A note on asymptotic inference for FIGARCH(p, d, q) models

Ngai Hang Chan; Chi Tim Ng

doi:10.4310/sii.2011.v4.n2.a16

A note on asymptotic inference for FIGARCH(p, d, q) models

Ngai Hang Chan
, Chi Tim Ng

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

Abstract

Parameters estimation for a FIGARCH(p, d, q) model is studied in this paper. By constructing a compact parameter space Θ satisfying the non-negativity constraints for the FIGARCH model, it is shown that the results of Robinson and Zaffaroni (2006) can be applied to establish the strong consistency and asymptotic normality of the quasi-maximum likelihood (QML) estimator of the FIGARCH model.

Original language	English
Pages (from-to)	227-234
Journal	Statistics and Its Interface
Volume	4
Issue number	2
DOIs	https://doi.org/10.4310/sii.2011.v4.n2.a16
Publication status	Published - 2011
Externally published	Yes

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

Asymptotic normality
Consistency
Fractionally-integrated GARCH model
Nonnegativity
Quasi-maximum likelihood estimator

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title = "A note on asymptotic inference for FIGARCH(p, d, q) models",

abstract = "Parameters estimation for a FIGARCH(p, d, q) model is studied in this paper. By constructing a compact parameter space Θ satisfying the non-negativity constraints for the FIGARCH model, it is shown that the results of Robinson and Zaffaroni (2006) can be applied to establish the strong consistency and asymptotic normality of the quasi-maximum likelihood (QML) estimator of the FIGARCH model.",

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T1 - A note on asymptotic inference for FIGARCH(p, d, q) models

AU - Chan, Ngai Hang

AU - Ng, Chi Tim

N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

PY - 2011

Y1 - 2011

N2 - Parameters estimation for a FIGARCH(p, d, q) model is studied in this paper. By constructing a compact parameter space Θ satisfying the non-negativity constraints for the FIGARCH model, it is shown that the results of Robinson and Zaffaroni (2006) can be applied to establish the strong consistency and asymptotic normality of the quasi-maximum likelihood (QML) estimator of the FIGARCH model.

AB - Parameters estimation for a FIGARCH(p, d, q) model is studied in this paper. By constructing a compact parameter space Θ satisfying the non-negativity constraints for the FIGARCH model, it is shown that the results of Robinson and Zaffaroni (2006) can be applied to establish the strong consistency and asymptotic normality of the quasi-maximum likelihood (QML) estimator of the FIGARCH model.

KW - Asymptotic normality

KW - Consistency

KW - Fractionally-integrated GARCH model

KW - Nonnegativity

KW - Quasi-maximum likelihood estimator

UR - https://www.scopus.com/pages/publications/84864408778

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DO - 10.4310/sii.2011.v4.n2.a16

M3 - RGC 21 - Publication in refereed journal

SN - 1938-7989

VL - 4

SP - 227

EP - 234

JO - Statistics and Its Interface

JF - Statistics and Its Interface

IS - 2

ER -

A note on asymptotic inference for FIGARCH(p, d, q) models

Abstract

Bibliographical note

Research Keywords

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