I have a time series
y that has both positive and negative that I want to predict. For the prediction I normalize the values to a range between 0 and 1.
If I give the normalized actual and forecast data in
WMAPE, I get an error of ~5%.
However, if I denormalize the actual data and forecast data back to the original span with negative and positive values and then put them into
WMAPE, I get an error of ~15%.
Which of the error measurements is correct?