Module net.finmath.lib
Package net.finmath.montecarlo.interestrate.models.covariance

Class BlendedLocalVolatilityModel

java.lang.Object
net.finmath.montecarlo.interestrate.models.covariance.AbstractLIBORCovarianceModel
net.finmath.montecarlo.interestrate.models.covariance.AbstractLIBORCovarianceModelParametric
net.finmath.montecarlo.interestrate.models.covariance.BlendedLocalVolatilityModel
All Implemented Interfaces:
Serializable, LIBORCovarianceModel, LIBORCovarianceModelCalibrateable
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 \[ ( a + (1-a) L_{i}(t) ) F_{i}(t) \text{,} \] or \[ ( a L_{i,0} + (1-a) L_{i}(t) ) F_{i}(t) \text{,} \] if an initial forward curve \( i \mapsto L_{i,0} \) is given, where a is the displacement or blending parameter 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. If a forward curve is provided, the deterministic value Li,0 is calculated form this curve (using fixing in Ti), otherwise it is replaced by 1. 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.
Version:
1.0
Author:
Christian Fries
See Also:
Serialized Form

  • Constructor Details

    • BlendedLocalVolatilityModel

      public BlendedLocalVolatilityModel​(AbstractLIBORCovarianceModelParametric covarianceModel, ForwardCurve forwardCurve, RandomVariable 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​(RandomVariableFactory abstractRandomVariableFactory, AbstractLIBORCovarianceModelParametric covarianceModel, ForwardCurve 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:
      abstractRandomVariableFactory - The factory used to create RandomVariable objects from constants.
      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​(RandomVariableFactory abstractRandomVariableFactory, 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:
      abstractRandomVariableFactory - The factory used to create RandomVariable objects from constants.
      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.

    • BlendedLocalVolatilityModel

      public BlendedLocalVolatilityModel​(AbstractLIBORCovarianceModelParametric covarianceModel, ForwardCurve 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 Details