps);
    final Double variance = new DoubleTimeSeriesStatisticsCalculator(new SampleVarianceCalculator()).evaluate(MA);
    double sum = 1;
    for (int i = 1; i <= ORDER; i++) {
      sum += THETA[i] * THETA[i];
    }
    assertEquals(variance, sum * STD * STD, eps);
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  private JensenAlphaCalculator getCalculator(final Set<String> excessReturnCalculatorNames) {
    if (excessReturnCalculatorNames == null || excessReturnCalculatorNames.isEmpty() || excessReturnCalculatorNames.size() != 1) {
      throw new OpenGammaRuntimeException("Missing or non-unique excess return calculator name: " + excessReturnCalculatorNames);
    }
    final Function<double[], Double> expectedExcessReturnCalculator = StatisticsCalculatorFactory.getCalculator(excessReturnCalculatorNames.iterator().next());
    final DoubleTimeSeriesStatisticsCalculator excessReturnCalculator = new DoubleTimeSeriesStatisticsCalculator(expectedExcessReturnCalculator);
    return new JensenAlphaCalculator(excessReturnCalculator, excessReturnCalculator, excessReturnCalculator); //TODO check that they can both be the same
  }
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      throw new OpenGammaRuntimeException("Missing or non-unique expected return calculator name: " + expectedReturnCalculatorNames);
    }
    if (stdDevCalculatorNames == null || stdDevCalculatorNames.isEmpty() || stdDevCalculatorNames.size() != 1) {
      throw new OpenGammaRuntimeException("Missing or non-unique standard deviation calculator name: " + stdDevCalculatorNames);
    }
    final DoubleTimeSeriesStatisticsCalculator expectedReturnCalculator =
        new DoubleTimeSeriesStatisticsCalculator(StatisticsCalculatorFactory.getCalculator(expectedReturnCalculatorNames.iterator().next()));
    final DoubleTimeSeriesStatisticsCalculator stdDevCalculator =
        new DoubleTimeSeriesStatisticsCalculator(StatisticsCalculatorFactory.getCalculator(stdDevCalculatorNames.iterator().next()));
    return new TotalRiskAlphaCalculator(expectedReturnCalculator, expectedReturnCalculator, expectedReturnCalculator, stdDevCalculator, stdDevCalculator);
  }
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      throw new OpenGammaRuntimeException("Missing or non-unique excess return calculator name: " + excessReturnCalculatorNames);
    }
    if (stdDevCalculatorNames == null || stdDevCalculatorNames.isEmpty() || stdDevCalculatorNames.size() != 1) {
      throw new OpenGammaRuntimeException("Missing or non-unique standard deviation calculator name: " + stdDevCalculatorNames);
    }
    final DoubleTimeSeriesStatisticsCalculator excessReturnCalculator =
        new DoubleTimeSeriesStatisticsCalculator(StatisticsCalculatorFactory.getCalculator(excessReturnCalculatorNames.iterator().next()));
    final DoubleTimeSeriesStatisticsCalculator stdDevCalculator =
        new DoubleTimeSeriesStatisticsCalculator(StatisticsCalculatorFactory.getCalculator(stdDevCalculatorNames.iterator().next()));
    return new SharpeRatioCalculator(WORKING_DAYS_PER_YEAR, excessReturnCalculator, stdDevCalculator);
  }
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      throw new OpenGammaRuntimeException("Missing or non-unique mean calculator name: " + meanCalculatorNames);
    }
    if (stdDevCalculatorNames == null || stdDevCalculatorNames.isEmpty() || stdDevCalculatorNames.size() != 1) {
      throw new OpenGammaRuntimeException("Missing or non-unique standard deviation calculator name: " + stdDevCalculatorNames);
    }
    final DoubleTimeSeriesStatisticsCalculator meanCalculator =
        new DoubleTimeSeriesStatisticsCalculator(StatisticsCalculatorFactory.getCalculator(meanCalculatorNames.iterator().next()));
    final DoubleTimeSeriesStatisticsCalculator stdDevCalculator =
