Module net.finmath.lib

Package net.finmath.timeseries.models.parametric

Class DisplacedLognormalGJRGARCH

java.lang.Object

net.finmath.timeseries.models.parametric.DisplacedLognormalGJRGARCH

All Implemented Interfaces:

HistoricalSimulationModel, TimeSeriesModelParametric

public class DisplacedLognormalGJRGARCH
extends Object
implements TimeSeriesModelParametric, HistoricalSimulationModel

Displaced log-normal process with GJR-GARCH(1,1) volatility. This class estimate the process \[ \mathrm{d} \log(X + a) = \frac{\sigma}{b + a} \mathrm{d}W(t) \] where \( a > -min(X(t_{i}) \) and thus \( X+a > 0 \) and \( b = 1 - -min(X(t_{i}) \) \) and \( \sigma \) is given by a GJR-GARCH(1,1) process. The choice of b ensures that b+a ≥ 1. For a=0 we have a log-normal process with volatility σ/(b + a). For a=infinity we have a normal process with volatility σ.

Version:

1.0

Author:

Christian Fries

Constructor Summary

Constructors

Constructor	Description
DisplacedLognormalGJRGARCH(TimeSeries timeSeries)
DisplacedLognormalGJRGARCH(TimeSeries timeSeries, double lowerBoundDisplacement)
DisplacedLognormalGJRGARCH(TimeSeries timeSeries, double lowerBoundDisplacement, double upperBoundDisplacement)

Method Summary

Modifier and Type	Method	Description
Map<String,Object>	getBestParameters()	Returns the parameters estimated for the given time series.
Map<String,Object>	getBestParameters(Map<String,Object> guess)	Returns the parameters estimated for the given time series, using a parameter guess.
TimeSeriesModelParametric	getCloneCalibrated(TimeSeries timeSeries)
HistoricalSimulationModel	getCloneWithWindow(int windowIndexStart, int windowIndexEnd)	Create a new model, using only a window of the times series.
double	getLastResidualForParameters(double[] parameters)
double	getLogLikelihoodForParameters(double[] parameters)
String[]	getParameterNames()
double[]	getParameters()
double[]	getSzenarios(double[] parameters)

Methods inherited from class java.lang.Object

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

Constructor Detail

DisplacedLognormalGJRGARCH

public DisplacedLognormalGJRGARCH(TimeSeries timeSeries)

DisplacedLognormalGJRGARCH

public DisplacedLognormalGJRGARCH(TimeSeries timeSeries,
                                  double lowerBoundDisplacement)

DisplacedLognormalGJRGARCH

public DisplacedLognormalGJRGARCH(TimeSeries timeSeries,
                                  double lowerBoundDisplacement,
                                  double upperBoundDisplacement)

Method Detail

getLogLikelihoodForParameters

public double getLogLikelihoodForParameters(double[] parameters)

getLastResidualForParameters

public double getLastResidualForParameters(double[] parameters)

getSzenarios

public double[] getSzenarios(double[] parameters)

getBestParameters

public Map<String,Object> getBestParameters()

Description copied from interface: HistoricalSimulationModel

Returns the parameters estimated for the given time series.

Specified by:

getBestParameters in interface HistoricalSimulationModel

Returns:

The parameters estimated for the given time series.

getBestParameters

public Map<String,Object> getBestParameters(Map<String,Object> guess)

Description copied from interface: HistoricalSimulationModel

Returns the parameters estimated for the given time series, using a parameter guess.

Specified by:

getBestParameters in interface HistoricalSimulationModel

Parameters:

guess - A parameter guess.

Returns:

The parameters estimated for the given time series.

getCloneCalibrated

public TimeSeriesModelParametric getCloneCalibrated(TimeSeries timeSeries)

Specified by:

getCloneCalibrated in interface TimeSeriesModelParametric

getCloneWithWindow

public HistoricalSimulationModel getCloneWithWindow(int windowIndexStart,
                                                    int windowIndexEnd)

Description copied from interface: HistoricalSimulationModel

Create a new model, using only a window of the times series.

Specified by:

getCloneWithWindow in interface HistoricalSimulationModel

Parameters:

windowIndexStart - Index of the first element to be part of the new time series.

windowIndexEnd - Index of the last element to be part of the new time series.

Returns:

A new historical simulation using a different data window.

getParameters

public double[] getParameters()

Specified by:

getParameters in interface TimeSeriesModelParametric

getParameterNames

public String[] getParameterNames()

Specified by:

getParameterNames in interface TimeSeriesModelParametric