Question $1$ Description:

Assume you started predicting the Monthly Dividend Rate $(D_t)$ of JEPI since its first ex$-$dividend date on July $1,2020.$ Employ two prediction methods: Exponential Smoothing $($ES$)$ with an alpha smoothing constant of $0\mathrm{.}6($i$.$e$.,$ ES $(0\mathrm{.}6)),$ and Moving Average $($MA$)$ with three months as the time window $($i$.$e$.,$ MA $(3)).$ Calculate the Sum of Squared Errors $($SSE$)$ for the predictions generated by both ES and MA methods. SSE represents the sum of the squared differences between the predicted values and the actual values, reflecting the accuracy of the forecasting models. For the initial value of ES $(0\mathrm{.}6)$ use Monthly Dividend Rate $(D_t)$ on the first ex$-$dividend date of July $1,2020.$ Predict the next Monthly Dividend Rate both with ES and MA assuming next ex$-$dividend date is December $1,2023.$ Below is the itemized summary of the question:

Employ ES $(0\mathrm{.}6)$

Employ MA $(3)$

Report SSE for ES $(0\mathrm{.}6)$

Report SSE for MA $(3)$

Report whether ES $(0\mathrm{.}6)$ predicts more accurately than MA $(3)$ based on SSE.

Predict Monthly Dividend Rate with ES $(0\mathrm{.}6)$ assuming the next ex$-$dividend date is December $1,2023.$

Predict Monthly Dividend Rate with MA $(3)$ assuming the next ex$-$dividend date is December $1,2023.$