I'm using the rugarch::multifit() function in R. However, I can't figure out where the p-values are. Indeed, the output only report the coefficients, which is OK but I don't know about their significance.
This is my code :
require(pacman)
p_load(quantmod, dplyr, rugarch) #required packages
startDate=as.Date("2023-09-01")
endDate=as.Date(Sys.Date()) #dates
symbol.vec=c("SPY", "^DJI" )
getSymbols(symbol.vec ,from=startDate, to=endDate) #extract data in yahoo finance
names(DJI)<-c("Open", "High", "Low", "Close", "Volume", "Adjusted")
names(SPY)<-c("Open", "High", "Low", "Close", "Volume", "Adjusted")
zoo_object <- as.zoo(cbind(DJI$Close, SPY$Close))
names(zoo_object)<-c("DJI", "SPY")
returns <- as.zoo(apply(zoo_object , 2, function(x) diff(log(x) , lag=1))) #calculate returns
annualized_ret <- returns * sqrt(252) #calculate annualized returns
###univariate GARCH specifications
spec<-ugarchspec(variance.model=list(model="eGARCH",
garchOrder=c(1,1)),
mean.model=list(armaOrder=c(0,0), include.mean=T),
distribution.model="sstd")
### fit to data with multispec and multifit
mspec = multispec( replicate(spec, n = 2) )
fitlist = multifit(multispec = mspec, data = annualized_ret)
Now, the output in fitlist looks like this :
*----------------------------*
* GARCH Multi-Fit *
*----------------------------*
No. Assets :2
GARCH Multi-Spec Type : Equal
GARCH Model Spec
--------------------------
Model : eGARCH
Exogenous Regressors in variance equation: none
Mean Equation :
Include Mean : 1
AR(FI)MA Model : (0,d,0)
GARCH-in-Mean : FALSE
Exogenous Regressors in mean equation: none
Conditional Distribution: sstd
GARCH Model Fit
--------------------------
Optimal Parameters:
DJI SPY
mu 0.02781 0.01743
omega -0.42092 -0.52861
alpha1 -0.06894 -0.20948
beta1 0.91263 0.87563
gamma1 -0.45938 -0.55203
skew 1.12497 0.91316
shape 5.94730 4.31638
Log-Lik 112.11050 88.24099
Where can I see the p-values for each variable ? Also, is there a way to create a table with both the coefficients and the pvalues ?