good point paul. so the bar variables must be the grand means of each stock
? definitely not
mean up to that point in time. my bad there.


On Wed, Oct 31, 2012 at 7:04 AM, Paul Teetor <paulteetor@yahoo.com> wrote:

> Thanks for the clarification, Serdar. Three more questions.
>
> Mark Leeds reminded us that your variables are indexed by "i". I assumed
> that referred to the "i-th" security in your CAPM model. Is that correct?
>
> Do you really want phi_1 and phi_2 to be identical for all securities
> (that is, for all "i")?
>
> Also, I believe that four parameters are missing in your list: the initial
> values for alpha, beta, alphabar, and betabar (at time t = 0). Or do you
> have known, initial values?
>
> Paul
>
>
> Paul Teetor, Elgin, IL  USA
> http://quanttrader.info/public
>
>
> ________________________________
>  From: nserdar <snes1982@hotmail.com>
> To: r-sig-finance@r-project.org
> Sent: Wednesday, October 31, 2012 3:36 AM
> Subject: Re: [R-SIG-Finance] Kalman Filter + DLM Package in R
>
> Thanks for your response
>
> Model:
>
> R(it)= Alpha(it)+ Beta(it)R(mt)+ V(it)
>
> KF Mean Reverting
>
> Alpha(it)= Alphabar(i)+ phi* (Alpha(it-1)-Alphabar(i))+W(i1t)
> Beta(it)= Betabar(i)+ phi* (Beta(it-1)-Betahabar(i))+W(i2t)
>
> Parameters are  estimated in  MLE function, these are
>
> Phi_1, Phi_2 ,  Alpha_bar, Beta_bar, Variance(Wi1t), Variance(Wi2t) and
> Variance (Vit)
>
> Some restrictions I need in this process:
>
> 0 <=  Phi_1  and Phi_2  < =1
>
> Variances >0
>
> Alpha_bar and Beta_bar  are close to least square results.
>
> But some resources suggest Alpha is constant, otherwise multicollinearity
> problem can be raised.
>
> Regards,
> Serdar
>
>
>
>
>
>
> --
> View this message in context:
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>
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