
Dear all,

I have spent the last few days on a seemingly simple and previously documented rolling regression.

I have a 60 year data set organized in a ts matrix. 
The matrix has 5 columns; cash_ret, epy1, ism1, spread1, unemp1

I have been able to come up with the following based on previous help threads. It seems to work fine.
The trouble is I get regression coefficients but need the immediate next period forecast.

cash_fit= rollapply(cash_data, width=60, 

function(x) coef(lm(cash_ret~epy1+ism1+spread1+unemp1, data = as.data.frame(x))), 

by.column=FALSE, align="right"); cash_fit


I tried to replace "coef" above to "predict" but I get a whole bunch of results too big to be displayed. I would be grateful 
if someone could guide me on how to get the next period forecast after each regression. 

If there is a possibility of getting the significance of each regressor and the standard error in addition to R-sq 
without having to spend the next week, that would be helpful as well.

Many thanks,
Darius




 		 	   		  
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