Elements of Forecasting, 3e is a concise, modern survey of business and economic forecasting methods. Written by a leading expert on forecasting, it focuses on the core techniques of widest applicability and umes only an elementary background in statistics. It is applications-oriented and illustrates all methods with detailed real-world applications, many of them international in flavor, designed to mimic typical forecasting situations. In many chapters, the application is the centerpiece of the presentation.
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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.
Diebold (economics, finance and statistics, University of Pennsylvania) has added a new chapter on volatility measurement, modeling, and forecasting, plus new problems emphasizing hands-on implementation of methods, to this introductory forecasting text for business, finance, economics, statistics, and even engineering students in a one-semester co
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