Local Polynomial Whittle Estimation of Long-range Dependence
By Donald W. K. Andrews, Yixiao Sun. 2001
138 citations recorded by the source corpus.
Subfields: Finance, Global and Planetary Change, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/769c2d7c8c4739b38d938be9e9744c61d371e0a3
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In Finance
- Jie Hou
- Pierre Perron
- Franccois Roueff
- Gilles Faÿ
- Murad S. Taqqu
- Eric Moulines
- Per Frederiksen
- Liudas Giraitis
In Global and Planetary Change
- Per Frederiksen
- Violetta Dalla
- J. Hidalgo
- Frank Nielsen
- Gilles Faÿ
- Murad S. Taqqu
- Jie Hou
- Eric Moulines
In Statistics and Probability
- Pierre Perron
- Franccois Roueff
- Per Frederiksen
- Violetta Dalla
- J. Hidalgo
- Frank Nielsen
- Gilles Faÿ
- Murad S. Taqqu
Citations in the corpus
- Local Polynomial Whittle Estimation of Perturbed Fractional Processes (2008, methodology): “Finally, as in Andrews & Sun (2004) we could calculate the asymptotic bias which is of order O((m=n)'y + (m=n)2d0+'w), where 'a = min fsa; 2 + 2Rag ; a = y; w, see the proof of Lemma 3(e) in the appendix.”
- Estimators of Long-Memory: Fourier versus Wavelets (2008, methodology): “It seems that the log2(mn) term in these assumptions is superfluous (see (Andrews and Sun, 2004, Comments of Assumption 4) for the required adaptation of the proof).”
- Semiparametric inference in multivariate fractionally cointegrated systems (2010, unknown): “With respect to f̂ , Parzen (1957) employed higherorder kernels in the frequency domain, while with respect to the δ̂’s Andrews and Sun (2004), Hurvich andBrodsky (2001),Moulines and Soulier (1999) and Robinson and Henry (2003) employed various methods (albeit justified only in case of integration o”
- Long Memory and the Relation between Implied and Realized Volatility (2006, unknown): “σt = α ∗ + β∗σBS t + γRPt + et, (5) where RPt denotes a time varying volatility risk premium.”
- Consistent estimation of the memory parameter for nonlinear time series (2006, methodology): “Various bias-reduction methods for linear and signal plus noise models were discussed by Sun and Phillips (2003), Hurvich et al. (2005) and Andrews and Sun (2004).”
- Nonstationarity-Extended Local Whittle Estimation (2007, unknown): “Under some additional restrictions, the optimal m can be chosen using the data driven methods of Henry and Robinson (1996) or Andrews and Sun (2004). Although there is no known general way to choose an optimal bandwidth for Whittle estimators, the results of this simulation exercise, together with t”
- Local Whittle estimation in nonstationary and unit root cases (2004, unknown): “,m, E|wu(λj)−C(ej )wε(λj)|(2) = 1⁄2 O(n−β), for β ∈ (0, 1), O(n−1 logn), for β ∈ [1, 2].”
- Finite Sample Comparison of Parametric, Semiparametric, and Wavelet Estimators of Fractional Integration (2005, methodology): “Andrews & Sun (2004) propose a generalization of the local Whittle estimator in the spirit of the BRLPR estimator.”
- Estimating Long Memory in Volatility (2005, unknown): “This was already noticed by Andrews and Sun (2001) in the context of local polynomial approximation.”
- Modified local Whittle estimator for long memory processes in the presence of low frequency (and other) contaminations (2014, methodology): “It adopts techniques used in Andrews and Sun (2004), Hurvich et al. (2005) and Frederiksen et al. (2012) to introduce additive terms in the frequency domain quasi maximum likelihood function to capture the effect of the low frequency contaminations, based on results of Perron and Qu (2010) and…”