# The data in Table P-12 are weekly prices for IBM stock. a. Using a program for ARIMA modeling, obtain a plot of the data, the sample autocorrelations, and the sample partial autocorrelations. Use this information to tentatively identify an appropriate ARIMA model for this series.b. Is the IBM series stationary? What correction would you recommend if the series is nonstationary?c.

a. Using a program for ARIMA modeling, obtain a plot of the data, the sample autocorrelations, and the sample partial autocorrelations. Use this information to tentatively identify an appropriate ARIMA model for this series.

b. Is the IBM series stationary? What correction would you recommend if the series is nonstationary?

c. Fit an ARIMA model to the IBM series. Interpret the result. Are successive changes random?

d. Perform diagnostic checks to determine the adequacy of your fitted model.

e. After a satisfactory model has been found, forecast the IBM stock price for the first week of January of the next year. How does your forecast differ from the naive forecast, which says that the forecast for the first week of January is the price for the last week in December (current price)?

## This problem has been solved!

**Related Book For**