Time$-$series forecasting models are helpful when historical data exists. Toby, a local restaurant owner, is considering using them to forecast monthly demand but is still determining which one to use. He wants to use the one that has the highest responsiveness to change. Which one would be best?

Hint: In forecasting, the highest responsiveness to change means that if the actual demand for something goes up$,$ your prediction for how much you'll need in the future also increases quickly.

Question $9$ options:

Weighted moving average $($n$=3)$

Naive method

Exponential smoothing $($alpha$=0\mathrm{.}5)$

Moving average $($n$=3)$