Maximum likelihood estimation of STAR and STAR-GARCH models: Theory and Monte Carlo evidence

Journal of Applied Econometrics

Volumn 17, Issue 5, 2002, Pages 509-534

  Chan, Felix ^a   McAleer, Michael ^a  

^a UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0036403577     PISSN: 08837252     EISSN: None     Source Type: Journal    
DOI: 10.1002/jae.686     Document Type: Article

References (33)

1. Berndt E, Hall B, Hall R, Hausman J. 1974. Estimation and inference in non-linear structural models. Annals of Economic and Social Measurement 3: 653-665.
2. Bollerslev T. 1986. Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics 31: 307-327.
3. Bougerol P, Picard N. 1992. Stationarity of GARCH processes and of some non-negative time series. Journal of Econometrics 52: 115-127.
4. Boussama F. 2000. Asymptotic normality for the quasi-maximum likelihood estimator of a GARCH model. Comptes Rendus de l'Acadèmie des Sciences, Sèrie I 331: 81-84 (in French).
5. Brooks C, Burke S, Persand G. 2001. Benchmarks and the accuracy of GARCH model estimation. International Journal of Forecasting 17: 45-56.
6. van Dijk D, Teräsvirta T, Franses P. 2002. Smooth transition autoregressive models - a survey of recent developments. Econometric Reviews 21: 1-47.
7. Ding Z, Granger C, Engle R. 1993. A long memory property of stock market returns and a new model. Journal of Empirical Finance 1: 83-106.
8. Elie L, Jeantheau T. 1995. Consistency in heteroskedastic models. Comptes Rendus de l'Acadèmie des Sciences, Sèrie 1 320: 1255-1258 (in French).
9. Engle R. 1982. Autoregressive conditional heteroscedasticity, with estimates of the variance of United Kingdom inflation. Econometrica 50: 987-1007.
10. Franses P, van Dijk D. 2000. Non-linear Time Series Models in Empirical Finance. Cambridge University Press: New York.
11. Franses P, Neele J, van Dijk D. 1998. Forecasting volatility with switching persistence GARCH models. Econometric Institute Report, E1-9819.
12. Haggan V, Ozaki T. 1981. Modelling nonlinear random vibrations using an amplitude-dependent autoregressive time series model. Biometrika 68: 189-196.
13. He C, Teras̈virta T. 1999a. Properties of moments of a family of GARCH processes. Journal of Econometrics 92: 173-192.
14. He C, Teräsvirta T. 1999b. Fourth moment structure of the GARCH(p, q) process. Econometric Theory 15: 824-846.
15. Jeantheau T. 1998. Strong consistency of estimators for multivariate ARCH models. Econometric Theory 14: 70-86.
16. Ling S. 1999. On the probabilitistic properties of a double threshold ARMA conditional heteroscedasticity model. Journal of Applied Probability 36: 1-18.
17. Ling S, Li W. 1997. On fractional integrated autoregressive moving average time series models with conditional heteroscedasticity. Journal of the American Statistical Association 92: 1184-1194.
18. Ling S, McAleer M. 2002a. Necessary and sufficient moment conditions for the GARCH(r, s) and asymmetric power GARCH(r, s) models. Econometric Theory 18: 722-729.
19. Ling S, McAleer M. 2002b. Stationary and the existence of moments of a family of GARCH processes. Journal of Econometrics 106: 109-117.
20. Ling S, McAleer M. 2002c. Asymptotic theory for a vector ARMA-GARCH model. To appear in Econometric Theory.
21. Ling S, McAleer M. 2002d. On adaptive estimation in nonstationary models with GARCH errors. To appear in Annals of Statistics.
22. Lundbergh S, Teräsvirta T. 1999. Modelling economic high frequency time series with STAR-STGARCH models. SSE/EFI Working Paper Series in Economics and Finance, No. 291.
23. Lundbergh S, Teräsvirta T. 2000. Forecasting with smooth transition autoregressive models. SSE/EFI Working Paper Series in Economics and Finance, No. 390.
24. Mak T, Wong H, Li W. 1997. Estimation of nonlinear time series with conditional heteroscedasticity variances by iteratively weighted least squares. Computational Statistics & Data Analysis 24: 169-178.
25. Milhöj A. 1985. The moment structure of ARCH processes. Scandinavian Journal of Statistics 12: 281-292.
26. Nelson D. 1990. Stationarity and persistence in the GARCH(1,1) model. Econometric Theory 6: 318-334.
27. Pantula S. 1989. Estimation of autoregressive models with ARCH errors. Sankhya B 50: 119-138.
28. Pötscher B, Prucha I. 1997. Dynamic Nonlinear Econometric Models - Asymptotic Theory. Springer-Verlag: New York.
29. Teras̈virta T. 1994. Specification, estimation and evaluation of smooth transition autoregressive models. Journal of the American Statistical Association 89: 208-218.
30. Tong H. 1978. On a threshold model. In Pattern Recognition and Signal Processing, Chen C (ed.). Sijhoff and Noordoff: Amsterdam; 101-141.
31. Tong H, Lim K. 1980. Threshold autoregressive, limit cycles and data. Journal of the Royal Statistical Society B 42: 245-292.
32. Weiss A. 1986. Asymptotic theory for ARCH models: estimation and testing. Econometric Theory 2: 107-131.
33. Wooldridge J. 1994. Estimation and Inference for Dependent Processes. In Aspects of Modelling Nonlinear Time Series, Engle RF, McFadden DL (eds). Elsevier Science: Amsterdam; 2639-2738.