- Cover
- Preface to the Second Edition
- Preface to the First Edition
- Notation
- 1 Classical Time Series Models and Financial Series
- Part I: Univariate GARCH Models
- 2 GARCH(p, q) Processes
- 3 Mixing*
- 4 Alternative Models for the Conditional Variance
- 4.1 Stochastic Recurrence Equation (SRE)
- 4.2 Exponential GARCH Model
- 4.3 Log‐GARCH Model
- 4.4 Threshold GARCH Model
- 4.5 Asymmetric Power GARCH Model
- 4.6 Other Asymmetric GARCH Models
- 4.7 A GARCH Model with Contemporaneous Conditional Asymmetry
- 4.8 Empirical Comparisons of Asymmetric GARCH Formulations
- 4.9 Models Incorporating External Information
- 4.10 Models Based on the Score: GAS and Beta‐t‐(E)GARCH
- 4.11 GARCH‐type Models for Observations Other Than Returns
- 4.12 Complementary Bibliographical Notes
- 4.13 Exercises
- Part II: Statistical Inference
- 5 Identification
- 6 Estimating ARCH Models by Least Squares
- 7 Estimating GARCH Models by Quasi‐Maximum Likelihood
- 8 Tests Based on the Likelihood
- 8.1 Test of the Second‐Order Stationarity Assumption
- 8.2 Asymptotic Distribution of the QML When θ 0 is at the Boundary
- 8.3 Significance of the GARCH Coefficients
- 8.4 Diagnostic Checking with Portmanteau Tests
- 8.5 Application: Is the GARCH(1,1) Model Overrepresented?
- 8.6 Proofs of the Main Results
- 8.7 Bibliographical Notes
- 8.8 Exercises
- 9 Optimal Inference and Alternatives to the QMLE*
- Part III: Extensions and Applications
- Appendix B: Ergodicity, Martingales, Mixing
- Appendix B: Autocorrelation and Partial Autocorrelation
- Appendix C: Markov Chains on Countable State Spaces
- Appendix D: The Kalman Filter
- Appendix E: Solutions to the Exercises
- References
- Index
- End User License Agreement
GARCH Models
Structure, Statistical Inference and Financial Applications
Second Edition
Christian Francq
CREST and University of Lille, France
Jean-Michel Zakoian
CREST and University of Lille, France
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