st: Heteroskedasticity still presents after using DCC-MGARCH

[Ra Nad <ranad112011@gmail.com>]

Hi all,

I have a problem  running the DCC-MGARCH model.Heteroskedasticity
still presents after using DCC-MGARCH no matter what mean equation or
order of ARCH/GARCH that I use

I tested several series of returns and found no autocorrelation but
heteroskedasticity in the returns . So I use DCC-MGARCH model to
estimate their correlation.After running the DCC-MGARCH, I checked the
residuals for heteroskedasticity and found heteroskedasticity still
presents. The special thing is, whatever lag order or mean equation I
use, when I check for PACF of the squared residuals, they are still
significant at the same lags like the PACF of the squared return.

I don't know if my explanation is clear or not so I give an example below:

When checking the PACF of  squared prices A,B, and C, I found the PACF
is significant at lag 1,2,3,9 for squared A, the PACF is significant
at lag 2 for squared B, and at lag 3,5 for squared C. After running
the DCC-MGARCH  with several types of mean equation such as VAR,
ARIMA, I check for the residual's PACF and found PACF of squared A are
still significant at lag 1,2,3,9 , PACF of squared B is still
significant at lag 2, the same happens for squared C. So basically the
DCC-MGARCH did not remove any ARCH effect at all.

The problem happens will every return series that I have. I also tried
to use ARCH or GARCH for each returns individually, but the
residuals's PACF after using ARCH or GARCH or DCC-MGARCH look just
exact the same like the PACF of the squared returns.

Do you know why this problem occurs? and What should I do to fix it?
Many thanks for any suggestion.

Best,
Ranad
*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/