# 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.

bayesDccGarch-package, bayesDccGarch

### 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.