ASYMPTOTIC THEORY FOR A FACTOR GARCH MODEL
By Christian M. Hafner, Arie Preminger. Econometric Theory, 2009
50 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/8dcaa723d92928d5ecbe6637a9acd73b18c56516
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
- Christian Francq
- Jean-Michel Zakoian
- Alexander Aue
- Esther Ruiz
- Luiz Koodi Hotta
- D. Almeida
- Marie Husková
In Finance
- Lajos Horv'ath
- Alexander Aue
- Christian Francq
- Jean-Michel Zakoian
- Siegfried Hormann
- Marie Husková
- Esther Ruiz
- Josef G. Steinebach
In Statistics and Probability
- Lajos Horv'ath
- Alexander Aue
- Marie Husková
- Siegfried Hormann
- Josef G. Steinebach
- Gregory Rice
- Esther Ruiz
- Luiz Koodi Hotta
Citations in the corpus
- SEQUENTIAL TESTING FOR THE STABILITY OF HIGH-FREQUENCY PORTFOLIO BETAS (2011, methodology): “Other approaches to high-frequency data which model stock prices and instantaneous returns (H → 0) as solutions to stochastic differential equations are discussed in Harrison et al. (1984), Zhang et al. (2005), Barndorff-Nielsen et al.”
- MGARCH models: Trade-off between feasibility and flexibility (2018, background): “Furthermore, Hafner (2003) derives analytical expressions of the fourth order moments of returns and Hafner and Preminger (2009) establish sufficient conditions for geometric ergodicity.”
- Generalized dynamic factor models and volatilities: estimation and forecasting (2017, unknown): “For each of the four quantities appearing in (3.1)-(3.2), wecan think of a conditional heteroskedastic GARCH dynamic scheme of the form exp (χs;it) = ωs;itν 2 s;it, exp (ξs;it) = hs;itǫ 2 s;it, i ∈ N, t ∈ Z (3.10) exp (χw;it) = ωw;itν 2 w;it, exp (ξw;it) = hw;itǫ 2 w;it, i ∈ N, t ∈ Z (3.11) 10See, f”
- Regularly varying multivariate time series (2007, methodology): “In a recent article, Hafner and Preminger (2007) considered a natural generalization of the GARCH(1,1) process to the multivariate setting, called factor GARCH model.”
- Sequential Conditional Correlations: Inference and Evaluation (2009, unknown): “Furthermore, since the dimensions of the parameters’ variance-covariance matrix are at least8 of order 7For example, Comte and Lieberman (2003) and Hafner and Preminger (2009) verify the conditions for consistency and asymptotic normality of the QMLE, but Chen and Fan (2006) and Kawakatsu (2006) do…”
- QML ESTIMATION OF A CLASS OF MULTIVARIATE ASYMMETRIC GARCH MODELS (2011, background): “To our knowledge, CAN results for multivariate GARCH without moments restriction have only been established by Hafner and Preminger (2009), for a factor model of the form FF-GARCH. However, their model is a first-order model (it reduces to the standard GARCH(1,1) when the dimension is one). For univ”
- Multivariate Variance Targeting in the BEKK-GARCH Model (2014, unknown): “As in Comte and Lieberman (2003), Hafner and Preminger (2009b), and Francq, Horváth, and Zakoïan (2011), we assume that{Xt}t=0,...,T is strictly stationary and ergodic: Assumption 4.1 The assumptions of Theorem 2.1 are satisfied, and the observed process {Xt}t=0,...,T is generated by the strictly…”
- GARCH Models (2010, unknown): “The reader may refer to Hafner and Preminger (2009a), Lanne and Saikkonen (2007), van der Weide (2002) and Vrontos, Dellaportas and Politis (2003) for the definition and study of FF-GARCH models of the form (11.26) where P is not assumed to be orthonormal.”