net.finmath.montecarlo.interestrate.models.covariance

Class LIBORVolatilityModel

java.lang.Object

net.finmath.montecarlo.interestrate.models.covariance.LIBORVolatilityModel

All Implemented Interfaces:

Serializable

Direct Known Subclasses:

LIBORVolatilityModelFourParameterExponentialForm, LIBORVolatilityModelFourParameterExponentialFormIntegrated, LIBORVolatilityModelFromGivenMatrix, LIBORVolatilityModelMaturityDependentFourParameterExponentialForm, LIBORVolatilityModelPiecewiseConstant, LIBORVolatilityModelTimeHomogenousPiecewiseConstant, LIBORVolatilityModelTwoParameterExponentialForm

public abstract class LIBORVolatilityModel
extends Object
implements Serializable

Abstract base class and interface description of a volatility model (as it is used in LIBORCovarianceModelFromVolatilityAndCorrelation). Derive from this class and implement the getVolatlity method. You have to call the constructor of this class to set the time discretizations.

Version:

1.0

Author:

Christian Fries

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
LIBORVolatilityModel(TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization)

Method Summary

Modifier and Type	Method and Description
abstract Object	clone()
abstract LIBORVolatilityModel	getCloneWithModifiedData(Map<String,Object> dataModified) Returns a clone of this model where the specified properties have been modified.
abstract LIBORVolatilityModel	getCloneWithModifiedParameter(RandomVariable[] parameter)
TimeDiscretization	getLiborPeriodDiscretization()
abstract RandomVariable[]	getParameter()
double[]	getParameterAsDouble()
TimeDiscretization	getTimeDiscretization()
abstract RandomVariable	getVolatility(int timeIndex, int component) Implement this method to complete the implementation.

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

LIBORVolatilityModel

public LIBORVolatilityModel(TimeDiscretization timeDiscretization,
                            TimeDiscretization liborPeriodDiscretization)

Parameters:

timeDiscretization - The vector of simulation time discretization points.

liborPeriodDiscretization - The vector of tenor discretization points.

Method Detail

getParameter

public abstract RandomVariable[] getParameter()

getCloneWithModifiedParameter

public abstract LIBORVolatilityModel getCloneWithModifiedParameter(RandomVariable[] parameter)

getVolatility

public abstract RandomVariable getVolatility(int timeIndex,
                                             int component)

Implement this method to complete the implementation.

Parameters:

timeIndex - The time index (for timeDiscretizationFromArray)

component - The libor index (for liborPeriodDiscretization)

Returns:

A random variable (e.g. as a vector of doubles) representing the volatility for each path.

getParameterAsDouble

public double[] getParameterAsDouble()

getLiborPeriodDiscretization

public TimeDiscretization getLiborPeriodDiscretization()

Returns:

Returns the liborPeriodDiscretization.

getTimeDiscretization

public TimeDiscretization getTimeDiscretization()

Returns:

Returns the timeDiscretizationFromArray.

clone

public abstract Object clone()

Overrides:

clone in class Object

getCloneWithModifiedData

public abstract LIBORVolatilityModel getCloneWithModifiedData(Map<String,Object> dataModified)

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.

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).