[R-SIG-Finance] garchFit and garchSim

[Andrey Riabushenko]

Yes, I meant presample indeed.

I see that it needs to be a thee column matrix, but I don't understand how to 
get this columns from the times series of the returns that I have.

> Hi,
>
> I guess you meant 'presample'. It is a matrix of starting values for the
> modeled series, h.t and innovations (with zero mean and unit variance).
> Have a look at the help page for garchSpec. I think the arma simulation is
> OK if n.ahead = 1. I would say it is possible to simulate an arma process
> with garchSim when you set the parameters of the conditional distribution
> to zero but I have never done it myself.
>
> Regards,
>
> Michal
>
>
>
>
> ----- Original Message ----
> From: Andrey Riabushenko <cdome at bk.ru>
> To: r-sig-finance at stat.math.ethz.ch
> Sent: Friday, May 16, 2008 3:35:17 PM
> Subject: [R-SIG-Finance] garchFit and garchSim
>
> Hi !
>
> I am trying to fit garch(1,1) model to stock returns using fGarch.
>
> m = garchFit(~garch(1,1), data = returns)
>
>
> But next I need to do 100 simulations of future returns. I am trying to use
> garchSim for that
> I have extracted estimated alpha, beta and omega
>     params = model at fit$matcoef[,1]
>     mu = params[1]
>     omega = params[2]
>     alpha = params[3]
>     beta = params[4]
>
> and i trying to do future simulation of returns
>     sim = mu + garchSim(list(alpha = alpha, beta = beta, omega = omega),
> resample=???)
>
> I see that there is a resample parameter in garchSim function, but can't
> figure out how to use it, docs do not help.
>
> Please help me, I am writing my MA theses and only one week is left till
> submission and my supervisor can't help with that.
>
>
> P.S.
> Also I have done similar thing, but using arima model. Please, check it if
> I am  doing everything right, because I  not sure about it.
>
> forecast_arima = function (returns, n.ahead) {
>     model = armaFit(~arma(10, 5), data=returns)
>     c = coef(model)
>     arma_mean = c["intercept"]
>     arma_ar = c[1:10]
>     arma_ma = c[11:15]
>
>     m = matrix(NA, n.ahead, MAX_SIM)
>
>     for(i in 1:MAX_SIM) {
>     m[,i] = arma_mean + armaSim(list(ar = arma_ar, ma = arma_ma, d=0), n =
> n.ahead, start.innov = as.vector(returns))
>     }
>     return(m)
> }
>
>
> Thank you for you expertise.
>
> _______________________________________________
> R-SIG-Finance at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-finance
> -- Subscriber-posting only.
> -- If you want to post, subscribe first.