I've got this prediction problem for daily data across several years. My data has both yearly and weekly seasonality. It's also stationary.
I tried using the following recurrence:(which I just came up with, from nowhere if you like) xn = 1/4(xn-738 + xn-364 + xn-7 + 1/6(xn-1+xn-2+xn-3+xn-4+xn-5+xn-6)
Basically, I am taking into consideration some of the previous days in the week before the day I am trying to predict and also the corresponding day a year and two years earlier. I am doing an average over them.
Why or Why not would such a formula be a good idea and can I improve this FOR example by adding some terms sampled from a distribution or in another way? Thanks!