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- Title
Quasi‐maximum exponential likelihood estimation for double‐threshold GARCH models.
- Authors
Zhang, Tongwei; Wang, Dehui; Yang, Kai
- Abstract
We consider the nonparametric inference for the double‐threshold generalized autoregressive conditional heteroscedastic models. The quasi‐maximum exponential likelihood estimators (QMELEs) of the model parameters are obtained, and their asymptotic properties are established. Simulation studies imply that the estimators are asymptotically normally distributed. An empirical investigation of stock returns illustrates our findings. Both the simulations and the example indicate that the QMELE is feasible, reliable and appropriate to fit the financial time series data of the Hang Seng Index.
- Subjects
GARCH model; HANG Seng Index; TIME series analysis; HETEROSCEDASTICITY
- Publication
Canadian Journal of Statistics, 2021, Vol 49, Issue 4, p1152
- ISSN
0319-5724
- Publication type
Article
- DOI
10.1002/cjs.11614