I have two time series of daily data. One is
sign-ups and the other
terminations of subscriptions. I'd like to predict the latter using the information contained in both variables.
Looking at the graph of these series it's obvious that terminations are correlated with multiples of the sign-ups the months before. That is, a spike in sign-ups on May 10th, will lead to an increase in terminations in June 10th, July 10th and August 10th and so on, although the effect wears off.
I'm hoping to get a hint as to which models I might employ to model this specific problem. Any advice would be much appreciated..
So far, I've been thinking a VAR model, but I'm not sure how to include the monthly effect - use a really high order of lags or add a seasonal component somehow?