| dccPre {MTS} | R Documentation |
Preliminary Fitting of DCC Models
Description
This program fits marginal GARCH models to each component of a vector return series and returns the standardized return series for further analysis. The garchFit command of fGarch package is used.
Usage
dccPre(rtn, include.mean = T, p = 0, cond.dist = "norm")
Arguments
rtn |
A T-by-k data matrix of k-dimensional asset returns |
include.mean |
A logical switch to include a mean vector. Deafult is to include the mean. |
p |
VAR order for the mean equation |
cond.dist |
The conditional distribution of the innovations. Default is Gaussian. |
Details
The program uses fGarch package to estimate univariate GARCH model for each residual series after a VAR(p) fitting, if any.
Value
marVol |
A matrix of the volatility series for each return series |
sresi |
Standardized residual series |
est |
Parameter estimates for each marginal volatility model |
se.est |
Standard errors for parameter estimates of marginal volatility models |
Note
fGarch package is used
Author(s)
Ruey S. Tsay
References
Tsay (2014, Chapter 7). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.
See Also
dccFit