I know the reason for using squared values is so the values don’t get cancelled out. Why not absolute values? I get it when calculating error metrics that squaring can punish the model more for bigger errors, but I don’t get the reason here.
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There are different measures for volatility. You can consider the mean absolute error or other measure instead of the variance. Variance has a **definition** (involving squares as you know). I am not sure if there is an underlying reason (which you are asking about).
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