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Preface
Abbreviations and Notation
1 Introduction
1.1 Types of forecasting method
1.2 Some preliminary questions
1.3 The dangers of extrapolation
1.4 Are forecasts genuinely out-of-sample?
1.5 Brief overview of relevant literature
2 Basics of Time-Series Analysis
2.1 Different types of time series
2.2 Objectives of time-series analysis
2.3 Simple descriptive techniques
2.4 Stationary stochastic processes
2.5 Some classes of univariate time-series model
2.6 The correlogram
3 Univariate Time-Series Modelling
3.1 ARIMA models and related topics
3.2 State space models
3.3 Growth curve models
3.4 Non-linear models
3.5 Time-series model building
4 Univariate Forecasting Methods
4.1 The prediction problem
4.2 Model-based forecasting
4.3 Ad hoc forecasting methods
4.4 Some interrelationships and combinations
5 Multivariate Forecasting Methods
5.1 Introduction
5.2 Single-equation models
5.3 Vector AR and ARMA models
c 2000 by Chapman & Hall/CRC
5.4 Cointegration
5.5 Econometric models
5.6 Other approaches
5.7 Some relationships between models
6 A Comparative Assessment of ForecastingMeth ods
6.1 Introduction
6.2 Criteria for choosing a forecasting method
6.3 Measuring forecast accuracy
6.4 Forecasting competitions and case studies
6.5 Choosing an appropriate forecasting method
6.6 Summary
7 CalculatingI nterval Forecasts
7.1 Introduction
7.2 Notation
7.3 The need for different approaches
7.4 Expected mean square prediction error
7.5 Procedures for calculating P.I.s
7.6 A comparative assessment
7.7 Why are P.I.s too narrow?
7.8 An example
7.9 Summary and recommendations
8 Model Uncertainty and Forecast Accuracy
8.1 Introduction to model uncertainty
8.2 Model building and data dredging
8.3 Examples
8.4 Inference after model selection: Some findings
8.5 Coping with model uncertainty
8.6 Summary and discussion
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