Name
Abstract | ||
|---|---|---|
A closed-form estimator and its several robust versions for the integer-valued GARCH(1, 1) model are proposed. These estimators are easy to implement and do not require the use of any numerical optimization procedure. Consistency and asymptotic normality for the non-robust closed-form estimator is established. The robustification of the closed-form estimator is done by replacing the sample mean and autocorrelations by robust estimators of them, respectively. The performances of these closed-form estimators are investigated and compared via simulations. New estimators are applied to 5 stock-market data sets with different periods and time intervals, and their prediction performances are assessed by in-sample prediction, out-of-sample prediction and scoring rules. Other possible proposals related to the closed-form estimators are also discussed. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.csda.2016.03.006 | Computational Statistics & Data Analysis |
Keywords | Field | DocType |
Autocorrelation function,Closed-form estimator,Robustness,Time series of counts | Econometrics,Efficient estimator,M-estimator,Extremum estimator,Robustification,Minimax estimator,Statistics,Invariant estimator,Mathematics,Estimator,Asymptotic distribution | Journal |
Volume | Issue | ISSN |
101 | C | 0167-9473 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qi Li | 1 | 0 | 0.34 |
| Heng Lian | 2 | 106 | 27.59 |
| Fukang Zhu | 3 | 8 | 3.85 |