Incluye referencias bibliograficas. Bibliografía: p. 355-360.

1. Introduction to Forecasting: Applications, Methods, Books, Journals, and Software. Appendix: The Linear Regression Model. 2. Six Considerations Basic to Successful Forecasting. 3. Statistical Graphics for Forecasting. 4. Modeling and Forecasting Trend. 5. Modeling and Forecasting Seasonality. 6. Characterizing Cycles. 7. Modeling Cycles: MA, AR, and ARMA Models. 8. Forecasting Cycles. 9. Putting it All Together: A Forecasting Model with Trend, Seasonal, and Cyclical Components. 10. Forecasting with Regression Models. 11. Evaluating and Combining Forecasts. 12. Unit Roots, Stochastic Trends, ARIMA Forecasting Models, and Smoothing. 13. Volatility Measurement, Modeling and Forecasting.

Focuses on the core techniques of wide applicability and assumes an elementary background in statistics. This applications-oriented work illustrates the methods with real-world applications, many of them international in flavor, designed to mimic typical forecasting situations.