[R-sig-finance] tips and tricks for rolling regressions?

[Gregor.gawron at rmf.ch]

There is a 'running' function in the gregmisc package which I slightly
changed to suit my calcualtions. Below the code for doing one-step ahead
GARCH(1,1) estimations. This is just an extraction of a longer code for
various purposes, so it is surely not the nicest one. However, you can
easily replace the 'garch' function with 'lm' and adjust the output to
your needs.
-----------------------------------------
#moving one-step-ahead GARCH(1,1)
library(tseries)

width<-1500 #the size of the sample window
                        
data(EuStockMarkets) #data taken from package 'tseries'
X<- diff(log(EuStockMarkets))[,"DAX"]

n<-length(X)
from<-sapply((1:n)-width+1,function(x) max(x,1))
to<-1:n
all.elements<-apply(cbind(from,to),1,function(x) seq(x[1],x[2])) 
good.elements<-all.elements[width:length(all.elements)]
better.elements<-as.data.frame(good.elements)

#estimating GARCH(1,1) and extracting the fitted coefficients
myfun<-function(i){
    out<-garch(X[better.elements[,i]])
    garchsum<-summary(out)[[2]][1:3]
    names(garchsum)<-NULL
    return(garchsum)
}

res<-sapply(1:length(better.elements),function(i) myfun(i))
    
#adjusting the output
RES<-matrix(unlist(res))
dim(RES)<-dim(res)
dimnames(RES)<-list(c("a0","a1","b1"),NULL)        
(RES<-t(RES))
---------------------------------------------------



-----Original Message-----
From: r-sig-finance-bounces at stat.math.ethz.ch
[mailto:r-sig-finance-bounces at stat.math.ethz.ch] On Behalf Of Taher Khan
Sent: Mittwoch, 25. August 2004 13:32
To: r-sig-finance
Subject: [R-sig-finance] tips and tricks for rolling regressions?


Greetings!

I want to find out if there is a clever way to do a one-step-ahead
moving window rolling regression using a vectorized operation like with
apply, rather than a for loop.

Does anyone have a code snippet they would like to share for how they do
rolling regressions?!?!

Thanks in advance!

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