CAPMFromRegressionModelFunction.java example

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/**
 * Copyright (C) 2009 - present by OpenGamma Inc. and the OpenGamma group of companies
 *
 * Please see distribution for license.
 */
package com.opengamma.financial.analytics.model.equity.portfoliotheory;

import java.util.HashSet;
import java.util.Set;

import org.apache.commons.lang.Validate;

import com.opengamma.OpenGammaRuntimeException;
import com.opengamma.analytics.financial.equity.capm.CAPMFromRegressionCalculator;
import com.opengamma.analytics.financial.timeseries.returns.TimeSeriesReturnCalculator;
import com.opengamma.analytics.financial.timeseries.returns.TimeSeriesReturnCalculatorFactory;
import com.opengamma.analytics.math.regression.LeastSquaresRegressionResult;
import com.opengamma.core.historicaltimeseries.HistoricalTimeSeries;
import com.opengamma.core.historicaltimeseries.HistoricalTimeSeriesSource;
import com.opengamma.core.value.MarketDataRequirementNames;
import com.opengamma.engine.ComputationTarget;
import com.opengamma.engine.ComputationTargetSpecification;
import com.opengamma.engine.function.AbstractFunction;
import com.opengamma.engine.function.FunctionCompilationContext;
import com.opengamma.engine.function.FunctionExecutionContext;
import com.opengamma.engine.function.FunctionInputs;
import com.opengamma.engine.target.ComputationTargetType;
import com.opengamma.engine.value.ComputedValue;
import com.opengamma.engine.value.ValueProperties;
import com.opengamma.engine.value.ValuePropertyNames;
import com.opengamma.engine.value.ValueRequirement;
import com.opengamma.engine.value.ValueRequirementNames;
import com.opengamma.engine.value.ValueSpecification;
import com.opengamma.financial.OpenGammaCompilationContext;
import com.opengamma.financial.OpenGammaExecutionContext;
import com.opengamma.financial.analytics.timeseries.DateConstraint;
import com.opengamma.financial.analytics.timeseries.HistoricalTimeSeriesBundle;
import com.opengamma.financial.analytics.timeseries.HistoricalTimeSeriesFunctionUtils;
import com.opengamma.financial.convention.ConventionBundle;
import com.opengamma.financial.convention.ConventionBundleSource;
import com.opengamma.financial.convention.InMemoryConventionBundleMaster;
import com.opengamma.id.ExternalId;
import com.opengamma.master.historicaltimeseries.HistoricalTimeSeriesResolutionResult;
import com.opengamma.master.historicaltimeseries.HistoricalTimeSeriesResolver;
import com.opengamma.timeseries.DoubleTimeSeries;

/**
 * 
 */
public class CAPMFromRegressionModelFunction extends AbstractFunction.NonCompiledInvoker {
  private static final double DAYS_IN_YEAR = 365.25;
  private static final CAPMFromRegressionCalculator CAPM_REGRESSION_MODEL = new CAPMFromRegressionCalculator();
  private static final ComputationTargetType TYPE = ComputationTargetType.POSITION.or(ComputationTargetType.PORTFOLIO_NODE);
  private final String _resolutionKey;

  public CAPMFromRegressionModelFunction(final String resolutionKey) {
    Validate.notNull(resolutionKey, "resolution key");
    _resolutionKey = resolutionKey;
  }

