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- Publisher Website: 10.1111/jtsa.12474
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Article: Bootstrap Inference for Garch Models by the Least Absolute Deviation Estimation
Title | Bootstrap Inference for Garch Models by the Least Absolute Deviation Estimation |
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Authors | |
Keywords | Bootstrap method exchangeable weights GARCH models generalized bootstrap LAD estimator |
Issue Date | 2020 |
Publisher | Wiley. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1467-9892 |
Citation | Journal of Time Series Analysis, 2020, v. 41 n. 1, p. 21-40 How to Cite? |
Abstract | This article considers the generalized bootstrap method to approximate the least absolute deviation estimation and portmanteau test for generalized autoregressive conditional heteroskedastic models. The generalized bootstrap approach is easy‐to‐implement, and includes many bootstrap methods as special cases, such as Efron's bootstrap, Bayesian bootstrap, and random‐weighting bootstrap. The proposed bootstrap procedure is shown to be asymptotically valid for both estimation and test. The finite‐sample performance is assessed by simulation studies, and its usefulness is illustrated by a real application to the Hang Seng Index. |
Persistent Identifier | http://hdl.handle.net/10722/286689 |
ISSN | 2023 Impact Factor: 1.2 2023 SCImago Journal Rankings: 0.875 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Zhu, Q | - |
dc.contributor.author | Zeng, R | - |
dc.contributor.author | Li, G | - |
dc.date.accessioned | 2020-09-04T13:29:02Z | - |
dc.date.available | 2020-09-04T13:29:02Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Journal of Time Series Analysis, 2020, v. 41 n. 1, p. 21-40 | - |
dc.identifier.issn | 0143-9782 | - |
dc.identifier.uri | http://hdl.handle.net/10722/286689 | - |
dc.description.abstract | This article considers the generalized bootstrap method to approximate the least absolute deviation estimation and portmanteau test for generalized autoregressive conditional heteroskedastic models. The generalized bootstrap approach is easy‐to‐implement, and includes many bootstrap methods as special cases, such as Efron's bootstrap, Bayesian bootstrap, and random‐weighting bootstrap. The proposed bootstrap procedure is shown to be asymptotically valid for both estimation and test. The finite‐sample performance is assessed by simulation studies, and its usefulness is illustrated by a real application to the Hang Seng Index. | - |
dc.language | eng | - |
dc.publisher | Wiley. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1467-9892 | - |
dc.relation.ispartof | Journal of Time Series Analysis | - |
dc.rights | Preprint This is the pre-peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. Postprint This is the peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. | - |
dc.subject | Bootstrap method | - |
dc.subject | exchangeable weights | - |
dc.subject | GARCH models | - |
dc.subject | generalized bootstrap | - |
dc.subject | LAD estimator | - |
dc.title | Bootstrap Inference for Garch Models by the Least Absolute Deviation Estimation | - |
dc.type | Article | - |
dc.identifier.email | Zhu, Q: zhu.qianqian@mail.shufe.edu.cn | - |
dc.identifier.email | Li, G: gdli@hku.hk | - |
dc.identifier.authority | Li, G=rp00738 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1111/jtsa.12474 | - |
dc.identifier.scopus | eid_2-s2.0-85065811259 | - |
dc.identifier.hkuros | 313954 | - |
dc.identifier.volume | 41 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | 21 | - |
dc.identifier.epage | 40 | - |
dc.identifier.isi | WOS:000500797700002 | - |
dc.publisher.place | United Kingdom | - |
dc.identifier.issnl | 0143-9782 | - |