Richard Harris – Applied Time Series Modelling & Forecasting

Preface.

1. Introduction and Overview.

These are some initial concepts.

Forecasting.

The outline of the book.

2. Short- and long-term-run Models.

Long-run Models.

Stationary and non-stationary- Time Series.

Spurious Regressions

Cointegration.

Short-run Models.

Conclusion.

3. Test for Unit Roots.

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The Dickey–Fuller Test.

Augmented Dickey–Fuller Test.

Tests to determine the power and level of unit root.

Structural Breaks & Unit Root Tests

Roots of Seasonal Units

Structural Breaks, Seasonal Unit Root Tests

Periodic Integration and Unit root-testing.

Conclusion on Unit Root Tests

4. Cointegration in Single Equations

The Engle–Granger (EG) Approach.

Testing for cointegration with a structural break

Alternative approaches

Problems with Single Equation Approach

Estimating the Short-Dynamic Model.

Seasonal cointegration

Periodic Cointegration

Asymmetric tests for cointegration

Conclusion

5. Multivariate Systems – Cointegration

The Johansen Approach.

Test the Order of Integration of the Variables.

Formulation of a Dynamic Model.

Test for a Reduced Rank

Multivariate Model: Deterministic Components

Exogenous Exogeneity Testing and VECM Testing I (l) Variables.

Testing for Linear Hypotheses about Cointegration Relations

Testing for Unique Cointegration Vectors.

Joint Tests of Restrictions α And β Roots of Seasonal Units

Seasonal cointegration

Conclusions.

Appendix 1: Programming in SHAZAM.

6. Modelling The Short-Use Multivariate System.

Introduction.

Estimating the Long-Cointegration Relationships can be created.

Parsimonious VECM.

PVECM Conditional.

Structural Modelling.

Structural Macroeconomic Modelling.

7. Panel Data Models & Cointegration

Introduction.

Panel Data Modelling Techniques.

Panel Unit Root Tests

Testing for cointegration in panels.

Estimating Panel Cointegration Models.

Conclusion: Testing for Unit Roots and Cointegration of Panel Data.

8. Modelling And Forecasting Financial Times Series.

Introduction.

ARCH and GARCH.

Multivariate GARCH.

Estimation & Testing

An Empirical Application for ARCH and GARCH Models.

ARCH-M.

Models of Asymmetric GARCH.

Integrated and Fractionally Integrated GARCH Modells.

Conditional Heteroscedasticity and Unit Roots, as well as Cointegration.

Forecasting GARCH Models

Other Methods of Forecast Evaluation

Conclusions Modelling And Forecasting Financial Time Series.

Appendix: Cointegration Analysis Using the Johansen Technique: A Practitioner’s Guide to PcGive 10.1.

Statistical Appendix.

References.

Index.

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