n order to measure the accuracy of highly intermitted demand time series, I recently discovered a new accuracy measure, that overcomes the problem of zero values and values close to zero, when comparing a test forecast to the actual values. This is pretty useful, when it comes to forecast intermittent demand.
I am able to understand the simple calculation of measures like RMSE and MAPE, however, when it comes to MAAPE I do struggle, to understand the math behind it.
I found this paper, which is explaining it in very theoretical terms: https://www.sciencedirect.com/science/article/pii/S0169207016000121
In the abstract it sums up the meaning of MAAPE like this:
In essence, MAAPE is a slope as an angle, while MAPE is a slope as a ratio, considering a triangle with adjacent and opposite sides that are equal to an actual value and the difference between the actual and forecast values, respectively.
However, I could not find any simple example of MAAPE's calculation. The easiest way, to explain it to a customer would be some easy to understand visualizations or even a calculation done in excel.