Estimation and testing stationarity for double‐autoregressive models

By S. Ling. 2004

136 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/ca25962e7e5e7a65ab8833b18de8ad74041d8efb

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

1. Jean-Michel Zakoian
2. Christian Francq
3. S. Ling
4. Heino Bohn Nielsen
5. Dong Li
6. Anders Rahbek
7. Liang Peng
8. Olivier Wintenberger

In Finance

1. Jean-Michel Zakoian
2. Christian Francq
3. S. Ling
4. Dong Li
5. Anders Rahbek
6. Heino Bohn Nielsen
7. Liang Peng
8. Olivier Wintenberger

In Statistics and Probability

1. Christian Francq
2. Jean-Michel Zakoian
3. Dong Li
4. S. Ling
5. Anders Rahbek
6. Heino Bohn Nielsen
7. Liang Peng
8. Lu-Hung Chen

Citations in the corpus

• Conditional variance estimation in heteroscedastic regression models (2009, background): “See Borkovec (2001), Borkovec and Klüppelberg (2001) for probabilistic properties and Ling (2004) and Chan and Peng (2005) for statistical properties of such AR(1) processes with ARCH(1) errors.”
• Optimal predictions of powers of conditionally heteroscedastic processes (2013, methodology): “For instance, Ling (2004) introduced a class of double-auto-regressive models and studied the properties of the QMLE, whereas Audrino and Bühlmann (2009) developed estimation procedures for a non-parametric class.”
• Asymptotic inference for a nonstationary double AR(1) model (2008, methodology): “This is the idea used by Ling (2007a) for the stationarity condition of the higher-order dar model.”
• A Double AR(p) Model: Structure and Estimation (2007, unknown): “Ling (2004) showed that the MLE of the parameters in (1.1) with p = 1 is consistent and asymptotically normal only under the strict stationarity condition.”
• Self-weighted and local quasi-maximum likelihood estimators for ARMA-GARCH/IGARCH models (2007, methodology): “This paper is the revised version of Ling (2003), which included the self-weighted LSE for the ARMA-GARCH model and was completed when the author visited the Department of Statistics, Stanford University.”
• Unit root vector autoregression with volatility induced stationarity (2014, methodology): “For an introduction to the recent univariate DAR models, inference and estimation have been explored for univariate DAR models in Ling (2004, 2007) and Ling and Li (2008), while extremal and tail behavior have been analyzed for DAR models of order one in Borkovec (2000), Borkovec and Klüppelberg…”
• Risk-parameter estimation in volatility models (2012, background): “For instance, Ling (2004) introduced a class of double-autoregressive models and studied the properties of the QMLE.”