VGARCH stands for vector GARCH or multivariate GARCH. In the financial domain, the assumption is that financial volatilities move together over time across assets and markets. Acknowledging this aspect through a multivariate modeling framework leads to a better model separate univariate model. It helps in making better decision tools in various areas, such as asset pricing, portfolio selection, option pricing, and hedging and risk management. There are multiple options in R for building in multivariate mode.
Let us consider an example of multivariate GARCH in R for the last year of data from the S&P500 and DJI index:
>install.packages("rmgarch")
>install.packages("PerformanceAnalytics")
>library(rmgarch)
>library(PerformanceAnalytics)
>snpdji <- read.zoo("DataChap4SPDJIRet.csv",header = TRUE, sep = ",",format="%m/%d/%Y")
>garch_spec = ugarchspec(mean.model = list(armaOrder = c(2,1)),variance.model = list(garchOrder = c(1,1), model = "sGARCH"), distribution.model...
