net.finmath.montecarlo.interestrate.modelplugins

Class BlendedLocalVolatilityModel

java.lang.Object

net.finmath.montecarlo.interestrate.modelplugins.AbstractLIBORCovarianceModel

net.finmath.montecarlo.interestrate.modelplugins.AbstractLIBORCovarianceModelParametric

net.finmath.montecarlo.interestrate.modelplugins.BlendedLocalVolatilityModel

public class BlendedLocalVolatilityModel
extends AbstractLIBORCovarianceModelParametric

Blended model (or displaced diffusion model) build on top of a standard covariance model. The model constructed for the 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 from the given covariance model. If a forward curve is provided, the deterministic value L_i,0 is calculated form this curve (using fixing in T_i. 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.

Constructor Summary

Constructors

Constructor and Description
BlendedLocalVolatilityModel(AbstractLIBORCovarianceModelParametric covarianceModel, double displacement, boolean isCalibrateable) Displaced diffusion model build on top of a standard covariance model.
BlendedLocalVolatilityModel(AbstractLIBORCovarianceModelParametric covarianceModel, ForwardCurveInterface forwardCurve, double displacement, boolean isCalibrateable) Displaced diffusion model build on top of a standard covariance model.

Method Summary

Modifier and Type	Method and Description
java.lang.Object	clone()
AbstractLIBORCovarianceModelParametric	getBaseCovarianceModel() 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.
RandomVariableInterface[]	getFactorLoading(int timeIndex, int component, RandomVariableInterface[] realizationAtTimeIndex) Return the factor loading for a given time index and component index.
RandomVariable	getFactorLoadingPseudoInverse(int timeIndex, int component, int factor, RandomVariableInterface[] realizationAtTimeIndex) Returns the pseudo inverse of the factor matrix.
double[]	getParameter() Get the parameters of determining this parametric covariance model.
void	setParameter(double[] parameter)

Methods inherited from class net.finmath.montecarlo.interestrate.modelplugins.AbstractLIBORCovarianceModelParametric

getCloneCalibrated, getCloneCalibrated, getCloneWithModifiedParameters, toString

Methods inherited from class net.finmath.montecarlo.interestrate.modelplugins.AbstractLIBORCovarianceModel

getCovariance, getCovariance, getFactorLoading, getFactorLoading, getLiborPeriodDiscretization, getNumberOfFactors, getTimeDiscretization

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

BlendedLocalVolatilityModel

public BlendedLocalVolatilityModel(AbstractLIBORCovarianceModelParametric covarianceModel,
                                   ForwardCurveInterface forwardCurve,
                                   double displacement,
                                   boolean isCalibrateable)

Displaced diffusion model build on top of a standard covariance model. The model constructed is (a L₀ + (1-a)L) F where a is the displacement and L is the component of the stochastic process and F is the factor loading from the given covariance model. The parameter of this model is a joint parameter vector, where the first entry is the displacement and the remaining entries are the parameter vector of the given base covariance model. If this model is not calibrateable, its parameter vector is that of the covariance model.

Parameters:

covarianceModel - The given covariance model specifying the factor loadings F.

forwardCurve - The given forward curve L₀

displacement - The displacement a.

isCalibrateable - If true, the parameter a is a free parameter. Note that the covariance model may have its own parameter calibration settings.

BlendedLocalVolatilityModel

public BlendedLocalVolatilityModel(AbstractLIBORCovarianceModelParametric covarianceModel,
                                   double displacement,
                                   boolean isCalibrateable)

Displaced diffusion model build on top of a standard covariance model. The model performs a linear interpolation of a log-normal model (a = 0) and a normal model (a = 1). The model constructed is (a + (1-a)L) F where a is the displacement and L is the component of the stochastic process and F is the factor loading loading from the given covariance model. The parameter of this model is a joint parameter vector, where the first entry is the displacement and the remaining entries are the parameter vector of the given base covariance model. If this model is not calibrateable, its parameter vector is that of the covariance model.

Parameters:

covarianceModel - The given covariance model specifying the factor loadings F.

displacement - The displacement a.

isCalibrateable - If true, the parameter a is a free parameter. Note that the covariance model may have its own parameter calibration settings.

Method Detail

clone

public java.lang.Object clone()

Specified by:

clone in class AbstractLIBORCovarianceModelParametric

getBaseCovarianceModel

public AbstractLIBORCovarianceModelParametric getBaseCovarianceModel()

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.

Returns:

The base covariance model.

getParameter

public double[] getParameter()

Description copied from class: AbstractLIBORCovarianceModelParametric

Get the parameters of determining this parametric covariance model. The parameters are usually free parameters which may be used in calibration.

Specified by:

getParameter in class AbstractLIBORCovarianceModelParametric

Returns:

Parameter vector.

setParameter

public void setParameter(double[] parameter)

Specified by:

setParameter in class AbstractLIBORCovarianceModelParametric

getFactorLoading

public RandomVariableInterface[] getFactorLoading(int timeIndex,
                                                  int component,
                                                  RandomVariableInterface[] realizationAtTimeIndex)

Description copied from class: AbstractLIBORCovarianceModel

Return the factor loading for a given time index and component index. The factor loading is the vector f_i such that the scalar product
f_jf_k = f_j,1f_k,1 + ... + f_j,mf_k,m
is the instantaneous covariance of the component j and k.

Specified by:

getFactorLoading in class AbstractLIBORCovarianceModel

Parameters:

timeIndex - The time index at which factor loading is requested.

component - The index of the component i.

realizationAtTimeIndex - The realization of the stochastic process (may be used to implement local volatility/covariance/correlation models).

Returns:

The factor loading f_i(t).

getFactorLoadingPseudoInverse

public RandomVariable getFactorLoadingPseudoInverse(int timeIndex,
                                                    int component,
                                                    int factor,
                                                    RandomVariableInterface[] realizationAtTimeIndex)

Description copied from class: AbstractLIBORCovarianceModel

Returns the pseudo inverse of the factor matrix.

Specified by:

getFactorLoadingPseudoInverse in class AbstractLIBORCovarianceModel

Parameters:

timeIndex - The time index at which factor loading inverse is requested.

component - The index of the component i.

factor - The index of the factor j.

realizationAtTimeIndex - The realization of the stochastic process (may be used to implement local volatility/covariance/correlation models).

Returns:

The entry of the pseudo-inverse of the factor loading matrix.