logLikDccGarch: The logarithm of likelihood function of DCC-GARCH(1,1) Model.
In bayesDccGarch: Methods and Tools for Bayesian Dynamic Conditional Correlation GARCH(1,1) Model

logLikDccGarch

R Documentation

The logarithm of likelihood function of DCC-GARCH(1,1) Model.

Description

Compute the logarithm of likelihood function of DCC-GARCH(1,1) Model if mY is a matrix or the logarithm of likelihood function of GARCH(1,1) Model if mY is numeric vector.

Usage

logLikDccGarch(mY, omega = rep(0.03, ncol(mY)), alpha = rep(0.03, ncol(mY)), 
	beta = rep(0.8, ncol(mY)), a = 0.03, b = 0.8, gamma = rep(1, ncol(mY)), 
	tail = 10, errorDist = 2)

Arguments

`mY`	a matrix of the data (`n \times k`).
`omega`	a numeric vector (`k \times 1`) with the the values of `\omega_i` parameters. Default: `rep(0.03, ncol(mY))`.
`alpha`	a numeric vector (`k \times 1`) with the the values of `\alpha_i` parameters. Default: `rep(0.03, ncol(mY))`.
`beta`	a numeric vector (`k \times 1`) with the the values of `\beta_i` parameters. Default: `rep(0.80, ncol(mY))`.
`a`	a numeric value of the `a` parameter. Default: `0.03`.
`b`	a numeric value of the `b` parameter. Default: `0.8`.
`gamma`	a numeric vector (`k \times 1`) with the values of `\gamma_i` parameters. Default: `rep(1.0, ncol(mY))`.
`tail`	a numeric value of `\nu` parameter if `errorDist = 2` or of `\delta` parameter if `errorDist = 3`. If `errorDist = 1` so this arguments is no used.
`errorDist`	a probability distribution for errors. Use `errorDist=1` for `SSNorm`, `errorDist=2` for `SST` or `errorDist=3` for `SSGED`. Default: `2`.

Details

The log-likelihood of the model GARCH(1,1) is computed if mY has just one column. The arguments a and b are not consider in this case.

Value

Return a list with the elements:

`$H`	a matrix where the lines are the `H_t` values for t=1,...,n.
`$value`	the value of the logarithm of likelihood function.

Author(s)

Jose Augusto Fiorucci, Ricardo Sandes Ehlers and Francisco Louzada

References

Fioruci, J.A., Ehlers, R.S., Andrade Filho, M.G. Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions, Journal of Applied Statistics, 41(2), 320–331, 2014a. <doi:10.1080/02664763.2013.839635>

Fioruci, J.A., Ehlers, R.S., Louzada, F. BayesDccGarch - An Implementation of Multivariate GARCH DCC Models, ArXiv e-prints, 2014b. https://ui.adsabs.harvard.edu/abs/2014arXiv1412.2967F/abstract.

Examples


data(DaxCacNik)

Dax = DaxCacNik[,1]

######  log-likelihood function of GARCH(1,1) model with SST innovations ####
logLikDccGarch(Dax, omega=0.03, alpha=0.03, beta=0.8, gamma=0.7)$value

######  log-likelihood function of DCC-GARCH(1,1) model with SST innovations ####
logLikDccGarch(DaxCacNik, beta=c(0.82,0.91,0.85), gamma=c(0.7, 1.3, 1.7), tail=10)$value

bayesDccGarch documentation built on April 22, 2023, 9:08 a.m.