| Type: | Package |
| Title: | Estimating a GARCHSK Model and GJRSK Model |
| Version: | 0.1.0 |
| 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. |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| LazyData: | TRUE |
| Imports: | stats, Rsolnp |
| RoxygenNote: | 6.0.1 |
| NeedsCompilation: | no |
| Packaged: | 2021-07-21 23:53:27 UTC; keina |
| Author: | Kei Nakagawa 
[aut, cre] |
| Maintainer: | Kei Nakagawa <kei.nak.0315@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2021-07-22 07:00:07 UTC |
GARCHSK
Description
Functions for estimating GARCHSK model and GJRSK model based on a publication by Leon et,al (2005).
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 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
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