SEQUENTIAL CHANGE-POINT DETECTION IN GARCH(p,q) MODELS
By István Berkes, Edit Gombay, Lajos Horv'ath, Piotr Kokoszka. Econometric Theory, 2004
144 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/188474766e6cc365735eb202a7573bc781fc6e0f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Lajos Horv'ath
- Alexander Aue
- Gregory Rice
- Cristina Amado
- Timo Teräsvirta
- Remigijus Leipus
- Liudas Giraitis
- Donatas Surgailis
In Finance
- Lajos Horv'ath
- Alexander Aue
- Gregory Rice
- Timo Teräsvirta
- Donatas Surgailis
- Liudas Giraitis
- Matthew Reimherr
- Remigijus Leipus
In Statistics and Probability
- Gregory Rice
- Lajos Horv'ath
- Alexander Aue
- Matthew Reimherr
- Cristina Amado
- Liudas Giraitis
- Donatas Surgailis
- Timo Teräsvirta
Citations in the corpus
- Delay times of sequential procedures for multiple time series regression models (2009, methodology): “Other contributions in the literature are based on moving sum (MOSUM) procedures which generally have the advantage of faster detection times when compared to the corresponding CUSUM procedures (see, for example, Chu et al. (1995a,b)). On the other hand, Horváth et al. (2008) have shown that the app”
- SEQUENTIAL TESTING FOR THE STABILITY OF HIGH-FREQUENCY PORTFOLIO BETAS (2011, unknown): “, 2007), GARCH processes (Berkes et al., 2004), and multiple time series regressions (Aue et al.”
- Extensions of some classical methods in change point analysis (2014, methodology): “The rate of convergence in the Darling–Erdős type limit results is slow [cf. Berkes et al. (2004c)], so we used the recommended 0.05 critical value in Gombay and Horváth (1996) (the red line in the right panel).”
- Conditional Correlation Models of Autoregressive Conditional Heteroscedasticity With Nonstationary GARCH Equations (2014, methodology): “When Gt ≡ IN and the conditional correlation matrix Pt ≡ P, one obtains the Constant Conditional Correlation (CCC-) GARCH model of Bollerslev (1990). More generally, when Gt ≡ IN and Pt is a timevarying correlation matrix, the model belongs to the family of Conditional Correlation GARCH models.”
- Recent Advances in ARCH Modelling (2007, background): “where gj (8) and νt ≡ σ(2) t (ε(2)t − Eε(2)t ) are martingale differences.”
- Structural breaks in time series (2013, background): “For example, Bhattacharya et al. (1983) showed that the so-called Hurst effect (to achieve convergence, partial sums have to be scaled with n, H 1⁄4 12 þ d being the Hurst parameter, and d > 0) can also be explained in a short memory scenario if structural breaks in the mean are allowed. Giraitis et”