[R-SIG-Finance] mean reverting model

[Brian G. Peterson]

rechtsteiner at bgki.net wrote:
> dear list members,
>
> i'm trying to estimate the following two regressions:
>
> (I) v_t - v_t-1 = c*(v_t-1 - v_f) + s_t
>
> where v_t and v_t-1 are market volatility at t resp. t-1; c ist the
> persistence volatility parameter, v_f the long-run fundamental volatility
> and s_t are volatility surprises.
> parameters to estimate are c and v_f.
>
> (II) b_t(z_t) = m + f*(b_t-1(z_t) - m) + k*z_t
> where the b_t(z_t) are estimated in a seperate regression;
> parameters to be estimated are m, the mean reverting beta term, the
> persistence parameter f and the sensitivities k of b towards z.
>
> these equations are used in risk and beta anatomy in the hedge fund
> industry (savona 2008).
>
> my problem is, that i don't know how to estimate the two equations in R. i
> have searched Rsitesearch, google,.. for many hours and didn't find
> anything.
>
> could you please give me a hint?
>   

Sure, there are several books on regression models in R.  Start there.

Regards,

  - Brian