# WMAPE / WAPE for the evaluation of time series with positive and negative values

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 WAPE / 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 WAPE \ WMAPE, I get an error of ~15%.

Which of the error measurements is correct?