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Re: st: Heteroskedasticity still presents after using DCC-MGARCH


From   Tirthankar Chakravarty <tirthankar.lists@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Heteroskedasticity still presents after using DCC-MGARCH
Date   Thu, 27 Sep 2012 16:04:49 +0530

A few points:

- You say that you are checking the square of the prices for
heteroskedasticity, but are modelling the returns?

- Also, while the PACF is a visual indicator, you need to perform
actual tests, like the Box-Ljung type portmanteau tests on the squared
residuals to be able to say something statistically definite. You
might wish to start here:
http://onlinelibrary.wiley.com/doi/10.1111/1467-9892.00061/abstract

- You need to say what your model specification looks like.  You have
not told us your model selection device -- have you tried adding
further lags to your volatility equations?

T

On Wed, Sep 26, 2012 at 11:33 PM, Ra Nad <ranad112011@gmail.com> wrote:
> 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
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