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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