Optimal Bandwidth Selection for Forecasting under Parameter Instability.
This article addresses practical issues associated with the use of the local estimator in forecasting models that are affected by parameter instability. We propose an approach to select the bandwidth parameter in the context of out-of-sample forecasting. Derived by minimizing the conditional expecte...
| Published in: | Journal of Financial Econometrics Vol. 24; no. 2; pp. 1 - 32 |
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| Main Authors: | , , , |
| Format: | Article |
| Published: |
Oxford University Press / USA
2026
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=192849866&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 192849866 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 14798409 T2Y jtl: Journal of Financial Econometrics issn: 14798409 maglogo: N pubinfo: dt: 2026 vid: 24 iid: 2 pid: 622 pub: Oxford University Press / USA artinfo: ui: 192849866 10.1093/jjfinec/nbag001 ppf: 1 ppct: 31 formats: tig: atl: Optimal Bandwidth Selection for Forecasting under Parameter Instability. aug: au: Bai, Yu Peng, Bin Shi, Shuping Yao, Wenying affil: Faculty of Finance, City University of Macau, Macau S.A.R., China Department of Econometrics and Business Statistics, Monash University, Caulfield, 3145, Australia Department of Economics, Macquarie University, North Ryde, 2109, Australia Melbourne Business School, University of Melbourne, Carlton, 3053, Australia su: Forecasting Adaptive estimation (Statistics) Monte Carlo method Bonds (Finance) Interest rate forecasting Kernel functions sug: subj: Forecasting Adaptive estimation (Statistics) Monte Carlo method Bonds (Finance) Interest rate forecasting Kernel functions keyword: bandwidth selection bond return predictability C14 C51 C53 copyrightHolder:Oxford University Press copyrightYear:2026 inLanguage:en kernel function local estimator publisher:Oxford University Press sameAs:https://dx.doi.org/10.1093/jjfinec/nbag001 yield curve forecasting bandwidth selection bond return predictability C14 C51 C53 copyrightHolder:Oxford University Press copyrightYear:2026 inLanguage:en kernel function local estimator publisher:Oxford University Press sameAs:https://dx.doi.org/10.1093/jjfinec/nbag001 yield curve forecasting ab: This article addresses practical issues associated with the use of the local estimator in forecasting models that are affected by parameter instability. We propose an approach to select the bandwidth parameter in the context of out-of-sample forecasting. Derived by minimizing the conditional expected end-of-sample loss, the selection procedure is shown to be asymptotically optimal. We also discuss the implications of the choice of kernel functions. The theoretical properties are examined through an extensive Monte Carlo study. Two empirical applications on forecasting excess bond returns and the yield curve demonstrate the superior forecasting performance of the local estimator with the proposed optimal bandwidth selection. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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