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

Class LIBORVolatilityModelTwoParameterExponentialForm

java.lang.Object
net.finmath.montecarlo.interestrate.models.covariance.LIBORVolatilityModel
net.finmath.montecarlo.interestrate.models.covariance.LIBORVolatilityModelTwoParameterExponentialForm
All Implemented Interfaces:
Serializable
public class LIBORVolatilityModelTwoParameterExponentialForm extends LIBORVolatilityModel
Implements the volatility model σi(tj) = a * exp(-b (Ti-tj))
Version:
1.0
Author:
Christian Fries
See Also:

  • Constructor Details

    • LIBORVolatilityModelTwoParameterExponentialForm

      public LIBORVolatilityModelTwoParameterExponentialForm(RandomVariableFactory randomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, RandomVariable a, RandomVariable b, boolean isCalibrateable)
      Creates the volatility model σi(tj) = a * exp(-b (Ti-tj))
      Parameters:
      randomVariableFactory - The random variable factor used to construct random variables from the parameters.
      timeDiscretization - The simulation time discretization tj.
      liborPeriodDiscretization - The period time discretization Ti.
      a - The parameter a: an initial volatility level.
      b - The parameter b: exponential decay of the volatility.
      isCalibrateable - Set this to true, if the parameters are available for calibration.

    • LIBORVolatilityModelTwoParameterExponentialForm

      public LIBORVolatilityModelTwoParameterExponentialForm(RandomVariableFactory randomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, double a, double b, boolean isCalibrateable)
      Creates the volatility model σi(tj) = a * exp(-b (Ti-tj))
      Parameters:
      randomVariableFactory - The random variable factor used to construct random variables from the parameters.
      timeDiscretization - The simulation time discretization tj.
      liborPeriodDiscretization - The period time discretization Ti.
      a - The parameter a: an initial volatility level.
      b - The parameter b: exponential decay of the volatility.
      isCalibrateable - Set this to true, if the parameters are available for calibration.

    • LIBORVolatilityModelTwoParameterExponentialForm

      public LIBORVolatilityModelTwoParameterExponentialForm(TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, double a, double b)
      Creates the volatility model σi(tj) = a * exp(-b (Ti-tj))
      Parameters:
      timeDiscretization - The simulation time discretization tj.
      liborPeriodDiscretization - The period time discretization Ti.
      a - The parameter a: an initial volatility level.
      b - The parameter b: exponential decay of the volatility.

  • Method Details

    • getParameter

      public RandomVariable[] getParameter()
      Specified by:
      getParameter in class LIBORVolatilityModel

    • getCloneWithModifiedParameter

      public LIBORVolatilityModelTwoParameterExponentialForm getCloneWithModifiedParameter(RandomVariable[] parameter)
      Specified by:
      getCloneWithModifiedParameter in class LIBORVolatilityModel

    • getVolatility

      public RandomVariable getVolatility(int timeIndex, int liborIndex)
      Description copied from class: LIBORVolatilityModel
      Implement this method to complete the implementation.
      Specified by:
      getVolatility in class LIBORVolatilityModel
      Parameters:
      timeIndex - The time index (for timeDiscretizationFromArray)
      liborIndex - The libor index (for liborPeriodDiscretization)
      Returns:
      A random variable (e.g. as a vector of doubles) representing the volatility for each path.

    • clone

      public Object clone()
      Specified by:
      clone in class LIBORVolatilityModel

    • getCloneWithModifiedData

      public LIBORVolatilityModel getCloneWithModifiedData(Map<String,Object> dataModified)
      Description copied from class: LIBORVolatilityModel
      Returns a clone of this model where the specified properties have been modified. Note that there is no guarantee that a model reacts on a specification of a properties in the parameter map dataModified. If data is provided which is ignored by the model no exception may be thrown. Furthermore the structure of the correlation model has to match changed data. A change of the time discretizations may requires a change in the parameters but this function will just insert the new time discretization without changing the parameters. An exception may not be thrown.
      Specified by:
      getCloneWithModifiedData in class LIBORVolatilityModel
      Parameters:
      dataModified - Key-value-map of parameters to modify.
      Returns:
      A clone of this model (or a new instance of this model if no parameter was modified).