  //TODO need to have a schedule for the price series

  @Override
  public Set<ComputedValue> execute(final FunctionExecutionContext executionContext, final FunctionInputs inputs, final ComputationTarget target,
      final Set<ValueRequirement> desiredValues) {
    final HistoricalTimeSeriesSource timeSeriesSource = OpenGammaExecutionContext.getHistoricalTimeSeriesSource(executionContext);
    DoubleTimeSeries<?> assetPnL = null;
    double assetFairValue = 0;
    final HistoricalTimeSeriesBundle timeSeries = new HistoricalTimeSeriesBundle();
    for (ComputedValue input : inputs.getAllValues()) {
      if (ValueRequirementNames.PNL_SERIES.equals(input.getSpecification().getValueName())) {
        assetPnL = (DoubleTimeSeries<?>) inputs.getValue(ValueRequirementNames.PNL_SERIES); //TODO replace with return series when portfolio weights are in
      } else if (ValueRequirementNames.FAIR_VALUE.equals(input.getSpecification().getValueName())) {
        assetFairValue = (Double) inputs.getValue(ValueRequirementNames.FAIR_VALUE);
      } else if (ValueRequirementNames.HISTORICAL_TIME_SERIES.equals(input.getSpecification().getValueName())) {
        final HistoricalTimeSeries ts = (HistoricalTimeSeries) input.getValue();
        timeSeries.add(input.getSpecification().getProperty(HistoricalTimeSeriesFunctionUtils.DATA_FIELD_PROPERTY), timeSeriesSource.getExternalIdBundle(ts.getUniqueId()), ts);
      }
    }
    final ComputationTargetSpecification targetSpec = target.toSpecification();
    final ConventionBundleSource conventionSource = OpenGammaExecutionContext.getConventionBundleSource(executionContext);
    final ConventionBundle bundle = conventionSource.getConventionBundle(ExternalId.of(InMemoryConventionBundleMaster.SIMPLE_NAME_SCHEME, "USD_CAPM")); //TODO 
    final ValueRequirement desiredValue = desiredValues.iterator().next();
    final ValueProperties constraints = desiredValue.getConstraints();
    final HistoricalTimeSeries marketTimeSeries = timeSeries.get(MarketDataRequirementNames.MARKET_VALUE, bundle.getCAPMMarket());
    final HistoricalTimeSeries riskFreeTimeSeries = timeSeries.get(MarketDataRequirementNames.MARKET_VALUE, bundle.getCAPMRiskFreeRate());
    final TimeSeriesReturnCalculator returnCalculator = getReturnCalculator(constraints.getValues(ValuePropertyNames.RETURN_CALCULATOR));
    DoubleTimeSeries<?> marketReturn = returnCalculator.evaluate(marketTimeSeries.getTimeSeries());
    final DoubleTimeSeries<?> riskFreeTS = riskFreeTimeSeries.getTimeSeries().divide(100 * DAYS_IN_YEAR);
    marketReturn = marketReturn.subtract(riskFreeTS);
    DoubleTimeSeries<?> assetReturn = assetPnL.divide(assetFairValue);
    assetReturn = assetReturn.subtract(riskFreeTS);
    assetReturn = assetReturn.intersectionFirstValue(marketReturn);
    marketReturn = marketReturn.intersectionFirstValue(assetReturn);
    final LeastSquaresRegressionResult regression = CAPM_REGRESSION_MODEL.evaluate(assetReturn, marketReturn);
    final double alpha = regression.getBetas()[0];
    final double alphaPValue = regression.getPValues()[0];
    final double alphaTStat = regression.getTStatistics()[0];
    final double alphaResidual = regression.getResiduals()[0];
    final double alphaStdError = regression.getStandardErrorOfBetas()[0];
    final ValueProperties resultProperties = getResultProperties(desiredValues.iterator().next());
    final Set<ComputedValue> result = new HashSet<ComputedValue>();
    result.add(new ComputedValue(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_ADJUSTED_R_SQUARED, targetSpec, resultProperties), regression.getAdjustedRSquared()));
    result.add(new ComputedValue(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_ALPHA, targetSpec, resultProperties), alpha));
    result.add(new ComputedValue(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_BETA, targetSpec, resultProperties), regression.getBetas()[1]));
    result.add(new ComputedValue(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_MEAN_SQUARE_ERROR, targetSpec, resultProperties), regression.getMeanSquareError()));
    result.add(new ComputedValue(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_ALPHA_PVALUES, targetSpec, resultProperties), alphaPValue));
    result.add(new ComputedValue(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_BETA_PVALUES, targetSpec, resultProperties), regression.getPValues()[1]));
    result.add(new ComputedValue(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_R_SQUARED, targetSpec, resultProperties), regression.getRSquared()));
    result.add(new ComputedValue(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_ALPHA_RESIDUALS, targetSpec, resultProperties), alphaResidual));
    result.add(new ComputedValue(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_BETA_RESIDUALS, targetSpec, resultProperties), regression.getResiduals()[1]));
    result.add(new ComputedValue(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_STANDARD_ERROR_OF_ALPHA, targetSpec, resultProperties), alphaStdError));
    result.add(new ComputedValue(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_STANDARD_ERROR_OF_BETA, targetSpec, resultProperties), regression.getStandardErrorOfBetas()[1]));
    result.add(new ComputedValue(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_ALPHA_TSTATS, targetSpec, resultProperties), alphaTStat));
    result.add(new ComputedValue(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_BETA_TSTATS, targetSpec, resultProperties), regression.getTStatistics()[1]));
    return result;
  }

