Asymptotic Theory for the QMLE in GARCH-X Models With Stationary and Nonstationary Covariates
Bibliographic Data
| ID | 19418206 |
|---|---|
| Authors | Heejoon Han (0000-0003-2474-4146, Kyung Hee University), Dennis Kristensen (0000-0001-9713-1784, Institute for Fiscal Studies) |
| Year | 2014 |
| Volume | 32 |
| Issue | 3 |
| Pages | 416-429 |
| Publication date | 2014-07-03 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Business and Economic Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/07350015.2014.897954 |
| OpenAlex | W2100602094 |
| Language | EN |
| Citations received | 8 |
| References cited | 34 |
This article investigates the asymptotic properties of the Gaussian quasi-maximum-likelihood estimators (QMLE’s) of the GARCH model augmented by including an additional explanatory variable—the so-called GARCH-X model. The additional covariate is allowed to exhibit any degree of persistence as captured by its long-memory parameter dx; in particular, we allow for both stationary and nonstationary covariates. We show that the QMLE’s of the parameters entering the volatility equation are consistent and mixed-normally distributed in large samples. The convergence rates and limiting distributions of the QMLE’s depend on whether the regressor is stationary or not. However, standard inferential tools for the parameters are robust to the level of persistence of the regressor with t-statistics following standard Normal distributions in large sample irrespective of whether the regressor is stationary or not. Supplementary materials for this article are available online
Asymptotic analysis · Autoregressive conditional heteroskedasticity · Covariate · Econometrics · Physics · Statistical physics · Financial Risk and Volatility Modeling · Hydrology and Drought Analysis · Mathematics · Stochastic processes and financial applications · Applied Mathematics
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| Unique citing works | 8 |
|---|---|
| Citations per year | 1,33 |
| Citation span | 2020 - 2026 (7) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 7 |