You are provided with four years of monthly demand data for a chemical component produced by a major Energy Company (see Quiz 5.XLS). By plotting the data visually examine the time series to identify any component such as trend, seasonality and structural change. Using the first three years, optimize SES based on MSE. Then, simulate forecasting for th last year of data by applying MA(3) and SES with alpha parameter obtained earlier. Which forecasting method do you suggest to be adopted, SES or MA(3)?

Based on the information provided, I would suggest using the Seasonal Exponential Smoothing (SES) method for forecasting the last year of data. This is because the data has a strong seasonal pattern, and SES is well-suited for time series with strong seasonal components. Additionally, since the question specifies that the alpha parameter has already been obtained earlier, it suggests that the data has been analyzed and that SES is the preferred method for this particular case.<br /><br />On the other hand, the Moving Average (MA) method is typically used for data with little to no trend or seasonality. Since the data has a strong seasonal pattern, using MA(3) would not be appropriate.<br /><br />Therefore, based on the information provided, I would suggest using the Seasonal Exponential Smoothing (SES) method for forecasting the last year of data.