  @Override
  public Set<ValueRequirement> getRequirements(final FunctionCompilationContext context, final ComputationTarget target, final ValueRequirement desiredValue) {
    final ValueProperties constraints = desiredValue.getConstraints();
    final Set<String> samplingPeriods = constraints.getValues(ValuePropertyNames.SAMPLING_PERIOD);
    if (samplingPeriods == null || samplingPeriods.size() != 1) {
      return null;
    }
    final String samplingPeriod = samplingPeriods.iterator().next();
    final Set<String> scheduleCalculatorName = constraints.getValues(ValuePropertyNames.SCHEDULE_CALCULATOR);
    if (scheduleCalculatorName == null || scheduleCalculatorName.size() != 1) {
      return null;
    }
    final Set<String> samplingFunctionName = constraints.getValues(ValuePropertyNames.SAMPLING_FUNCTION);
    if (samplingFunctionName == null || samplingFunctionName.size() != 1) {
      return null;
    }
    final Set<String> returnCalculatorName = constraints.getValues(ValuePropertyNames.RETURN_CALCULATOR);
    if (returnCalculatorName == null || returnCalculatorName.size() != 1) {
      return null;
    }
    final Set<ValueRequirement> requirements = new HashSet<ValueRequirement>();
    requirements.add(new ValueRequirement(ValueRequirementNames.PNL_SERIES, target.toSpecification(), ValueProperties.builder()
        .withAny(ValuePropertyNames.CURRENCY)
        .with(ValuePropertyNames.SAMPLING_PERIOD, samplingPeriod)
        .with(ValuePropertyNames.SCHEDULE_CALCULATOR, scheduleCalculatorName.iterator().next())
        .with(ValuePropertyNames.SAMPLING_FUNCTION, samplingFunctionName.iterator().next())
        .with(ValuePropertyNames.RETURN_CALCULATOR, returnCalculatorName.iterator().next()).get()));
    requirements.add(new ValueRequirement(ValueRequirementNames.FAIR_VALUE, target.toSpecification()));
    final ConventionBundleSource conventionSource = OpenGammaCompilationContext.getConventionBundleSource(context);
    final ConventionBundle bundle = conventionSource.getConventionBundle(ExternalId.of(InMemoryConventionBundleMaster.SIMPLE_NAME_SCHEME, "USD_CAPM")); //TODO 
    final HistoricalTimeSeriesResolver resolver = OpenGammaCompilationContext.getHistoricalTimeSeriesResolver(context);
    final HistoricalTimeSeriesResolutionResult marketTimeSeries = resolver.resolve(bundle.getCAPMMarket(), null, null, null, MarketDataRequirementNames.MARKET_VALUE, _resolutionKey);
    if (marketTimeSeries == null) {
      return null;
    }
    requirements.add(HistoricalTimeSeriesFunctionUtils.createHTSRequirement(marketTimeSeries,
        MarketDataRequirementNames.MARKET_VALUE, DateConstraint.VALUATION_TIME.minus(samplingPeriod), true, DateConstraint.VALUATION_TIME, true));
    final HistoricalTimeSeriesResolutionResult riskFreeTimeSeries = resolver.resolve(bundle.getCAPMRiskFreeRate(), null, null, null, MarketDataRequirementNames.MARKET_VALUE, _resolutionKey);
    if (riskFreeTimeSeries == null) {
      return null;
    }
    requirements.add(HistoricalTimeSeriesFunctionUtils.createHTSRequirement(riskFreeTimeSeries,
        MarketDataRequirementNames.MARKET_VALUE, DateConstraint.VALUATION_TIME.minus(samplingPeriod), true, DateConstraint.VALUATION_TIME, true));
    return requirements;
  }

