net.finmath.montecarlo.interestrate.models.covariance.DisplacedLocalVolatilityModel Maven / Gradle / Ivy
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finmath lib is a Mathematical Finance Library in Java.
It provides algorithms and methodologies related to mathematical finance.
/*
* (c) Copyright Christian P. Fries, Germany. Contact: [email protected].
*
* Created on 26.05.2013
*/
package net.finmath.montecarlo.interestrate.models.covariance;
import java.util.Map;
import net.finmath.exception.CalculationException;
import net.finmath.marketdata.model.curves.ForwardCurve;
import net.finmath.montecarlo.RandomVariableFactory;
import net.finmath.stochastic.RandomVariable;
import net.finmath.stochastic.Scalar;
/**
* Displaced model build on top of a standard covariance model.
*
* The model constructed for the i-th factor loading is
* (Li(t) + d) Fi(t)
* where d is the displacement and Li is
* the realization of the i-th component of the stochastic process and
* Fi is the factor loading from the given covariance model.
*
* The parameter of this model is a joint parameter vector, consisting
* of the parameter vector of the given base covariance model and
* appending the displacement parameter at the end.
*
* If this model is not calibrateable, its parameter vector is that of the
* covariance model, i.e., only the displacement parameter will be not
* part of the calibration.
*
* @author Christian Fries
* @version 1.0
*/
public class DisplacedLocalVolatilityModel extends AbstractLIBORCovarianceModelParametric {
private static final long serialVersionUID = 4522227972747028512L;
private final AbstractLIBORCovarianceModelParametric covarianceModel;
private final RandomVariable displacement;
private ForwardCurve forwardCurve;
private boolean isCalibrateable = false;
/**
* Displaced model build on top of a standard covariance model.
*
* The model constructed for the i-th factor loading is
* (Li(t) + d) Fi(t)
* where d is the displacement and Li is
* the realization of the i-th component of the stochastic process and
* Fi is the factor loading from the given covariance model.
*
* The parameter of this model is a joint parameter vector, consisting
* of the parameter vector of the given base covariance model and
* appending the displacement parameter at the end.
*
* If this model is not calibrateable, its parameter vector is that of the
* covariance model, i.e., only the displacement parameter will be not
* part of the calibration.
*
* @param covarianceModel The given covariance model specifying the factor loadings F.
* @param displacement The displacement a.
* @param isCalibrateable If true, the parameter a is a free parameter. Note that the covariance model may have its own parameter calibration settings.
*/
public DisplacedLocalVolatilityModel(final AbstractLIBORCovarianceModelParametric covarianceModel, final RandomVariable displacement, final boolean isCalibrateable) {
super(covarianceModel.getTimeDiscretization(), covarianceModel.getLiborPeriodDiscretization(), covarianceModel.getNumberOfFactors());
this.covarianceModel = covarianceModel;
this.displacement = displacement;
this.isCalibrateable = isCalibrateable;
}
/**
* Displaced model build on top of a standard covariance model.
*
* The model constructed for the i-th factor loading is
* (Li(t) + d) Fi(t)
* where d is the displacement and Li is
* the realization of the i-th component of the stochastic process and
* Fi is the factor loading from the given covariance model.
*
* The parameter of this model is a joint parameter vector, consisting
* of the parameter vector of the given base covariance model and
* appending the displacement parameter at the end.
*
* If this model is not calibrateable, its parameter vector is that of the
* covariance model, i.e., only the displacement parameter will be not
* part of the calibration.
*
* @param covarianceModel The given covariance model specifying the factor loadings F.
* @param displacement The displacement a.
* @param isCalibrateable If true, the parameter a is a free parameter. Note that the covariance model may have its own parameter calibration settings.
*/
public DisplacedLocalVolatilityModel(final AbstractLIBORCovarianceModelParametric covarianceModel, final double displacement, final boolean isCalibrateable) {
super(covarianceModel.getTimeDiscretization(), covarianceModel.getLiborPeriodDiscretization(), covarianceModel.getNumberOfFactors());
this.covarianceModel = covarianceModel;
this.displacement = new Scalar(displacement);
this.isCalibrateable = isCalibrateable;
}
@Override
public Object clone() {
return new DisplacedLocalVolatilityModel((AbstractLIBORCovarianceModelParametric) covarianceModel.clone(), displacement, isCalibrateable);
}
/**
* Returns the base covariance model, i.e., the model providing the factor loading F
* such that this model's i-th factor loading is
* (a Li,0 + (1-a)Li(t)) Fi(t)
* where a is the displacement and Li is
* the realization of the i-th component of the stochastic process and
* Fi is the factor loading loading from the given covariance model.
*
* @return The base covariance model.
*/
public AbstractLIBORCovarianceModelParametric getBaseCovarianceModel() {
return covarianceModel;
}
@Override
public RandomVariable[] getParameter() {
if(!isCalibrateable) {
return covarianceModel.getParameter();
}
final RandomVariable[] covarianceParameters = covarianceModel.getParameter();
if(covarianceParameters == null) {
return new RandomVariable[] { displacement };
}
// Append displacement to the end of covarianceParameters
final RandomVariable[] jointParameters = new RandomVariable[covarianceParameters.length+1];
System.arraycopy(covarianceParameters, 0, jointParameters, 0, covarianceParameters.length);
jointParameters[covarianceParameters.length] = displacement;
return jointParameters;
}
@Override
public double[] getParameterAsDouble() {
final RandomVariable[] parameters = getParameter();
final double[] parametersAsDouble = new double[parameters.length];
for(int i=0; i dataModified)
throws CalculationException {
RandomVariable displacement = this.displacement;
boolean isCalibrateable = this.isCalibrateable;
AbstractLIBORCovarianceModelParametric covarianceModel = this.covarianceModel;
RandomVariableFactory randomVariableFactory = null;
if(dataModified != null) {
if(dataModified.containsKey("randomVariableFactory")) {
randomVariableFactory = (RandomVariableFactory)dataModified.get("randomVariableFactory");
displacement = randomVariableFactory.createRandomVariable(displacement.doubleValue());
}
if (!dataModified.containsKey("covarianceModel")) {
covarianceModel = covarianceModel.getCloneWithModifiedData(dataModified);
}
// Explicitly passed covarianceModel has priority
covarianceModel = (AbstractLIBORCovarianceModelParametric)dataModified.getOrDefault("covarianceModel", covarianceModel);
isCalibrateable = (boolean)dataModified.getOrDefault("isCalibrateable", isCalibrateable);
if (dataModified.getOrDefault("displacement", displacement) instanceof RandomVariable) {
displacement = (RandomVariable) dataModified.getOrDefault("displacement", displacement);
} else if (randomVariableFactory == null) {
displacement = new Scalar((double) dataModified.get("displacement"));
} else {
displacement = randomVariableFactory.createRandomVariable((double) dataModified.get("displacement"));
}
}
final AbstractLIBORCovarianceModelParametric newModel = new DisplacedLocalVolatilityModel(covarianceModel, displacement, isCalibrateable);
return newModel;
}
}