A survey of business and economics forecasting methods, this text focuses on the core techniques of widest applicability and assumes only an elementary background in statistics. It is applications-oriented and illustrates all methods with detailed examples and case studies.

Review

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.

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