A Survey of Recent Theoretical Results for Time Series Models with GARCH Errors

By Wai Keung Li, S. Ling, Michael Mcaleer. 2001

307 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/3b9717bf15408f904557e31d2be4f45f6aaa3c8e

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. Michael Mcaleer
2. Stavros Degiannakis *
3. Timo Teräsvirta
4. Marcelo C. Medeiros
5. Jean-Michel Zakoian
6. Christian Francq
7. Bernardo da Veiga
8. Christian M. Hafner

In Finance

1. Michael Mcaleer
2. Timo Teräsvirta
3. Jean-Michel Zakoian
4. Christian Francq
5. Stavros Degiannakis *
6. Marcelo C. Medeiros
7. Liudas Giraitis
8. Bernardo da Veiga

In Statistics and Probability

1. Michael Mcaleer
2. Marcelo C. Medeiros
3. Timo Teräsvirta
4. Bernardo da Veiga
5. Ke-Li Xu
6. Peter C. B. Phillips
7. Liudas Giraitis
8. Donatas Surgailis

Citations in the corpus

• An Introduction to Univariate GARCH Models (2006, background): “Theoretical results on time series models with conditional heteroskedasticity are also reviewed in Li et al. (2002) .”
• Self-weighted and local quasi-maximum likelihood estimators for ARMA-GARCH/IGARCH models (2007, unknown): “Li et al. (2002) identified this as an open problem.”
• Single Index and Portfolio Models for Forecasting Value-at-Risk Thresholds * (2008, methodology): “Likelihood Estimation (QMLE) method (see, for example, Li, Ling and McAleer (2002) ).”
• Recent Advances in ARCH Modelling (2007, methodology): “(21) Kazakevičius and Leipus (2002) showed that in the GARCH(p, q) case, the top Lyapunov exponent satisfies γ = − log R, (22) Liudas Giraitis, Remigijus Leipus and Donatas Surgailis where R = lim sup n σ 2 0,n −1 ∈ [0, ∞] is the convergence radius of the random power series σ 2 t (z) = b 0 1 + ∞ n=”
• Adaptive Estimation of Autoregressive Models with Time-Varying Variances (2008, methodology): “Efficient estimation of the mean function in this case is achieved by quasi-maximum likelihood-based or other adaptive procedures, and recent developments on this topic have been surveyed by Li et al. (2002). Although the GARCH-type model is successful in capturing many important features in macroec”
• Structure and Asymptotic Theory for Multivariate Asymmetric Conditional Volatility (2009, methodology): “VARMA– Ling and McAleer (2003a) No Yes Yes 1 2 m(m + 5) GARCH DCC Engle (2002) No Yes Yes 1 2 m(m + 5) + 2”
• Backtesting Parametric Value-at-Risk With Estimation Risk (2010, background): “See Li, Ling, and McAleer (2002) for a review of estimators for β0.”