Chapter 5 Assignment – FIN 335 Forecasting Methods
(Due 5/2/13)
Table B.8 in the text contain U.S. unemployment rates from January 1963 – December
2001. The JMP data set is linked on the course1 website (Unemployment US.JMP). For
this problem you should use Example 2 in the Seasonal ARIMA section to fit an
appropriate model to these data.
Create a test data set by extracting the last two years of data from the original
spreadsheet and save this data file as US Unemployment (test).JMP. (2 pts.)
b) Create a training data set by deleting the last two years of data (i.e. delete the last
24 rows) from this time series and save this data files as US Unemployment
(train).JMP. (2 pts.)
c) Use training data to fit an appropriate exponential smooth model to this time
series. Change the number of forecast periods from 25 to 24.
a)
Summarize the results of the exponential smooth:
 Find the R2, AIC, MAPE and MAE. Discuss.
 Examine the residuals from the exponential fit. Discuss.
(10 pts. Total)
d) Save the forecast results for the next 24 time periods. Compare the forecasted
values from exponential smooth to the actual values that are contained in the
data file you created in part (a). Calculate the MAPE and MAE for these
forecasts. (8 pts.)
e) Using training data to fit an appropriate seasonal ARIMA model to this time
series. Change the number of forecast periods from 25 to 24.
Summarize the results:
 What differencing did you use to create stationarity? Justify your choice.
 What seasonal ARIMA model did you use? Justify your choice.
 Find the R2, AIC, MAPE and MAE. Discuss. How do these values
compare to those for the exponential smoothing model from part (c)?

Examine the residuals from the seasonal ARIMA fit. Discuss.
(15 pts. Total)
f)
Save the forecast results for the next 24 time periods. Compare the forecasted
values from the seasonal ARIMA to the actual values that are contained in the
test dataset you created in part (a). Calculate the MAPE and MAE for these
forecasts. Which model performs better: exponential smoothing or seasonal
ARIMA? Explain. (10 pts.)