I have a series with double seasonality, one daily and one weekly. I modelled the daily seasonality with SARIMA, and I want to include weekly dummy variables.
I only included weekday variables for the times when spikes occur in my data, and dropped the rest. That's how a long term forecast looks with this model:
Now my problem: it isn't supposed to have an upward trend like that.
If I don't include the weekday dummies, it stays on the same level (which I want), but with weekday dummies, the above happens and I have an upward trend (in the spikes).
I don't know why that happens. Any clue why that happens/how I can fix that?
Regardless of the exact SARIMA specification, there is always no trend without dummies, and always a trend when i include "variablewochentag" (German for weekday variable). There are 2 spikes per day in my data, and my data is Mo-Fr, so i have 10 weekday variables. There is also a seasonal difference (65 = daily seasonality) in my estimation, and i have no constant. I have 2080 observations which i used for estimation, added weekday dummies for future observations and then have run the forecast which results in the above picture.
http://www.filedropper.com/data_10 Here is my data. Note: the first 2080 data points are my actual observations, the rest are just zeros + the relevant variables to do the long term forecast. Seasonality is 65 for daily, 325 for weekly.