This extra credit forecasting assignment is available for the next two weeks. I have provided two "mystery" time series below. Each is a real world, quarterly time series, that has been transformed in some way so that you cannot discover (easily) its true identity. Your assignment is to create a 1-year (4-quarter) forecast for each series (e.g., for Series X this means providing a forecast for the four quarters of year15 i.e., 15.1, 15.2, 15.3, and 15.4). You can use any method or combination of methods that you feel is best. After the due date, I will reveal the actual values for the next 4 quarters and, for each series, 15 points extra credit will be awarded to the most accurate forecast based on MSE. (Other, less accurate forecasts will receive extra credit points based on their accuracy in comparison to the most accurate forecast).
To submit the extra credit assignment, upload a spreadsheet to the appropriate D2L dropbox containing your forecast as well as a description of how it was created (any transformation you made to the series, which observations were used in the calculation, what technique, etc.). You should provide enough detail that someone else could replicate your forecast exactly.
Extra Credit Assignment This extra credit forecasting assignment is available for the next two weeks. I have provided two "mystery" time series below. Each is a real world, quarterly time series, that has been transformed in some way so that you cannot discover (easily) its true identity. Your assignment is to create a 1-year (4-quarter) forecast for each series (e.g., for Series X this means providing a forecast for the four quarters of year 15 i.e., 15.1, 15.2, 15.3, and 15.4). You can use any method or combination of methods that you feel is best. After the due date, I will reveal the actual values for the next 4 quarters and, for each series, 15 points extra credit will be awarded to the most accurate forecast based on MSE. (Other, less accurate forecasts will receive extra credit points based on their accuracy in comparison to the most accurate forecast). To submit the extra credit assignment, upload a spreadsheet to the appropriate D2L dropbox containing your forecast as well as a description of how it was created (any transformation you made to the series, which observations were used in the calculation, what technique, etc.). You should provide enough detail that someone else could replicate your forecast exactly.