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.
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/*
 * (c) Copyright Christian P. Fries, Germany. Contact: [email protected].
 *
 * Created on 26.05.2013
 */
package net.finmath.montecarlo.interestrate.models.covariance;

import net.finmath.marketdata.model.curves.ForwardCurve;
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
 * 
 * (L_i(t) + d) F_i(t)
 * 
 * where d is the displacement and L_i is
 * the realization of the i-th component of the stochastic process and
 * F_i 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 AbstractLIBORCovarianceModelParametric covarianceModel;
	private 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
	 * 
	 * (L_i(t) + d) F_i(t)
	 * 
	 * where d is the displacement and L_i is
	 * the realization of the i-th component of the stochastic process and
	 * F_i 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(AbstractLIBORCovarianceModelParametric covarianceModel, RandomVariable displacement, 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
	 * 
	 * (L_i(t) + d) F_i(t)
	 * 
	 * where d is the displacement and L_i is
	 * the realization of the i-th component of the stochastic process and
	 * F_i 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(AbstractLIBORCovarianceModelParametric covarianceModel, double displacement, 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 L_i,0 + (1-a)L_i(t)) F_i(t)
	 * 
	 * where a is the displacement and L_i is
	 * the realization of the i-th component of the stochastic process and
	 * F_i 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();
		}

		RandomVariable[] covarianceParameters = covarianceModel.getParameter();
		if(covarianceParameters == null) {
			return new RandomVariable[] { displacement };
		}

		// Append displacement to the end of covarianceParameters
		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() {
		RandomVariable[] parameters = getParameter();
		double[] parametersAsDouble = new double[parameters.length];
		for(int i=0; i