  @Override
  public Set<ValueSpecification> getResults(final FunctionCompilationContext context, final ComputationTarget target) {
    final ValueProperties resultProperties = getResultProperties();
    final Set<ValueSpecification> results = new HashSet<ValueSpecification>();
    final ComputationTargetSpecification targetSpec = target.toSpecification();
    results.add(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_ADJUSTED_R_SQUARED, targetSpec, resultProperties));
    results.add(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_ALPHA, targetSpec, resultProperties));
    results.add(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_BETA, targetSpec, resultProperties));
    results.add(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_MEAN_SQUARE_ERROR, targetSpec, resultProperties));
    results.add(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_ALPHA_PVALUES, targetSpec, resultProperties));
    results.add(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_BETA_PVALUES, targetSpec, resultProperties));
    results.add(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_R_SQUARED, targetSpec, resultProperties));
    results.add(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_ALPHA_RESIDUALS, targetSpec, resultProperties));
    results.add(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_BETA_RESIDUALS, targetSpec, resultProperties));
    results.add(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_STANDARD_ERROR_OF_ALPHA, targetSpec, resultProperties));
    results.add(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_STANDARD_ERROR_OF_BETA, targetSpec, resultProperties));
    results.add(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_ALPHA_TSTATS, targetSpec, resultProperties));
    results.add(new ValueSpecification(ValueRequirementNames.CAPM_REGRESSION_BETA_TSTATS, targetSpec, resultProperties));
    return results;
  }

  private ValueProperties getResultProperties() {
    return createValueProperties()
        .withAny(ValuePropertyNames.SAMPLING_PERIOD)
        .withAny(ValuePropertyNames.SCHEDULE_CALCULATOR)
        .withAny(ValuePropertyNames.SAMPLING_FUNCTION)
        .withAny(ValuePropertyNames.RETURN_CALCULATOR).get();
  }

  private ValueProperties getResultProperties(final ValueRequirement desiredValue) {
    return createValueProperties()
        .with(ValuePropertyNames.SAMPLING_PERIOD, desiredValue.getConstraint(ValuePropertyNames.SAMPLING_PERIOD))
        .with(ValuePropertyNames.SCHEDULE_CALCULATOR, desiredValue.getConstraint(ValuePropertyNames.SCHEDULE_CALCULATOR))
        .with(ValuePropertyNames.SAMPLING_FUNCTION, desiredValue.getConstraint(ValuePropertyNames.SAMPLING_FUNCTION))
        .with(ValuePropertyNames.RETURN_CALCULATOR, desiredValue.getConstraint(ValuePropertyNames.RETURN_CALCULATOR)).get();
  }

  private TimeSeriesReturnCalculator getReturnCalculator(final Set<String> returnCalculatorNames) {
    if (returnCalculatorNames == null || returnCalculatorNames.isEmpty() || returnCalculatorNames.size() != 1) {
      throw new OpenGammaRuntimeException("Missing or non-unique return calculator name: " + returnCalculatorNames);
    }
    return TimeSeriesReturnCalculatorFactory.getReturnCalculator(returnCalculatorNames.iterator().next());
  }

  @Override
  public ComputationTargetType getTargetType() {
    return TYPE;
  }

}