        new DoubleTimeSeriesStatisticsCalculator(StatisticsCalculatorFactory.getCalculator(stdDevCalculatorNames.iterator().next()));
    return new NormalLinearVaRCalculator<DoubleTimeSeries<?>>(meanCalculator, stdDevCalculator);
  }
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  private TreynorRatioCalculator getCalculator(final Set<String> excessReturnCalculatorNames) {
    if (excessReturnCalculatorNames == null || excessReturnCalculatorNames.isEmpty() || excessReturnCalculatorNames.size() != 1) {
      throw new OpenGammaRuntimeException("Missing or non-unique excess return calculator name: " + excessReturnCalculatorNames);
    }
    final Function<double[], Double> expectedExcessReturnCalculator = StatisticsCalculatorFactory.getCalculator(excessReturnCalculatorNames.iterator().next());
    final DoubleTimeSeriesStatisticsCalculator excessReturnCalculator = new DoubleTimeSeriesStatisticsCalculator(expectedExcessReturnCalculator);
    return new TreynorRatioCalculator(excessReturnCalculator, excessReturnCalculator); //TODO check that they can both be the same
  }
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      throw new OpenGammaRuntimeException("Missing or non-unique covariance calculator name: " + covarianceCalculatorNames);
    }
    if (varianceCalculatorNames == null || varianceCalculatorNames.isEmpty() || varianceCalculatorNames.size() != 1) {
      throw new OpenGammaRuntimeException("Missing or non-unique variance calculator name: " + varianceCalculatorNames);
    }
    final DoubleTimeSeriesStatisticsCalculator covarianceCalculator =
        new DoubleTimeSeriesStatisticsCalculator(StatisticsCalculatorFactory.getCalculator(covarianceCalculatorNames.iterator().next()));
    final DoubleTimeSeriesStatisticsCalculator varianceCalculator =
        new DoubleTimeSeriesStatisticsCalculator(StatisticsCalculatorFactory.getCalculator(varianceCalculatorNames.iterator().next()));
    return new CAPMBetaCalculator(covarianceCalculator, varianceCalculator);
  }
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    Validate.notNull(kurtosisCalculatorName, "kurtosis calculator name");
    Validate.notNull(startDate, "start date");
    Validate.notNull(dataSource, "data source");
    Validate.notNull(field, "field");
    _returnCalculator = TimeSeriesReturnCalculatorFactory.getReturnCalculator(returnCalculatorName);
    _skewCalculator = new DoubleTimeSeriesStatisticsCalculator(StatisticsCalculatorFactory.getCalculator(skewCalculatorName));
    _kurtosisCalculator = new DoubleTimeSeriesStatisticsCalculator(StatisticsCalculatorFactory.getCalculator(kurtosisCalculatorName));
    _isPearson = Boolean.parseBoolean(isPearson);
    _startDate = LocalDate.parse(startDate);
    _dataSource = dataSource;
    _dataProvider = dataProvider;
    _field = field;
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Related Classes of com.opengamma.analytics.financial.timeseries.analysis.DoubleTimeSeriesStatisticsCalculator

  • com.opengamma.analytics.financial.timeseries.model.AutoregressiveTimeSeriesModelTest
  • com.opengamma.analytics.financial.timeseries.model.MovingAverageTimeSeriesModelTest
  • com.opengamma.financial.analytics.model.equity.portfoliotheory.CAPMBetaModelFunction
  • com.opengamma.financial.analytics.model.equity.portfoliotheory.JensenAlphaFunction
  • com.opengamma.financial.analytics.model.equity.portfoliotheory.SharpeRatioFunction
  • com.opengamma.financial.analytics.model.equity.portfoliotheory.TotalRiskAlphaFunction
  • com.opengamma.financial.analytics.model.equity.portfoliotheory.TreynorRatioFunction
  • com.opengamma.financial.analytics.model.option.HistoricalSkewKurtosisFunction
  • com.opengamma.financial.analytics.model.var.NormalHistoricalVaRFunction
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