R help - Sep 2009 - Re cursive regression

Hi there, I'm in desperate need to figure out how to solve this issue.
I need to estimate a recursive model for a time series data of asset
returns. The dependent variable is the asset return and then I have a set of
k variables, a lagged value of the dependent variable (plus an intercept) as
regressors. My sample period (monthly observations) starts on Jan 1972. What
I need to do is the following:

1)use a moving window regression (window of 60 observations, i.e. 5 years)
2)estimate all the possible model (Jan 1972 Dec 1977) using a subset of the
k variables (intercept and lagged values always present) and choose the best
model according to thee AIC criterion
3)once the best model is chosen, make one-step ahead prediction with that
model
4)go back to step 2 shifting the sample period one month ahead (i.e. Feb
1972, Jan 1978) and then repeat step 2 and 3
5)keep going until the end of the sample (May 2009)

Hope it helps
-- 
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There is a huge literature on time series analysis with many 
functions and contributed packages in R, including many different ways 
"to estimate a recursive model". 


      If you are working with "asset returns", I suggest you start
with
Diethelm W?rtz, Yohan Chalabi, William Chen, Andrew Ellis (2009) 
Portfolio Optimization with R/Rmetrics (www.rmetrics.org/ebook.htm) and 
the companion Rmetrics bundle documented in that book.  You may also be 
interested in Ruey Tsay (2005) Analysis of Financial Time Series (Wiley) 
and the companion "FinTS" package on CRAN.  For recursive regression,
I
suggest you consider Giovanni Petris, Sonia Petrone, and Patrizia 
Campagnoli (2009) Dynamic Linear Models with R (Springer) and the 
companion "dlm" package. 


      There are many other books discussing time series mentioned on 
"http://www.r-project.org/doc/bib/R-books.html". 


      Beyond that, I suggest you acquaint yourself with the 
"RSiteSearch" function an the "sos" package to help search
capabilities
available in R. 


      Hope this helps. 
      Spencer Graves


manta wrote:
> Hi there, I'm in desperate need to figure out how to solve this issue.
> I need to estimate a recursive model for a time series data of asset
> returns. The dependent variable is the asset return and then I have a set
of
> k variables, a lagged value of the dependent variable (plus an intercept)
as
> regressors. My sample period (monthly observations) starts on Jan 1972.
What
> I need to do is the following:
>
> 1)use a moving window regression (window of 60 observations, i.e. 5 years)
> 2)estimate all the possible model (Jan 1972 Dec 1977) using a subset of the
> k variables (intercept and lagged values always present) and choose the
best
> model according to thee AIC criterion
> 3)once the best model is chosen, make one-step ahead prediction with that
> model
> 4)go back to step 2 shifting the sample period one month ahead (i.e. Feb
> 1972, Jan 1978) and then repeat step 2 and 3
> 5)keep going until the end of the sample (May 2009)
>
> Hope it helps
>   

-- 
Spencer Graves, PE, PhD
President and Chief Operating Officer
Structure Inspection and Monitoring, Inc.
751 Emerson Ct.
San Jos?, CA 95126
ph:  408-655-4567