Package 'GARCHSK'

Title: Estimating a GARCHSK Model and GJRSK Model
Description: Functions for estimating a GARCHSK model and GJRSK model based on a publication by Leon et,al (2005)<doi:10.1016/j.qref.2004.12.020> and Nakagawa and Uchiyama (2020)<doi:10.3390/math8111990>. These are a GARCH-type model allowing for time-varying volatility, skewness and kurtosis.
Authors: Kei Nakagawa [aut, cre]
Maintainer: Kei Nakagawa <[email protected]>
License: GPL (>= 2)
Version: 0.1.0
Built: 2025-02-06 03:55:30 UTC
Source: https://github.com/cran/GARCHSK

Help Index

GARCHSK

Description

Functions for estimating GARCHSK model and GJRSK model based on a publication by Leon et,al (2005).

This function constructs GARCHSK model of given data and parameters.

Description

This function constructs GARCHSK model of given data and parameters.

Usage

garchsk_construct(params, data)

Arguments

params

vector of GJRSK model parameters(p1,const2,p2,q2,const3,p3,q3,const4,p4,q4)
data

vector time series data

Value

list of conditional mean(mu), variance(h), skewness(sk) and kurtosis(ku)

This function estimates GARCHSK model's parameters.

Description

This function estimates GARCHSK model's parameters.

Usage

garchsk_est(data)

Arguments

data

vector time series data

Value

list of parameters,standard errors of parameters,t-statistics,the minimum value of log-likelihood,AIC and BIC.

Examples

library(GARCHSK)
  #load data
  data(GBP)
  
  # Estimate the parameters of GARCHSK model
  garchsk_GBP<-garchsk_est(GBP[1:100])
  
  # Parameters
  garchsk_GBP$params

This function forcasts conditional mean,variance,skewness and kurtosis with given GARCHSK model.

Description

This function forcasts conditional mean,variance,skewness and kurtosis with given GARCHSK model.

Usage

garchsk_fcst(params, data, max_forecast = 20)

Arguments

params

vector of GARCHSK model parameters(p1,const2,p2,q2,const3,p3,q3,const4,p4,q4)
data

vector time series data
max_forecast

how long does this function forecast(Default value is 20)

Value

list of predicted conditional mean,variance,skewness and kurtosis

This function is inequality equation of GARCHSK parameters used in optimization process(Rsolnp).

Description

This function is inequality equation of GARCHSK parameters used in optimization process(Rsolnp).

Usage

garchsk_ineqfun(params, data)

Arguments

params

vector of GARCHSK model parameters(p1,const2,p2,q2,r2,const3,p3,q3,r3,const4,p4,q4,r4)
data

vector time series data

Value

upper bound >parameters > lower bound

This function calculates the log-likelihood of GARCHSK model.

Description

This function calculates the log-likelihood of GARCHSK model.

Usage

garchsk_lik(params, data)

Arguments

params

vector of GARCHSK model parameters(p1,const2,p2,q2,const3,p3,q3,const4,p4,q4)
data

vector time series data

Value

(negative) log-likelihood of GJRSK model

GBP/USD exchange rate from 1990-01-03 to 2002-5-3 from Bloomberg.

Description

GBP/USD exchange rate from 1990-01-03 to 2002-5-3 from Bloomberg.

Format

A numeric vector with 3218 length

Source

Bloomberg(GBP CURRNCY)

This function constructs GJRSK model of given data and parameters.

Description

This function constructs GJRSK model of given data and parameters.

Usage

gjrsk_construct(params, data)

Arguments

params

vector of GJRSK model parameters(p1,const2,p2,q2,r2,const3,p3,q3,r3,const4,p4,q4,r4)
data

vector time series data

Value

list of conditional mean(mu), variance(h), skewness(sk) and kurtosis(ku)

This function estimates GJRSK model's parameters.

Description

This function estimates GJRSK model's parameters.

Usage

gjrsk_est(data)

Arguments

data

vector time series data

Value

list of parameters,standard errors of parameters,t-statistics,the minimum value of log-likelihood,AIC and BIC.

Examples

library(GARCHSK)
  #load data
  data(GBP)
  
  # Estimate the parameters of GJR-SK model
  gjrsk_GBP<-gjrsk_est(GBP[1:100])
  
  # Parameters
  gjrsk_GBP$params

This function forcasts conditional mean,variance,skewness and kurtosis with given GJRSK model.

Description

This function forcasts conditional mean,variance,skewness and kurtosis with given GJRSK model.

Usage

gjrsk_fcst(params, data, max_forecast = 20)

Arguments

params

vector of GJRSK model parameters(p1,const2,p2,q2,r2,const3,p3,q3,r3,const4,p4,q4,r4)
data

vector time series data
max_forecast

how long does this function forecast(Default value is 20)

Value

list of predicted conditional mean,variance,skewness and kurtosis

This function is inequality equation of GJRSK parameters used in optimization process(Rsolnp).

Description

This function is inequality equation of GJRSK parameters used in optimization process(Rsolnp).

Usage

gjrsk_ineqfun(params, data)

Arguments

params

vector of GJRSK model parameters(p1,const2,p2,q2,r2,const3,p3,q3,r3,const4,p4,q4,r4)
data

vector time series data

Value

upper bound >parameters > lower bound

This function calculates the log-likelihood of GJRSK model.

Description

This function calculates the log-likelihood of GJRSK model.

Usage

gjrsk_lik(params, data)

Arguments

params

vector of GJRSK model parameters(p1,const2,p2,q2,r2,const3,p3,q3,r3,const4,p4,q4,r4)
data

vector time series data

Value

(negative) log-likelihood of GJRSK model

This function calculates kurtosis of given data.

Description

This function calculates kurtosis of given data.

Usage

kurtosis(data)

Arguments

data

vector or T by 1 matrix

Value

kurtosis of given data

This function calculates skewness of given data.

Description

This function calculates skewness of given data.

Usage

skewness(data)

Arguments

data

vector or T by 1 matrix

Value

skewness of given data