# Is average standard deviation a good way to measure forecasts accuracy?

I have a database of forecasts (ranging from 1 week to 4 weeks in advance) and one of experimentally recorded values for a specific index whose value ranges from 1 to 9 (most of the time it measures 2 or 3, with values 5 and upwards becoming exponentially more rare). I guess I should compare each delta-time separately (1-week, 2-weeks, etc.).

I'd like to get an idea on how accurate these forecasts tend to be. Would average standard deviation be the best way? Or would you suggest something else?

Thank you

Edit: given two sets of variables, A being forecasted number and B number measured, I was thinking about assessing forecast accuracy by doing something like:

$$A_1 - B_1 = |C_1|$$ $$A_n - B_n = |C_n|$$ $$\frac{\sum_i |C_i| }{n} = D$$

And then...I don't know. Advice welcome. Thank you

• Average standard deviation of what quantities?
– whuber
Jan 30, 2020 at 20:19
• Average SD of a single digit index variable.
– Domi
Jan 30, 2020 at 20:27
• When the forecast is a constant, its SD will be as small as possible--but obviously has little to do with accuracy.
– whuber
Jan 30, 2020 at 20:32
• I see, thank you. I am trying to understand how can I assess accuracy of forecasts by comparing the values of that index number in forecasts and the measured values after the even occurred.
– Domi
Jan 30, 2020 at 20:34
• What do you think about my answer? Does it answer your question? If so, you may accept it by clicking on the tick mark to the left. Otherwise, you may ask for further clarification. This is how Cross Validated works. May 2, 2020 at 6:34