WEIGHTED LEAST ABSOLUTE DEVIATIONS ESTIMATION FOR ARMA MODELS WITH INFINITE VARIANCE

By Jiazhu Pan, Hui Wang, Qiwei Yao. Econometric Theory, 2007

55 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

ESTIMATION FOR A NONSTATIONARY SEMI-STRONG GARCH(1,1) MODEL WITH HEAVY-TAILED ERRORS (2009, methodology): “By Theorem 2 and using the same method of Theorem 3 in Pan, Wang, and Yao (2007), we can obtain that f̂∗(0) and ̂∗ are consistent estimators for f (0) and , respectively.”
Quantile Regression Estimator for GARCH Models (2013, background): “Some authors such as Davis & Dunsmuir (1997), Peng & Yao (2003), and Pan et al. (2007) have established the asymptotic normality of a sequence of local minimizers in M-estimation (and also in LAD), which, however, does not necessarily mean the √ n-consistency of global minimizers.”
LADE-Based Inference for ARMA Models With Unspecified and Heavy-Tailed Heteroscedastic Noises (2015, background): “When Eε2t = ∞, Davis, Knight, and Liu (1992) and Mikosch et al. (1995) obtained the limiting distribution of the M-estimator and Whittle estimator, respectively; and Pan, Wang, and Yao (2007) and Zhu and Ling (2012) considered the self-weighted LADE (SLADE).”