Dear prof. Robert,
********example***************************************
webuse wpi1
arima D.ln_wpi, arima(1,0,1) noconstant nolog
arch D.ln_wpi, arch(1) arima(1,0,1) noconstant nolog
**********************************************************
I think that with this example you can replicate the Vasja doubt.
Best regards,
Joao Lima
2008/8/18 Robert A Yaffee <[email protected]>:
> Vasja,
> I cannot replicate that problem with my Stata10. Changing the subcommand order
> does not change the parameter estimates in my arch output.
> - Regards,
> Bob
>
>
> Robert A. Yaffee, Ph.D.
> Research Professor
> Silver School of Social Work
> New York University
>
>
> Biosketch: http://homepages.nyu.edu/~ray1/Biosketch2008.pdf
>
> CV: http://homepages.nyu.edu/~ray1/vita.pdf
>
> ----- Original Message -----
> From: Robert A Yaffee <[email protected]>
> Date: Monday, August 18, 2008 10:16 am
> Subject: Re: st: Problem with ARIMA-ARCH model
> To: [email protected]
>
>
>> Dear Vasja,
>> The variance model is not robust to misspecification of the mean model.
>> You need to properly specify your mean model before attempting to
>> model the conditional error variance. Variations in specification
>> of the mean
>> model will clearly affect the modeling of the conditional error
>> variance from it.
>> Regards,
>> Bob Yaffee
>>
>> Robert A. Yaffee, Ph.D.
>> Research Professor
>> Silver School of Social Work
>> New York University
>>
>>
>> Biosketch: http://homepages.nyu.edu/~ray1/Biosketch2008.pdf
>>
>> CV: http://homepages.nyu.edu/~ray1/vita.pdf
>>
>> ----- Original Message -----
>> From: vasja sivec <[email protected]>
>> Date: Monday, August 18, 2008 10:03 am
>> Subject: st: Problem with ARIMA-ARCH model
>> To: [email protected]
>>
>>
>> > Dear Statalist users,
>> >
>> > I have a DAX stock index return series and I am trying to model its
>> > volatility with ARCH type model. First I modeled the return series
>> > itself to obtain the residuals which enter into the ARCH model. The
>> > most appropriate model for returns was ARIMA (1,0,1) model with no
>> > constant. Then I estimated an ARCH(1) model with the residuals
>> > obtained from ARIMA model. But now, the coefficients of ARIMA model
>> > have completely changed. This is what happened:
>> >
>> > . arima dlndax, arima(1,0,1) noconstant nolog
>> >
>> > ARMA Coef. P>|z|
>> > ar
>> > L1. -.8310875 0.000
>> > ma
>> > L1. .811545 0.000
>> >
>> > . arch dlndax, arch(1) arima(1,0,1) noconstant nolog
>> >
>> > ARMA Coef. P>|z|
>> > ar
>> > L1. .2875023 0.079
>> > ma
>> > L1. -.2352394 0.167
>> >
>> > ARCH Coef. P>|z|
>> > arch
>> > L1. .3028063 0.000
>> > _const. .0001436 0.000
>> >
>> > How come that ARCH estimation affects the ARIMA model? Isn`t this a
>> > one-way road (ex.: ARIMA->get residuals->calculate cond.
>> > variances->estimate ARCH->the end)?
>> >
>> > Thank you for any kind of help,
>> > Vasja Sivec
>> > *
>> > * 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/
> *
> * 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/
>
--
-------------------------------
Joao Ricardo Lima
Professor
UFPB-CCA-DCFS
+553138923914
-------------------------------
*
* 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/
